CN118949358A

CN118949358A - Portable blood pressure reducing treatment system

Info

Publication number: CN118949358A
Application number: CN202410885606.1A
Authority: CN
Inventors: 皮喜田; 唐小军; 刘洪英; 杨奕琳; 程欣怡; 李怡
Original assignee: Chongqing University
Current assignee: Chongqing University
Filing date: 2024-07-03
Publication date: 2024-11-15

Abstract

A portable buck treatment system comprising: wearable sensor module, intelligent terminal; according to the invention, the wearable sensor module is used for monitoring physiological parameters and transmitting the physiological parameters to the intelligent terminal and the cloud platform, and the intelligent terminal takes the breathing frequency as a biofeedback quantity, and guides a user to carry out breathing training in a video and voice breathing guiding mode, so that the portable intelligent terminal is convenient for the user to carry. The invention can select a proper mode according to the requirements of the user, and can meet different application scenes of the user. According to the invention, the current treatment state of the user is judged according to the monitored physiological parameter analysis, and the system is intelligently controlled to guide the treatment of the user. The invention combines the respiratory training treatment and the music treatment with the ischemia pre-adaptation training, and the upper limb is repeatedly, intermittently and noninvasively trained to excite the endogenous protection of the body, generate protective substances and regulate the cell response, thereby achieving the high-efficiency blood pressure reduction treatment effect.

Description

Portable blood pressure reducing treatment system

Technical Field

The invention relates to the field of biofeedback treatment, in particular to a portable blood pressure reduction treatment system.

Background

With the acceleration of life rhythm and the increasing intensity of social competition, the incidence of hypertension and psychological problems is continuously rising. Hypertension is used as an invisible killer for human health, not only directly threatens the physical health of people, but also patients of the hypertension generally bear huge psychological stress, and psychological health problems are increasingly prominent.

In the prior art, through carrying out a hypertension auxiliary depressurization experiment based on slow respiration regulation and control, the biofeedback type treatment based on slow respiration training can effectively reduce hypertension, and experimental data are as follows:

TABLE 1 analysis of Critical hypertension patient slow breathing adjustment data

Respiratory training is a non-drug treatment method with significant therapeutic advantages in terms of hypertension and psychological stress regulation. However, current respiratory training devices have some significant drawbacks in practical applications. Firstly, the problem of inconvenient portability limits the flexibility and popularity of its use; secondly, these devices often only monitor a single physiological parameter and cannot fully reflect the physical condition of the patient; finally, the treatment form is single, the diversity is lacking, and the personalized requirements of different patients are difficult to meet.

Disclosure of Invention

The object of the present invention is to provide a portable blood pressure lowering therapeutic system comprising: wearable sensor module, intelligent terminal.

The wearable sensor module comprises a main control module, a physiological parameter monitoring module and a wireless data transmission module.

And the main control module controls the physiological parameter monitoring module to work according to the instruction signal generated by the intelligent terminal.

The physiological parameter monitoring module is used for monitoring physiological parameter data of a user.

The wireless data transmission module is used for transmitting the physiological parameter data to the intelligent terminal.

The wireless data transmission module is used for transmitting command signals generated by the intelligent terminal to the wearable sensor module.

The intelligent terminal comprises a man-machine interaction module, a depressurization treatment effect evaluation module and a historical data recording module.

The man-machine interaction module is used for generating an instruction signal.

The blood pressure reducing treatment module performs blood pressure reducing treatment on the user according to the instruction signal.

The blood pressure reduction treatment effect evaluation module evaluates the blood pressure reduction treatment effect of the user according to the received physiological parameter data.

The historical data recording module is used for storing treatment data of a user.

Further, the main control module comprises a control module, a data processing module and a data storage module.

The control module controls the physiological parameter monitoring module to work according to the control signal.

The data processing module is used for processing the instruction signal generated by the intelligent terminal and generating a control signal.

The data storage module is used for storing control instruction data of a user.

The control instruction data includes an instruction signal and a control signal.

Further, the physiological parameter monitoring module comprises a respiratory frequency monitoring module, an electrocardio monitoring module, a blood oxygen monitoring module, a blood pressure monitoring module, an electroencephalogram monitoring module and a heart sound monitoring module.

The respiratory rate monitoring module is used for monitoring respiratory signals of a user.

The electrocardio monitoring module is used for monitoring electrocardiosignals of a user.

The blood oxygen monitoring module is used for monitoring blood oxygen signals of a user.

The blood pressure monitoring module is used for monitoring blood pressure signals of a user.

The electroencephalogram monitoring module is used for monitoring electroencephalogram signals of a user.

The heart sound monitoring module is used for monitoring heart sound signals of a user.

Further, the respiratory rate monitoring module comprises a headset type respiratory rate monitoring module, a chest impedance type respiratory rate monitoring module, a chest and abdomen pressure type respiratory rate monitoring module, a pulse type respiratory rate monitoring module and a mattress type respiratory rate monitoring module.

The headset type respiratory rate monitoring module comprises a respiratory sensor module and a headset data processing module.

The breath sensor module includes a microphone sensor module or a thermistor sensor module.

The microphone sensor module is used for capturing sound signals generated when a user breathes through placing the earphone frame at the position of the mouth and the nose of the user, sensing the breathing action of the user and obtaining breathing sound data.

The thermistor sensor module is used for capturing temperature change of a user during breathing by placing the earphone frame at the position of the mouth and the nose of the user, sensing the breathing action of the user and obtaining resistance value data.

When the breath sensor module is a microphone sensor module, the headset data processing module carries out filtering, denoising, feature extraction processing and analysis on the collected breath sound data, and calculates to obtain the breath frequency.

When the respiration sensor module is a thermistor sensor module, the headset data processing module converts the acquired resistance value data into temperature data, and then performs smoothing, filtering, feature extraction processing and analysis on the temperature data, and calculates to obtain the respiration frequency.

The chest impedance type respiratory rate monitoring module comprises a chest impedance sensor module and a chest impedance data processing module.

The chest impedance sensor module is attached to the chest of a user and senses chest impedance changes generated by respiratory motion to obtain chest impedance data.

The chest impedance data processing module is used for carrying out smoothing, filtering, feature extraction processing and analysis on the chest impedance data, and calculating to obtain respiratory rate.

The chest and abdomen pressure type respiratory frequency monitoring module comprises a pressure sensor module, a chest and abdomen belt module and a pressure data processing module.

The pressure sensor module is placed on the chest or the abdomen of a user, and pressure data are obtained by sensing pressure changes generated by the chest and the abdomen during breathing.

The chest and abdomen belt module is used for fixing the pressure sensor module at the chest or abdomen position of the user.

The pressure data processing module performs smoothing, filtering, normalization, feature extraction processing and analysis on the pressure data received from the pressure sensor module, and calculates to obtain the respiratory rate.

The pulse type respiratory rate monitoring module comprises a pulse blood oxygen sensor module and a pulse data processing module.

The pulse blood oxygen sensor module is placed at the fingertips, wrists and earlobes of a user and collects pulse wave signals in respiratory motion.

The pulse data processing module performs smoothing, filtering, feature extraction processing and analysis on the acquired pulse wave signals, and calculates to obtain respiratory rate.

The mattress type respiratory rate monitoring module comprises a piezoelectric film sensor module, a mattress module and a piezoelectric data processing module.

The piezoelectric film sensor module is embedded into the mattress module or the surface of the mattress module, and senses the breathing action of a human body to obtain piezoelectric data.

The mattress module is used as a carrier of the piezoelectric film sensor module.

The piezoelectric data processing module is used for smoothing, filtering, feature extraction processing and analysis on piezoelectric data, and calculating to obtain respiratory frequency.

Further, the wearable sensor module further comprises a respiratory resistance adjusting module and an ischemia pre-adaptation adjusting module.

The respiratory resistance adjusting module comprises one or two of peripheral resistance adjusting modules and an oral-nasal airway resistance adjusting module.

The peripheral resistance adjusting module comprises an elastic band module, a tightness adjusting module and a resistance sensor module.

The elastic band module is worn on the chest and abdomen of a user and is used for providing certain respiratory resistance for the user.

The tightness adjusting module is used for adjusting the tightness or length of the elastic band module so as to change the breathing resistance.

The resistance sensor module is fixed on the elastic band module and is used for sensing the respiratory resistance and resistance change in the respiratory process.

The mouth-nose airway resistance adjusting module comprises a flow sensor module, a ventilation flow control module and a mask module.

The flow sensor module is used for monitoring the gas flow change of the user during the expiration and inspiration movements in real time.

The ventilation flow control module controls ventilation flow by controlling the valve size or the switching time of the airflow regulating valve according to preset ventilation parameters and real-time monitoring feedback of the flow sensor module, so as to achieve respiratory resistance control.

The mask module serves as a carrier of the flow sensor module and is closely attached to the face of a user.

The ischemia pre-adaptation adjusting module comprises a cuff module, an air bag module, an air pressure control module and an air pressure detection module.

The cuff module fixes the air bag module on the arm part and the wrist part of the user. The air pressure control module is fixed on the cuff module.

The airbag module is used for squeezing the arm part and the wrist part of a user.

The air pressure control module is used for controlling the pressurization and the depressurization of the air bag module.

The air pressure control module comprises a timer module and an air pump module.

The timer module is used for calculating the continuous compression time after the air bag module is pressurized to a preset pressure value and for calculating the continuous recovery time after the air bag module is depressurized.

The air pump module comprises an air charging and discharging integrated air pump module, an air charging pump and a discharging valve module.

The inflation and deflation integrated air pump module is used for inflating and pressurizing or deflating and depressurizing the air bag module.

The inflator pump in the inflator pump and the air release valve module is used for inflating and pressurizing the air bag module, and the air release valve in the inflator pump and the air release valve module is used for deflating and decompressing the air bag module.

The air pressure detection module monitors the pressure condition of the air bag module in the pressurizing and depressurizing process through the air pressure sensor and sends the pressure condition to the air pressure control module.

Further, the wearable sensor module further comprises a power management module and a wireless positioning module.

The power management module comprises a power supply module and a charging module.

The power supply module supplies power for the wearable sensor module.

The charging module charges the power supply module.

The wireless positioning module comprises a GPS antenna module or a Beidou satellite antenna module and a positioning signal processing module.

The GPS antenna module is used for receiving or transmitting GPS navigation signals.

The Beidou satellite antenna module is used for receiving or transmitting Beidou satellite communication signals.

And the positioning signal processing module calculates GPS navigation signals or Beidou satellite communication signals and acquires positioning.

Further, the blood pressure reduction treatment module comprises a respiration training treatment module, a music treatment module, an ischemia pre-adaptation training treatment module, a treatment state detection module and a treatment intelligent control module.

The respiratory training treatment module comprises an auditory respiratory guiding module and a visual respiratory guiding module.

The hearing and breathing guiding module plays voice or background music according to the instruction signal, so that a user is prompted to inhale and exhale.

The visual breathing guiding module plays an inspiration and expiration rhythm guiding picture according to the instruction signal, so that a user is prompted to perform inspiration and expiration actions.

The music treatment module comprises a slow rhythm music module and a traditional Chinese medicine five-tone music module.

The slow rhythm music module plays slow rhythm music according to the instruction signal, and the music style of the slow rhythm music comprises classical music, light music and natural music.

The Chinese five-tone music module plays Chinese five-tone music according to the instruction signal, and music debugging is mainly performed by using the characteristic sound and auxiliary by using palace, quotient, angle and feather.

The ischemia pre-adaptation training treatment module performs ischemia pre-adaptation training on the user according to the instruction signal.

The ischemia pre-adaptation training is performed by pressing the arm part or the wrist part of the user by using a single cuff or by pressing the arm part or the wrist part of the user by using a double cuff.

The treatment state detection module is used for analyzing the physiological parameter data monitored by the physiological parameter monitoring module to obtain the current treatment state of the user.

The intelligent treatment control module controls the blood pressure reduction treatment system to carry out blood pressure reduction treatment on the user according to the treatment state detected by the treatment state detection module.

After the user falls asleep or feels tired, the treatment intelligent control module controls the depressurization treatment system to automatically stop working and be in a standby state. When the user wakes up or fatigue is relieved before the set treatment time is over, the treatment intelligent control module controls the depressurization treatment system to automatically start to continue treatment.

In the treatment process, if the physiological parameter data monitored by the physiological parameter monitoring module is abnormal, the treatment intelligent control module stops the operation of the blood pressure reduction treatment system.

Further, the blood pressure reduction treatment effect evaluation module comprises a heart rate variability calculation module, a respiratory sinus arrhythmia calculation module, a fatigue and concentration calculation analysis module, a respiratory guiding effect calculation module, a physiological state calculation module and a treatment effect calculation analysis module.

The heart rate variability calculation module calculates standard deviation of RR intervals according to electrocardiosignals of a user, and further obtains heart rate variability indexes.

The heart rate variability index comprises a heart rate total standard deviation SDNN.

The heart rate total standard deviation SDNN is as follows:

Where i represents RR interval number. N represents the total number of RR intervals. RR _i denotes the length of the ith RR interval. The average of all RR interval lengths is shown.

The heart variability calculation module is used for analyzing heart sound signals and calculating to obtain heart variability indexes.

The heart variability index comprises an amplitude ratio S1/S2 of the first heart sound and the second heart sound, a left ventricular contraction time LVST and a time limit ratio D/S of the diastole and the systole.

The respiratory sinus arrhythmia calculation module calculates respiratory sinus arrhythmia RSA parameters according to the electrocardiosignals and the respiratory signals of the user, and the respiratory sinus arrhythmia RSA parameters are calculated as follows:

where RSA is the respiratory sinus arrhythmia RSA parameter and RR _max is the maximum RR interval during exhalation in one respiratory cycle. RR _mi n is the minimum RR interval during inspiration in one breathing cycle.

The fatigue and concentration calculation and analysis module calculates alpha wave, beta wave and theta wave signals in the brain electric signals according to the brain electric signals of the user, and analyzes the fatigue degree and concentration degree of the user.

The breath guiding effect calculation module comprises an effective training duration ratio analysis module, a target frequency completion duration ratio analysis module and a breath stability analysis module.

The effective training duration ratio analysis module is used for calculating an effective training duration ratio ERTR.

The effective training duration ratio ERTR represents the ratio of effective training time ERTT to total training time TRTT. The effective training time ERTT is an effective slow breathing duration with a respiratory rate of 10 or less.

The target frequency completion time length ratio analysis module is used for calculating a target frequency completion time length ratio TRFR. The target frequency completion duration ratio TRFR is equal to the ratio of the cumulative training duration TFTT to the total training time TRTT to reach the target frequency.

The breath stability analysis module is used for calculating breath stability RS, and the breath stability RS is used for measuring fluctuation conditions of the breath frequency during breath training.

The respiratory guidance effect calculation module calculates and obtains a respiratory guidance effect score RG _score according to the effective training duration ratio ERTR, the target frequency completion duration ratio TRFR and the respiratory stability RS of the user, as follows:

Where σ _RF is the standard deviation of the respiratory rate over a period of time, As the average of respiratory rate over a period of time, b ₁、b₂、b₃ are all weighting factors, and b ₁+b₂+b₃ =1.

The physiological state calculation module calculates a physiological state score PI _score of the user according to the systolic pressure SBP, the diastolic pressure DBP, the heart rate variability SDNN, the respiratory sinus arrhythmia RSA, the heart rate HR, and the blood oxygen saturation SpO2 before and after treatment of the user, as follows:

wherein Δsbp, Δdbp, Δsdnn, Δrsa, Δhr, Δspo2 are the parameter variation values before and after the treatment of systolic pressure SBP, diastolic pressure DBP, heart rate variability SDNN, respiratory sinus arrhythmia RSA, heart rate HR, and blood oxygen saturation SpO2, respectively. SBP ₀、DBP₀、SDNN₀、RSA₀、HR₀、SpO2₀ is the range of parameter variation values before and after treatment of systolic SBP, diastolic DBP, heart rate variability SDNN, respiratory sinus arrhythmia RSA, heart rate HR, blood oxygen saturation SpO2, respectively. c ₁、c₂、c₃、c₄、c₅、c₆ are all weight factors, and c ₁+c₂+c₃+c₄+c₅+c₆ =1.

The treatment effect calculation and analysis module calculates and obtains a blood pressure reduction treatment effect score DP _score according to the respiratory guidance effect score and the physiological state score, as follows:

DP_score＝RG_score*b+PI_score*c (5)

wherein b and c are weight factors, and b+c=1.

The blood pressure reduction treatment effect score is a percentile, and the treatment effect grades are divided into four grades with good middle difference according to the blood pressure reduction treatment effect score.

Further, the man-machine interaction module comprises a sensor module interaction control module, a personalized treatment scheme making module and a data display module.

The sensor module interaction control module is used for generating an instruction signal and controlling the wearable sensor module to work.

The personalized treatment scheme making module comprises a respiratory training treatment scheme module, a music treatment scheme module and an ischemia pre-adaptation training treatment scheme module.

The breath training treatment scheme module comprises a breath training mode selection module and a breath training mode selection module.

The respiratory training mode selection module comprises a simple treatment scheme module and a feedback treatment scheme module.

The easy treatment protocol module directs the user to perform respiratory training based on a constant respiratory guidance frequency or a constant varying respiratory guidance frequency.

And the feedback treatment scheme module is used for guiding the user to adjust the breathing rhythm according to the real-time breathing frequency of the user and carrying out breathing training.

The breath training mode selection module is used for selecting one of an abdominal breath training method, a lip contraction breath training method, a deep breath training method, a rapid-breathing and slow-breathing training method and an active breath circulation technology training method to guide a user to conduct breath training.

The music treatment scheme module is used for setting the types and the tracks of the music treatment of the user.

The ischemia pre-adaptation training treatment scheme module is used for setting a pressure value, a compression time and a recovery time for the ischemia pre-adaptation training of a user.

The data display module is used for displaying treatment data and blood pressure reduction treatment effect evaluation data of a user.

The blood pressure reduction treatment effect evaluation data comprise heart rate variability indexes, respiratory sinus arrhythmia RSA parameters, alpha wave signals in brain electrical signals, beta wave signals in brain electrical signals, theta wave signals in brain electrical signals, respiratory guidance effect scores, physiological state scores, blood pressure reduction treatment effect scores and treatment effect grades.

Further, the portable buck treatment system also includes a cloud platform.

The cloud platform comprises a cloud data storage module and a cloud data processing module.

The cloud data storage module is used for storing analysis results of the cloud data processing module.

And the cloud data processing module receives and analyzes the data transmitted by the intelligent terminal to obtain the data of the cloud platform.

The data of the cloud platform comprise physiological parameter data, control instruction data, treatment data and blood pressure reduction treatment effect evaluation data.

The portable depressurization therapy system provided by the invention has the technical effects that the wearable sensor module is adopted to monitor physiological parameters and transmit the physiological parameters to the intelligent terminal and the cloud platform, and the intelligent terminal takes respiratory frequency as a biofeedback quantity and guides a user to carry out respiratory training in a video and voice respiratory guiding mode, so that the portable depressurization therapy system is convenient for the user to carry; the invention adopts various modes such as headset type, chest impedance type, chest and abdomen pressure type, pulse type, mattress type and the like to monitor the respiratory rate, and can select a proper mode according to the requirements of users to meet different application scenes of the users; according to the invention, peripheral resistance adjustment and oral-nasal airway resistance adjustment are adopted, respiratory resistance is adjusted to assist in respiratory training, the effect of combining resistance training with respiratory training is achieved, and hypertension is further treated and pressure is adjusted; according to the monitored physiological parameter analysis, the current treatment state of the user is judged, and the system is intelligently controlled to guide the treatment of the user; according to the invention, respiratory training treatment and music treatment are adopted, ischemia pre-adaptation training is combined, and repeated, intermittent and noninvasive ischemia training is carried out on the upper limb, so that endogenous protection of the body is stimulated, protective substances are generated, cell response is regulated, and the efficient blood pressure reduction treatment effect is achieved; the invention monitors the physiological parameters of the user such as respiratory rate, electrocardio, blood oxygen, blood pressure, brain electricity, heart sound and the like, calculates heart rate variability, heart rate variability and respiratory sinus arrhythmia index, analyzes the fatigue degree and attention concentration degree of the user, calculates the score of respiratory guiding effect and the score of physiological state, and comprehensively evaluates the hypertension treatment and pressure regulation effect of the user.

Drawings

FIG. 1 is an overall block diagram of a portable buck treatment system according to an embodiment of the present invention;

FIG. 2 is a block diagram of a system incorporating a respiratory resistance adjustment module in an embodiment of the present invention;

FIG. 3 is a block diagram of a system incorporating an ischemic preconditioning module in accordance with an embodiment of the present invention;

FIG. 4 is a diagram of a system architecture incorporating a power management module in an embodiment of the present invention;

FIG. 5 is a system architecture diagram of a wireless location module added in an embodiment of the invention;

FIG. 6 is a block diagram of a master control module in a wearable sensor module;

FIG. 7 is a block diagram of a physiological parameter monitoring module in a wearable sensor module;

FIG. 8 is a block diagram of a respiratory resistance adjustment module in a wearable sensor module;

FIG. 9 is a block diagram of an ischemia pre-adaptation adjustment module in a wearable sensor module;

FIG. 10 is a block diagram of a wireless location module in a wearable sensor module;

FIG. 11 is a block diagram of a human-computer interaction module in an intelligent terminal;

FIG. 12 is a block diagram of a buck treatment module in the intelligent terminal;

FIG. 13 is a block diagram of a step-down treatment effect evaluation module in the intelligent terminal;

FIG. 14 is a block diagram of a respiratory rate monitoring module of the physiological parameter monitoring module;

FIG. 15 is a block diagram of the peripheral resistance adjustment module in the respiratory resistance adjustment module;

FIG. 16 is a block diagram of an oral-nasal airway resistance adjustment module of the respiratory resistance adjustment module;

FIG. 17 is a block diagram of a personalized treatment plan formulation module in a human-machine interaction module;

FIG. 18 is a block diagram of a respiratory training therapy module of the buck therapy module;

FIG. 19 is a block diagram of a music therapy module in a buck therapy module;

FIG. 20 is a basic workflow diagram of a portable buck treatment system;

FIG. 21 is a schematic diagram of a user using a portable buck treatment system;

FIG. 22 is a second schematic diagram of a user using a portable buck treatment system;

FIG. 23 is a third schematic diagram of a user using a portable buck treatment system;

FIG. 24 is a schematic diagram of a user using a portable buck treatment system;

In the drawing the view of the figure, wearable sensor module 1000, main control module 1100, control module 1110, data processing module 1120, data storage module 1130, physiological parameter monitoring module 1200, respiratory rate monitoring module 1210, headset respiratory rate monitoring module 1211, chest impedance respiratory rate monitoring module 1212, chest and abdomen pressure respiratory rate monitoring module 1213, pulse respiratory rate monitoring module 1214, mattress respiratory rate monitoring module 1215, electrocardiograph monitoring module 1220, blood oxygen monitoring module 1230, blood pressure monitoring module 1240, electroencephalogram monitoring module 1250, heart sound monitoring module 1260, wireless data transmission module 1300, respiratory resistance adjustment module 1400, peripheral resistance adjustment module 1410, elastic band module 1411, tightness adjustment module 1412, resistance sensor module 1413, oronasal airway resistance adjustment module 1420, flow sensor module 1421, ventilation flow control module 1422, mask module 1423 ischemia pre-adaptation adjustment module 1500, cuff module 1510, airbag module 1520, barometric control module 1530, barometric detection module 1540, power management module 1600, wireless location module 1700, GPS antenna module 1710, beidou satellite antenna module 1720, location signal processing module 1730, intelligent terminal 2000, human-computer interaction module 2100, sensor module interaction control module 2110, personalized treatment plan formulation module 2120, respiratory training treatment plan module 2121, music treatment plan module 2122, ischemia pre-adaptation training treatment plan module 2123, data display module 2130, depressurization treatment module 2200, respiratory training treatment module 2210, auditory respiration guidance module 2211, visual respiration guidance module 2212, music treatment module 2220, slow tempo music module 2221, traditional Chinese medicine five-tone music module 2222, ischemia pre-adaptation training treatment module 2230, treatment state detection module 2240, the therapy intelligent control module 2250, the depressurization therapy effect evaluation module 2300, the heart rate variability calculation module 2310, the heart rate variability calculation module 2320, the respiratory sinus arrhythmia calculation module 2330, the fatigue concentration calculation analysis module 2340, the respiratory guidance effect calculation module 2350, the physiological state calculation module 2360, the therapy effect calculation analysis module 2370, the history data recording module 2400, the cloud platform 3000, the cloud data storage module 3100, and the cloud data processing module 3200.

Detailed Description

The present invention is further described below with reference to examples, but it should not be construed that the scope of the above subject matter of the present invention is limited to the following examples. Various substitutions and alterations are made according to the ordinary skill and familiar means of the art without departing from the technical spirit of the invention, and all such substitutions and alterations are intended to be included in the scope of the invention.

Example 1

Referring to fig. 1-24, a portable buck treatment system, comprising: wearable sensor module 1000, intelligent terminal 2000.

The wearable sensor module 1000 comprises a main control module 1100, a physiological parameter monitoring module 1200 and a wireless data transmission module 1300.

The main control module 1100 controls the physiological parameter monitoring module 1200 to work according to the instruction signal generated by the intelligent terminal 2000.

The physiological parameter monitoring module 1200 is configured to monitor physiological parameter data of a user.

The wireless data transmission module 1300 is used for transmitting physiological parameter data to the intelligent terminal 2000.

The wireless data transmission module 1300 is configured to transmit an instruction signal generated by the intelligent terminal 2000 to the wearable sensor module 1000.

The intelligent terminal 2000 comprises a man-machine interaction module 2100, a step-down treatment module 2200, a step-down treatment effect evaluation module 2300 and a history data record module 2400.

The man-machine interaction module 2100 is configured to generate an instruction signal.

The step-down treatment module 2200 performs step-down treatment on the user according to the instruction signal.

The blood pressure reduction treatment effect evaluation module 2300 evaluates the blood pressure reduction treatment effect of the user according to the received physiological parameter data.

The history data record module 2400 is configured to store treatment data of a user.

Example 2

The main technical content of the portable blood pressure reduction treatment system is as shown in embodiment 1, and further, the main control module 1100 includes a control module 1110, a data processing module 1120, and a data storage module 1130.

The control module 1110 controls the physiological parameter monitoring module 1200 to operate according to the control signal.

The data processing module 1120 is configured to process the instruction signal generated by the intelligent terminal 2000 to generate a control signal.

The data storage module 1130 is used for storing control instruction data of a user.

Example 3

The main technical content of the portable blood pressure reduction treatment system is as shown in any one of embodiments 1 to 2, and further, the physiological parameter monitoring module 1200 includes a respiratory frequency monitoring module 1210, an electrocardiograph monitoring module 1220, a blood oxygen monitoring module 1230, a blood pressure monitoring module 1240, an electroencephalogram monitoring module 1250, and a heart sound monitoring module 1260.

The respiratory rate monitoring module 1210 is configured to monitor a respiratory signal of a user.

The electrocardiograph monitoring module 1220 is configured to monitor electrocardiographic signals of a user.

The blood oxygen monitoring module 1230 is configured to monitor a blood oxygen signal of a user.

The blood pressure monitoring module 1240 is configured to monitor a blood pressure signal of a user.

The electroencephalogram monitoring module 1250 is used for monitoring electroencephalogram signals of a user.

The heart sound monitoring module 1260 is configured to monitor heart sound signals of a user.

Example 4

The portable blood pressure reduction treatment system has the main technical content as shown in any one of embodiments 1 to 3, and further, the respiratory rate monitoring module 1210 comprises a headset respiratory rate monitoring module 1211, a chest impedance respiratory rate monitoring module 1212, a chest and abdomen pressure respiratory rate monitoring module 1213, a pulse respiratory rate monitoring module 1214 and a mattress respiratory rate monitoring module 1215.

The headset respiratory rate monitoring module 1211 includes a respiratory sensor module and a headset data processing module.

The thoracic impedance respiratory rate monitoring module 1212 includes a thoracic impedance sensor module and a thoracic impedance data processing module.

The chest and abdomen pressure type respiratory rate monitoring module 1213 comprises a pressure sensor module, a chest and abdomen belt module and a pressure data processing module.

The pulse type respiratory rate monitoring module 1214 includes a pulse oximetry sensor module, a pulse data processing module.

The mattress type respiratory rate monitoring module 1215 comprises a piezoelectric film sensor module, a mattress module and a piezoelectric data processing module.

Example 5

The main technical matters of the portable blood pressure reduction treatment system are as shown in any one of embodiments 1 to 4, and further, the wearable sensor module 1000 further comprises a respiratory resistance adjusting module 1400 and an ischemia pre-adaptation adjusting module 1500.

The respiratory resistance adjustment module 1400 includes one or a combination of two of a peripheral resistance adjustment module 1410, an oral-nasal airway resistance adjustment module 1420.

The peripheral resistance adjustment module 1410 includes an elastic band module 1411, a slack adjustment module 1412, and a resistance sensor module 1413.

The elastic band module 1411 is worn on the chest and abdomen of the user to provide a certain respiratory resistance to the user.

The tightness adjustment module 1412 is used to adjust the tightness or length of the elastic band module 1411 to vary the amount of respiratory resistance.

The resistance sensor module 1413 is fixed on the elastic band module 1411, and is used for sensing the magnitude of respiratory resistance and resistance change in the respiratory process.

The oronasal airway resistance adjustment module 1420 includes a flow sensor module 1421, a ventilation flow control module 1422, a mask module 1423.

The flow sensor module 1421 is configured to monitor in real time the change in the flow of gas during the exhalation and inhalation movements of the user.

The ventilation flow control module 1422 controls the ventilation flow by controlling the valve size or the switching time of the airflow regulating valve according to the preset ventilation parameters and the real-time monitoring feedback of the flow sensor module 1421, so as to achieve the control of respiratory resistance.

The mask module 1423 serves as a carrier for the flow sensor module 1421, and is tightly attached to the face of the user.

The ischemia pre-adaptation adjustment module 1500 includes a cuff module 1510, a balloon module 1520, a pneumatic control module 1530, a pneumatic detection module 1540.

The cuff module 1510 secures the airbag module 1520 to the user's arm, wrist. The air pressure control module 1530 is secured to the cuff module 1510.

The airbag module 1520 is used to squeeze the user's arm and wrist.

The air pressure control module 1530 is used for pressurizing and depressurizing the air bag module 1520.

The air pressure control module 1530 includes a timer module, an air pump module.

The timer module is used for calculating a duration compression time after the air bag module 1520 is pressurized to a preset pressure value, and for calculating a duration recovery time after the air bag module 1520 is depressurized.

The inflation and deflation integrated air pump module is used for inflating and pressurizing or deflating and depressurizing the air bag module 1520.

The inflator in the inflator and deflate valve module is used to inflate and pressurize the air bladder module 1520, and the deflate valve in the inflator and deflate valve module is used to deflate and decompress the air bladder module 1520.

The air pressure detecting module 1540 monitors the compression of the air bag module 1520 during the compression and decompression by the air pressure sensor, and transmits the compression to the air pressure control module 1530.

Example 6

The main technical content of the portable blood pressure reduction treatment system is as described in any one of embodiments 1 to 5, further, the wearable sensor module 1000 further includes a power management module 1600 and a wireless positioning module 1700.

The power management module 1600 includes a power supply module and a charging module.

The power supply module supplies power to the wearable sensor module 1000.

The charging module charges the power supply module.

The wireless positioning module 1700 includes a GPS antenna module 1710 or a beidou satellite antenna module 1720, and a positioning signal processing module 1730.

The GPS antenna module 1710 is configured to receive or transmit GPS navigation signals.

The Beidou satellite antenna module 1720 is used for receiving or transmitting Beidou satellite communication signals.

The positioning signal processing module 1730 calculates and obtains a positioning signal of a GPS navigation signal or a beidou satellite communication signal.

Example 7

The main technical content of the portable blood pressure reduction treatment system is as shown in any one of embodiments 1 to 6, and further, the blood pressure reduction treatment module 2200 includes a respiration training treatment module 2210, a music treatment module 2220, an ischemia pre-adaptation training treatment module 2230, a treatment state detection module 2240, and a treatment intelligent control module 2250.

The breath training therapy module 2210 includes an auditory breath guidance module 2211 and a visual breath guidance module 2212.

The auditory breath guide module 2211 plays voice or background music according to the instruction signal, so as to prompt the user to perform inhalation and exhalation actions.

The visual breathing guiding module 2212 plays an inspiration and expiration rhythm guiding picture according to the instruction signal, so as to prompt a user to perform inspiration and expiration actions.

The music treatment module 2220 includes a slow tempo music module 2221 and a chinese five-tone music module 2222.

The slow rhythm music module 2221 plays slow rhythm music according to the instruction signal, and the music style of the slow rhythm music includes classical music, light music and natural music.

The Chinese five-tone music module 2222 plays Chinese five-tone music according to the instruction signal, and music debugging takes the symptomatic sound as the main part and the palace, quotient, angle and feather as the auxiliary parts.

The ischemia pre-adaptation training treatment module 2230 performs ischemia pre-adaptation training on the user according to the instruction signal.

The treatment state detection module 2240 is configured to analyze the physiological parameter data monitored by the physiological parameter monitoring module 1200, so as to obtain a current treatment state of the user.

The intelligent therapeutic control module 2250 controls the blood pressure lowering therapeutic system to perform blood pressure lowering therapy on the user according to the therapeutic state detected by the therapeutic state detection module 2240.

After the user falls asleep or feels tired, the therapeutic intelligent control module 2250 controls the buck therapeutic system to automatically stop working in a standby state. When the user wakes up or fatigue eases before the end of the set treatment time, the treatment intelligent control module 2250 controls the buck treatment system to automatically start continuing the treatment.

During the treatment process, if the physiological parameter data monitored by the physiological parameter monitoring module 1200 is abnormal, the treatment intelligent control module 2250 suspends the operation of the blood pressure reduction treatment system.

Example 8

The portable blood pressure reduction treatment system has the main technical content as shown in any one of embodiments 1 to 7, and further, the blood pressure reduction treatment effect evaluation module 2300 includes a heart rate variability calculation module 2310, a heart rate variability calculation module 2320, a respiratory sinus arrhythmia calculation module 2330, a fatigue and concentration calculation analysis module 2340, a respiratory guidance effect calculation module 2350, a physiological state calculation module 2360, and a treatment effect calculation analysis module 2370.

The heart rate variability calculation module 2310 calculates a standard deviation of the RR interval according to the electrocardiograph signal of the user, so as to obtain a heart rate variability index.

The heart rate total standard deviation SDNN is as follows:

The heart variability calculation module 2320 is configured to analyze the heart sound signal and calculate a heart variability index.

The respiratory sinus arrhythmia calculating module 2330 calculates respiratory sinus arrhythmia RSA parameters according to the electrocardiograph signals and the respiratory signals of the user, as follows:

Where RSA is the respiratory sinus arrhythmia RSA parameter and RR _max is the maximum RR interval during exhalation in one respiratory cycle. RR _min is the minimum RR interval during inspiration in one breathing cycle.

The fatigue and concentration calculation and analysis module 2340 calculates alpha wave, beta wave and theta wave signals in the electroencephalogram signals according to the electroencephalogram signals of the user, and analyzes the fatigue degree and concentration of the user.

The breath guiding effect calculation module 2350 includes an effective training duration ratio analysis module, a target frequency completion duration ratio analysis module, and a breath stability analysis module.

The respiratory guidance effect calculation module 2350 calculates a respiratory guidance effect score RG _score according to the effective training duration ratio ERTR, the target frequency completion duration ratio TRFR, and the respiratory stability RS of the user, as follows:

The physiological state calculating module 2360 calculates a physiological state score PI _score of the user according to the systolic pressure SBP, the diastolic pressure DBP, the heart rate variability SDNN, the respiratory sinus arrhythmia RSA, the heart rate HR, and the blood oxygen saturation SpO2 before and after the treatment of the user, as follows:

The therapeutic effect calculation and analysis module 2370 calculates a blood pressure reduction therapeutic effect score DP _score according to the respiratory guidance effect score and the physiological state score, as follows:

DP_score＝RG_score*b+PI_score*c (5)

wherein b and c are weight factors, and b+c=1.

Example 9

The main technical matters of the portable blood pressure reduction treatment system are as shown in any one of embodiments 1 to 8, and further, the man-machine interaction module 2100 includes a sensor module interaction control module 2110, a personalized treatment scheme formulation module 2120 and a data display module 2130.

The sensor module interaction control module 2110 is configured to generate an instruction signal to control the wearable sensor module 1000 to work.

The personalized treatment regimen formulation module 2120 includes a respiratory training treatment regimen module 2121, a musical treatment regimen module 2122, and an ischemia pre-adaptation training treatment regimen module 2123.

The breath training treatment protocol module 2121 includes a breath training mode selection module and a breath training mode selection module.

The music therapy plan module 2122 is configured to set the type and track of the music therapy of the user.

The ischemia pre-adaptation training treatment scheme module 2123 is used for setting a pressure value, a compression time and a recovery time for the ischemia pre-adaptation training of the user.

The data display module 2130 is used for displaying therapeutic data and blood pressure reduction therapeutic effect evaluation data of the user.

Example 10

A portable blood pressure reduction treatment system, the main technical content of which is as described in any one of embodiments 1 to 9, further comprising a cloud platform 3000.

The cloud platform 3000 includes a cloud data storage module 3100 and a cloud data processing module 3200.

The cloud data storage module 3100 is configured to store an analysis result of the cloud data processing module 3200.

The cloud data processing module 3200 receives and analyzes the data transmitted by the intelligent terminal 2000, and obtains the data of the cloud platform 3000.

The data of the cloud platform 3000 includes physiological parameter data, control instruction data, treatment data, and blood pressure reduction treatment effect evaluation data.

Example 11

Referring to fig. 1 to 24, a portable blood pressure reduction treatment system includes a wearable sensor module 1000, an intelligent terminal 2000, and a cloud platform 3000.

The main control module 1100 includes a control module 1110, a data processing module 1120, and a data storage module 1130; the control module 1110 controls the physiological parameter monitoring module 1200 to work according to the control signal of the intelligent terminal 2000; the data processing module 1120 is configured to receive and process an instruction signal input by the intelligent terminal 2000, and generate a control signal; the data storage module 1130 stores control instruction data of a user.

The physiological parameter monitoring module 1200 includes a respiratory rate monitoring module 1210, the respiratory rate monitoring module 1210 configured to monitor a respiratory rate physiological parameter of a user.

The wireless data transmission module 1300 adopts wireless transmission modes such as Bluetooth, wiFi, zigBee, 4G/5G and the like to transmit physiological parameter data and intelligent terminal 2000 control signal data.

The man-machine interaction module 2100 is configured to generate a control command signal of the wearable sensor module 1000, formulate a treatment plan, and display treatment data.

The blood pressure reduction treatment module 2200 achieves the effects of hypertension treatment and pressure regulation through respiratory training treatment.

The blood pressure reduction treatment effect evaluation module 2300 evaluates the blood pressure reduction treatment effect according to the physiological parameter data of the user training treatment monitoring.

The history data record module 2400 stores each time the user's treatment data.

The cloud data storage module 3100 is configured to store data of a user cloud.

The cloud data processing module 3200 analyzes and processes the data transmitted by the user intelligent terminal 2000.

The physiological parameter monitoring module 1200 further includes an electrocardiograph monitoring module 1220, a blood oxygen monitoring module 1230, and a blood pressure monitoring module 1240.

The electrocardiograph monitoring module 1220 monitors the user's electrocardiograph.

The blood oxygen monitoring module 1230 monitors blood oxygen of the user.

The blood pressure monitoring module 1240 monitors the blood pressure of the user.

The physiological parameter monitoring module 1200 also includes an electroencephalogram monitoring module 1250.

The electroencephalogram monitoring module 1250 monitors the electroencephalogram of the user.

The physiological parameter monitoring module 1200 also includes a heart sound monitoring module 1260.

The heart sound monitoring module 1260 monitors heart sounds of the user.

The respiratory rate monitoring module 1210 includes a headset respiratory rate monitoring module 1211.

The microphone sensor module is placed at the position of the mouth and the nose of the user through the earphone frame, captures sound signals generated when the user breathes, senses the breathing action of the user and obtains breathing sound data.

The thermistor sensor module is placed at the position of the mouth and the nose of the user through the earphone frame, captures the temperature change of the user during breathing, senses the breathing action of the user and obtains resistance value data.

When the breath sensor module is the microphone sensor module, the headset data processing module carries out filtering, denoising, feature extraction processing and analysis on the breath sound data collected by the microphone sensor module, and calculates the breath frequency.

When the respiration sensor module is the thermistor sensor module, the headset data processing module converts the acquired resistance value data into temperature data, and then performs smoothing, filtering, feature extraction processing and analysis on the temperature data to calculate the respiration frequency.

The respiratory rate monitoring module 1210 further includes a chest impedance respiratory rate monitoring module 1212.

The thoracic impedance data processing module performs smoothing, filtering, feature extraction processing and analysis on the thoracic impedance data received from the thoracic impedance sensor module, and calculates a respiratory rate.

The respiratory rate monitoring module 1210 also includes a chest and abdomen pressure respiratory rate monitoring module 1213.

The pressure data processing module performs smoothing, filtering, normalization, feature extraction processing and analysis on the pressure data received from the pressure sensor module, and calculates the respiratory rate.

The respiratory rate monitoring module 1210 further includes a pulse-type respiratory rate monitoring module 1214.

The pulse blood oxygen sensor module is placed at the positions of the fingertips, wrists, earlobes and the like of a user and collects pulse wave signals in respiratory motion.

The pulse data processing module performs smoothing, filtering, feature extraction processing and analysis on the acquired pulse wave signal data, and calculates the respiratory rate.

The respiratory rate monitoring module 1210 also includes a mattress-style respiratory rate monitoring module 1215.

The piezoelectric film sensor module is embedded in the mattress module or on the surface of the mattress module, and senses the breathing action of a human body to obtain piezoelectric data.

The mattress module is used for supporting the weight of a human body and simultaneously serves as a carrier of the piezoelectric film sensor module.

The piezoelectric data processing module performs smoothing, filtering, feature extraction processing and analysis on piezoelectric data received from the piezoelectric film sensor module, and calculates respiratory rate.

The wearable sensor module 1000 further includes a respiratory resistance adjustment module 1400.

The elastic band module 1411 is configured to be worn on the chest and abdomen of a user, and the elastic band provides a certain resistance when the user breathes.

The tightness adjustment module 1412 is used to adjust the tightness or length of the elastic band to vary the resistance during breathing.

The resistance sensor module 1413 is used for being connected to the elastic band module 1411 to sense the respiratory resistance, so that the peripheral resistance can be conveniently adjusted; the resistance sensor module 1413 can sense the resistance change in the breathing process of the user, and the data processing module 1120 analyzes and processes the peripheral resistance data of the breath to calculate the breathing frequency.

The flow sensor module 1421 is configured to monitor the gas flow change of the user during the exhalation and inhalation movements in real time, analyze the gas flow data through the data processing module 1120, and calculate the respiratory rate.

The ventilation flow control module 1422 controls the flow by controlling the valve size or the switching time of the airflow regulating valve according to the preset ventilation parameters and the real-time monitoring feedback of the flow sensor module 1421, so as to achieve the respiratory resistance control.

The mask module 1423 is used as a carrier, and is tightly attached to the face of the user by using a silica gel material.

The wearable sensor module 1000 further includes an ischemia pre-adaptation adjustment module 1500.

The cuff module 1510 fixes the airbag module 1520 to the arm part and the wrist part of the user; the air bag module 1520 and the air pressure control module 1530 are fixed to the cuff module 1510.

The air bag module 1520 is connected to the air pressure control module 1530 and the air pressure detection module 1540, and the air bag module 1520 is pressurized and depressurized by the air pressure control module 1530 to squeeze the arm and wrist of the user.

The timer module is used for counting the duration pressing time after the control air bag is pressed to a preset pressure value and for counting the duration recovery time after the control air bag is depressurized.

The air pump module comprises an air charging and discharging integrated air pump module or an air charging pump and discharging valve module.

The air pump module performs inflation pressurization or deflation depressurization on the air bag module 1520.

The inflator and the deflate valve module inflator are used to inflate and pressurize the airbag module 1520, and the deflate valve is used to deflate and decompress the airbag module 1520.

The air pressure detecting module 1540 monitors the pressure conditions of the air bag module 1520 in the pressurizing and depressurizing process through an air pressure sensor, and sends the pressure conditions to the air pressure control module 1530, and the air pressure detecting module 1540 sends the data monitored by the air pressure sensor to the data processing module 1120 for processing and analyzing, and calculates the blood pressure value.

The buck treatment module 2200 includes a breath training treatment module 2210.

The auditory breath guide module 2211 plays voice or background music according to the received control signal, so as to prompt the user to perform inhalation and exhalation actions.

The visual breathing guiding module 2212 plays the inspiration and expiration rhythm guiding pictures according to the received control signals, so as to prompt the user to perform inspiration and expiration actions.

The buck treatment module 2200 also includes a music treatment module 2220.

The slow rhythm music module 2221 plays slow rhythm music according to the received control signal, the music rhythm is controlled to be 60-80 beats per minute, the music melody is soft and smooth, and the music style covers classical music, light music, natural music and the like.

The traditional Chinese medicine five-tone music module 2222 plays traditional Chinese medicine five-tone music according to the received control signals, music debugging is mainly performed by using the symptoma, the palace, the quotient, the angle and the feather as auxiliary materials, the music melody is easy and cheerful, the music rhythm is smooth and steady, and the music tone color is warm and soft.

The buck treatment module 2200 also includes an ischemia pre-adaptation training treatment module 2230.

The ischemia pre-adaptation training treatment module 2230 controls the wearable sensor module 1000 to work through the human-computer interaction module 2100; after the ischemia pre-adaptation adjusting module 1500 receives the training command, the air pressure control module 1530 controls the air pump module to inflate and pressurize the air bag module 1520, thereby pressing the arm and the wrist of the user to perform ischemia pre-adaptation training; the ischemia pre-adaptation training adopts a single cuff to press the arm part or the wrist part for training, or adopts a double cuff to press the arm part or the wrist part for training; the air pressure detection module 1540 collects pressure data and sends the pressure data to the air pressure control module 1530, the air pressure control module 1530 sends an instruction of stopping inflation to the air pump module and sends a timing instruction to the timer module after inflation and pressurization reach a preset pressure value, the timer module sends an air release instruction to the air pump module and sends a timing instruction to the timer module after timing reaches a preset compression time, the timer module starts timing after air release and depressurization, continues to perform inflation and deflation process after timing reaches a preset recovery time, continuously intermittently extrudes the arm part and the wrist part, and performs ischemia pre-adaptation training and treatment on hypertension.

The buck treatment module 2200 also includes a treatment status detection module 2240.

The treatment state detection module 2240 performs analysis and processing according to the electroencephalogram data, the respiratory frequency data, the electrocardiographic data, and the heart sound data in the physiological parameter monitoring module 1200, so as to determine the current treatment state of the user.

The buck treatment module 2200 also includes a treatment intelligent control module 2250.

The intelligent treatment control module 2250 intelligently controls the system to perform the depressurization treatment on the user according to the user treatment state detected by the treatment state detection module 2240, and the system automatically stops working to be in a standby state after the user falls asleep or fatigues; when the user wakes up or fatigue is relieved before the set treatment time is over, the system automatically starts to continue treatment; and when the physiological parameter is monitored to be abnormal in the treatment process, sending an alarm signal carrying the positioning, and stopping the operation of the treatment system.

The step-down treatment effect evaluation module 2300 includes a heart rate variability calculation module 2310, a heart rate variability calculation module 2320, a respiratory sinus arrhythmia calculation module 2330, a fatigue concentration calculation analysis module 2340, a respiratory guidance effect calculation module 2350, a physiological state calculation module 2360, and a treatment effect calculation analysis module 2370.

The heart rate variability calculation module 2310 calculates a standard deviation of the RR interval according to the electrocardiograph signal of the user to obtain the heart rate variability index.

The heart rate variability index comprises a heart rate total standard deviation SDNN:

Where N represents the total number of RR intervals, RR _i represents the length of the ith RR interval, Representing the average of all RR interval lengths.

The heart variability calculation module 2320 analyzes and processes the heart sound signals to calculate heart variability indexes.

The respiratory sinus arrhythmia calculating module 2330 calculates respiratory sinus arrhythmia RSA parameters according to the electrocardiograph signals and the respiratory signals of the user, and the RSA calculating formula is as follows:

RSA in the formula is a measurement parameter of the influence of respiration on heart rate, and RR _max is the maximum RR interval in the expiration process in one respiration period; RR _mi n is the minimum RR interval during inspiration in one respiratory cycle; Is the average RR interval throughout the respiratory phase.

The effective training duration ratio analysis module is configured to calculate an effective training duration ratio ERTR (Effective Respiratory Training Ratio), where the effective training duration ratio ERTR represents a ratio of an effective training time ERTT (EFFECTIVE RESPIRATORY TRAINING TIME) to a total training time TRTT (Total Respiratory TRAINING TIME), and the effective training time ERTT is an effective slow breathing duration with a respiratory rate of 10 or less.

The Target Frequency completion duration ratio analysis module is configured to calculate a Target Frequency completion duration ratio TRFR (Target Respiratory Frequency Ratio), where the Target Frequency completion duration ratio TRFR is equal to a ratio of a cumulative training duration TFTT (Target Frequency TRAINING TIME) to a total training time TRTT for reaching a Target Frequency.

The breath stability analysis module is used for calculating breath stability RS (Respiratory Stationarity), and the breath stability RS is used for measuring the fluctuation condition of the breath frequency during the breath training period.

The respiratory guidance effect calculation module 2350 calculates a respiratory guidance effect score RG _sc ore according to the effective training duration ratio ERTR, the target frequency completion duration ratio TRFR, and the respiratory stability RS of the user:

The physiological state calculating module 2360 calculates a physiological state score PI _score of the user according to the systolic pressure SBP and the diastolic pressure DBP before and after the treatment of the user, the heart rate variability SDNN, the respiratory sinus arrhythmia RSA, the heart rate HR, and the blood oxygen saturation SpO 2:

Wherein Δsbp, Δdbp, Δsdnn, Δrsa, Δhr, Δspo2 are parameter variation values before and after treatment; SBP ₀、DBP₀、SDNN₀、RSA₀、HR₀、SpO2₀ is the value of the range of variation of the parameters before and after treatment; c ₁、c₂、c₃、c₄、c₅、c₆ are all weight factors, and c ₁+c₂+c₃+c₄+c₅+c₆ =1.

The treatment effect calculation and analysis module 2370 calculates a blood pressure reduction treatment effect score DP _score according to the respiratory guidance effect score and the physiological state score:

DP_score＝RG_score*b+PI_score*c (5)

wherein b and c are weight factors, and b+c=1.

The blood pressure reduction treatment effect score is made in percentage and divided into four grades with excellent middle difference, the treatment effect grade is obtained according to the blood pressure reduction treatment effect score, and the hypertension treatment and pressure regulation effects are evaluated.

The man-machine interaction module 2100 includes a sensor module interaction control module 2110, a personalized treatment plan formulation module 2120, and a data display module 2130.

The sensor module interaction control module 2110 is configured to send a control instruction to the wearable sensor module 1000 by the intelligent terminal 2000, and control the wearable sensor module 1000 to work;

The respiratory training mode selection module comprises a simple treatment scheme module and a feedback treatment scheme module; the simple treatment scheme module is used for a user to select a constant breathing guiding frequency or a constant changing breathing guiding frequency to perform breathing training; the feedback treatment scheme module is used for guiding the user to adjust the breathing rhythm to breathe slowly according to the real-time breathing frequency of the user and carrying out breathing training.

The breath training mode selection module comprises an abdominal type breath training module, a lip contraction breath training module, a deep breath training module, a rapid-breathing and slow-breathing training module and an active breath circulation technology training module; the breath training mode selection module is used for a user to select one of an abdominal breath training method, a lip contraction breath training method, a deep breath training method, a quick-suction slow-breathing training method and an active breath circulation technology training method as a breath training mode to perform breath training.

The music therapy plan module 2122 sets parameters such as the type of music therapy and the track of the user.

The ischemia pre-adaptation training treatment scheme module 2123 sets parameters such as a preset pressure value, a preset compression time, a preset recovery time and the like for performing ischemia pre-adaptation training by a user.

The data display module 2130 displays the treatment data and the blood pressure reduction treatment effect evaluation data of the user.

The wearable sensor module 1000 further includes a power management module 1600 and a wireless positioning module 1700.

The power supply module supplies power to the wearable sensor module 1000 through a button battery or a rechargeable lithium battery.

The charging module comprises an interface charging module and a wireless charging module.

The interface charging module charges the power supply module through an external power plug wire.

The wireless charging module comprises a power source transmitter module, a power source receiver module, a communication and control module and a heat dissipation module.

The power transmitter module comprises an intelligent terminal bracket module, wherein the intelligent terminal bracket module converts electric energy into magnetic field energy, transmits the energy to the power receiver module through electromagnetic induction, and receives the wearable sensor.

The power receiver module receives the magnetic field energy transmitted by the power transmitter module through electromagnetic induction and converts the magnetic field energy into electric energy for charging the wearable sensor module 1000.

The communication and control module is responsible for communication between the power transmitter module and the power receiver module, as well as controlling the charging process.

The heat dissipation module ensures that it will not overheat during wireless charging, thereby protecting the circuit and the wearable sensor module 1000.

Example 12

The main technical content of the portable blood pressure reduction treatment system is as shown in embodiment 11, and further, the wearable sensor module 1000 is worn by a user, and physiological parameters of the user are monitored through the wearable sensor module 1000; the physiological parameter is monitored by the physiological parameter monitoring module 1200.

The physiological parameter monitoring module 1200 includes a respiratory rate monitoring module 1210, an electrocardiograph monitoring module 1220, a blood oxygen monitoring module 1230, a blood pressure monitoring module 1240, an electroencephalogram monitoring module 1250, and a heart sound monitoring module 1260.

The respiratory rate monitoring module 1210 monitors respiratory sounds or respiratory temperature changes at the mouth and nose of the user to obtain respiratory rate through the headset respiratory rate monitoring module 1211.

The electrocardiograph monitoring module 1220 is placed on the chest of the user to monitor the user's electrocardiograph.

The blood oxygen monitoring module 1230 monitors blood oxygen of the wrist part of the user in a wrist strap manner.

The blood pressure monitoring module 1240 monitors the dynamic blood pressure of the user via the electrocardiographic signal and the oximetry pulse signal.

The electroencephalogram monitoring module 1250 monitors the electroencephalogram of the forehead of the user in a single-lead mode.

The heart sound monitoring module 1260 is disposed at a heart site of the user to monitor heart sounds of the user.

The man-machine interaction module 2100 is used for a user to select a respiratory training treatment scheme, wherein the respiratory training treatment scheme is a feedback treatment scheme and a lip-shrinking respiratory training method, the wearable sensor module 1000 is controlled by the sensor module interaction control module 2110 to monitor physiological parameters of the user, the physiological parameters are transmitted to the intelligent terminal 2000 or the cloud platform 3000 through the wireless data transmission module 1300, the intelligent terminal 2000 takes respiratory frequency physiological parameters as biofeedback quantity, a respiratory guidance control signal is generated through a guidance algorithm, and the respiratory training treatment module 2210 is controlled to feed back and guide the user to perform respiratory training in a video and voice respiratory guidance mode; the treatment state detection module 2240 analyzes and processes the brain electrical data, the respiratory frequency data, the electrocardiograph data and the heart sound data, judges the current treatment state of the user, intelligently controls the system to perform the blood pressure reduction treatment on the user, and sends an alarm signal carrying positioning when the physiological parameter is monitored to be abnormal in the treatment process, and stops the operation of the treatment system.

The blood pressure reduction treatment effect evaluation module 2300 calculates heart rate variability index, heart rate variability index and respiratory sinus arrhythmia parameters, and analyzes the fatigue degree and the concentration degree of attention in the training process of the user; calculating a breath guiding effect score RG _score by combining an effective training duration ratio ERTR, a target frequency completion duration ratio TRFR and a breath stability RS; calculating a physiological state score PI _score by combining systolic pressure SBP, diastolic pressure DBP, heart rate variability SDNN, respiratory sinus arrhythmia RSA, heart rate HR and blood oxygen saturation SpO2 before and after treatment of a user; comprehensively evaluating the antihypertensive treatment effect score of the user according to the respiratory guidance effect score and the physiological state score, obtaining the treatment effect grade according to the antihypertensive treatment effect score, and evaluating the hypertension treatment and pressure regulation effects of the user; the cloud platform 3000 analyzes and processes the treatment data of the user to obtain the effect of the training scheme, and the intelligent terminal data display module 2130 calls the treatment data of the user processed by the cloud platform 3000 to display in the form of diagrams, characters and numbers.

Example 13

The respiratory rate monitoring module 1210 monitors pulse signals of the earlobe portion of the user to obtain respiratory rate through the pulse respiratory rate monitoring module 1214.

The blood oxygen monitoring module 1230 monitors blood oxygen at the earlobe of the user in an ear clip manner.

The blood pressure monitoring module 1240 intermittently monitors the blood pressure of the user via a cuff.

The electroencephalogram monitoring module 1250 monitors the electroencephalogram of the forehead of the user in a three-lead mode.

The ischemia pre-adaptation adjustment module 1500 is worn on the user's arms for ischemia pre-adaptation training.

The human-computer interaction module 2100 allows a user to select a respiratory training treatment regimen and an ischemic preconditioning training treatment regimen.

The respiratory training treatment scheme is a feedback treatment scheme and a deep respiratory training method, the wearable sensor module 1000 is controlled by the sensor module interaction control module 2110 to monitor physiological parameters of a user, the physiological parameters are transmitted to the intelligent terminal 2000 or the cloud platform 3000 by the wireless data transmission module 1300, the intelligent terminal 2000 takes respiratory frequency physiological parameters as biofeedback quantity, and generates respiratory guidance control signals by a guidance algorithm to control the respiratory training treatment module 2210 to feedback and guide the user to perform respiratory training in a video and voice respiratory guidance mode.

At the same time of respiratory training, the ischemia pre-adaptation training treatment scheme controls the ischemia pre-adaptation adjusting module 1500 in the wearable sensor module 1000 to work through the sensor module interaction control module 2110 in the intelligent terminal 2000, after the ischemia pre-adaptation adjusting module 1500 receives a training instruction, the air pressure control module 1530 controls the air pump module to inflate and pressurize the air bag module 1520, so as to press the arm of the user to perform ischemia pre-adaptation training, and the ischemia pre-adaptation training adopts a pressing double-arm mode to perform training; the air pressure detection module 1540 collects pressure data and sends the pressure data to the air pressure control module 1530, the air pressure control module 1530 sends an instruction of stopping inflation to the air pump module and sends a preset pressing time timing instruction to the timer module after inflation is pressurized to a preset pressure value, the preset pressing time is 1-15 minutes at any time, the timer module sends an air release instruction to the air pump module and sends a preset recovery time timing instruction to the timer module after timing is up to the preset pressing time, the preset recovery time is 1-15 minutes at any time, the timer module starts timing after air release is depressurized, continues to perform inflation and deflation processes after timing is up to the preset recovery time, and continuously and intermittently extrudes the arm part to perform ischemia pre-adaptation training treatment.

The treatment state detection module 2240 analyzes and processes the brain electrical data, the respiratory frequency data, the electrocardiograph data and the heart sound data, judges the current treatment state of the user, intelligently controls the system to perform the blood pressure reduction treatment on the user, and sends an alarm signal carrying positioning when the physiological parameter is monitored to be abnormal in the treatment process, and stops the operation of the treatment system.

Example 14

The respiratory rate monitoring module 1210 monitors the pressure change of the user's abdomen breathing through the chest and abdomen pressure type respiratory rate monitoring module 1213 to obtain the respiratory rate.

The electrocardiograph monitoring module 1220 is placed on the chest of the user to monitor the user's electrocardiograph. The blood oxygen monitoring module 1230 monitors blood oxygen at the earlobe of the user in an ear clip manner. The blood pressure monitoring module 1240 monitors the dynamic blood pressure of the user via the electrocardiographic signal and the oximetry pulse signal. The electroencephalogram monitoring module 1250 monitors the electroencephalogram of the forehead of the user in a single-lead mode. The heart sound monitoring module 1260 is disposed at a heart site of the user to monitor heart sounds of the user. The ischemia pre-adaptation adjustment module 1500 is worn on the wrist of the user for ischemia pre-adaptation training. The human-computer interaction module 2100 allows a user to select a respiratory training treatment regimen and an ischemic preconditioning training treatment regimen.

The respiratory training treatment scheme is a feedback treatment scheme and an abdominal respiratory training method, the wearable sensor module 1000 is controlled by the sensor module interaction control module 2110 to monitor physiological parameters of a user, the physiological parameters are transmitted to the intelligent terminal 2000 or the cloud platform 3000 by the wireless data transmission module 1300, the intelligent terminal 2000 takes respiratory frequency physiological parameters as biofeedback quantity, and generates respiratory guidance control signals by a guidance algorithm, and the respiratory training treatment module 2210 is controlled to feed back and guide the user to perform respiratory training in a video and voice respiratory guidance mode.

At the same time of respiratory training, the ischemia pre-adaptation training treatment scheme controls the ischemia pre-adaptation adjusting module 1500 in the wearable sensor module 1000 to work through the sensor module interaction control module 2110 in the intelligent terminal 2000, after the ischemia pre-adaptation adjusting module 1500 receives a training instruction, the air pressure control module 1530 controls the air pump module to inflate and pressurize the air bag module 1520, so as to press the wrist of the user to perform ischemia pre-adaptation training, and the ischemia pre-adaptation training adopts a pressing double wrist mode to perform training; the air pressure detection module 1540 collects pressure data and sends the pressure data to the air pressure control module 1530, the air pressure control module 1530 sends an instruction of stopping inflation to the air pump module and sends a preset pressing time timing instruction to the timer module after inflation is pressurized to a preset pressure value, the preset pressing time is 1-15 minutes at any time, the timer module sends an air release instruction to the air pump module and sends a preset recovery time timing instruction to the timer module after timing is up to the preset pressing time, the preset recovery time is 1-15 minutes at any time, the timer module starts timing after air release is depressurized, continues to perform inflation and deflation processes after timing is up to the preset recovery time, and continuously and intermittently extrudes the wrist part to perform ischemia pre-adaptation training treatment.

Example 15

The respiratory rate monitoring module 1210 monitors the impedance change of the chest breath of the user through the chest impedance respiratory rate monitoring module 1212 to obtain the respiratory rate. The electrocardiograph monitoring module 1220 monitors the electrocardiograph of the user by wrist mode. The blood oxygen monitoring module 1230 monitors blood oxygen of the user by wrist mode. The blood pressure monitoring module 1240 monitors the dynamic blood pressure of the user via the electrocardiographic signal and the oximetry pulse signal. The electroencephalogram monitoring module 1250 monitors the electroencephalogram of the forehead of the user in a single-lead mode. The heart sound monitoring module 1260 is disposed at a heart site of the user to monitor heart sounds of the user. The peripheral resistance adjustment module 1410 of the respiratory resistance adjustment module 1400 is worn on the abdomen of the user to assist in respiratory training.

The man-machine interaction module 2100 is used for a user to select a respiratory training treatment scheme, the respiratory training treatment scheme is a feedback treatment scheme and a rapid-breathing and slow-breathing training method, the wearable sensor module 1000 is controlled by the sensor module interaction control module 2110 to monitor physiological parameters of the user, the physiological parameters are transmitted to the intelligent terminal 2000 or the cloud platform 3000 through the wireless data transmission module 1300, the intelligent terminal 2000 takes respiratory frequency physiological parameters as biofeedback quantity, a respiratory guidance control signal is generated through a guidance algorithm, and the respiratory training treatment module 2210 is controlled to feed back and guide the user to perform respiratory training in a video and voice respiratory guidance mode.

Before respiratory training, the tightness or length of the abdomen elastic band is adjusted to reach a preset resistance value by an tightness adjusting module 1412; when the user breathes during breathing training, the elastic band can provide certain resistance to assist breathing training, and the effect of resistance training is achieved.

Claims

1. A portable buck treatment system, comprising: the intelligent terminal comprises a wearable sensor module (1000) and an intelligent terminal (2000);

The wearable sensor module (1000) comprises a main control module (1100), a physiological parameter monitoring module (1200) and a wireless data transmission module (1300);

the main control module (1100) controls the physiological parameter monitoring module (1200) to work according to the instruction signal generated by the intelligent terminal (2000);

the physiological parameter monitoring module (1200) is configured to monitor physiological parameter data of a user.

The wireless data transmission module (1300) is used for transmitting physiological parameter data to the intelligent terminal (2000).

The wireless data transmission module (1300) is used for transmitting an instruction signal generated by the intelligent terminal (2000) to the wearable sensor module (1000);

the intelligent terminal (2000) comprises a man-machine interaction module (2100), a step-down treatment module (2200), a step-down treatment effect evaluation module (2300) and a historical data recording module (2400);

the man-machine interaction module (2100) is used for generating an instruction signal;

the blood pressure reduction treatment module (2200) performs blood pressure reduction treatment on a user according to the instruction signal;

The blood pressure reduction treatment effect evaluation module (2300) evaluates the blood pressure reduction treatment effect of the user according to the received physiological parameter data;

The history data logging module (2400) is configured to store treatment data of a user.

2. The portable buck treatment system of claim 1, wherein the main control module (1100) includes a control module (1110), a data processing module (1120), a data storage module (1130);

The control module (1110) controls the physiological parameter monitoring module (1200) to work according to the control signal;

the data processing module (1120) is used for processing the instruction signal generated by the intelligent terminal (2000) to generate a control signal;

The data storage module (1130) is used for storing control instruction data of a user;

3. The portable blood pressure reduction therapy system of claim 1, wherein the physiological parameter monitoring module (1200) comprises a respiratory rate monitoring module (1210), an electrocardiographic monitoring module (1220), a blood oxygen monitoring module (1230), a blood pressure monitoring module (1240), an electroencephalogram monitoring module (1250), a heart sound monitoring module (1260);

The respiratory rate monitoring module (1210) is configured to monitor a respiratory signal of a user;

the electrocardio monitoring module (1220) is used for monitoring electrocardiosignals of a user;

the blood oxygen monitoring module (1230) is used for monitoring blood oxygen signals of a user;

The blood pressure monitoring module (1240) is used for monitoring a blood pressure signal of a user;

the electroencephalogram monitoring module (1250) is used for monitoring electroencephalogram signals of a user;

the heart sound monitoring module (1260) is for monitoring heart sound signals of a user.

4. The portable buck treatment system of claim 3, wherein the respiratory rate monitoring module (1210) includes a headset respiratory rate monitoring module (1211), a chest impedance respiratory rate monitoring module (1212), a chest-abdominal pressure respiratory rate monitoring module (1213), a pulse respiratory rate monitoring module (1214), a mattress respiratory rate monitoring module (1215);

the headset breathing frequency monitoring module (1211) includes a breathing sensor module, a headset data processing module;

The breath sensor module comprises a microphone sensor module or a thermistor sensor module;

the microphone sensor module captures sound signals generated when a user breathes by placing the earphone frame at the mouth and nose positions of the user, senses the breathing action of the user and obtains breathing sound data;

The thermistor sensor module captures temperature change of a user when breathing by placing the earphone frame at the mouth and nose positions of the user, senses breathing actions of the user and obtains resistance value data;

When the breath sensor module is a microphone sensor module, the headset data processing module carries out filtering, denoising, feature extraction processing and analysis on the collected breath sound data, and calculates to obtain the breath frequency;

When the respiration sensor module is a thermistor sensor module, the headset data processing module converts the acquired resistance value data into temperature data, and then performs smoothing, filtering, feature extraction processing and analysis on the temperature data, and calculates to obtain respiration frequency;

The chest impedance type respiratory rate monitoring module (1212) comprises a chest impedance sensor module and a chest impedance data processing module;

The chest impedance sensor module is attached to the chest of a user and senses chest impedance changes generated by respiratory motion to obtain chest impedance data;

the chest impedance data processing module is used for smoothing, filtering, feature extraction processing and analysis of chest impedance data and calculating to obtain respiratory frequency;

the chest and abdomen pressure type respiratory frequency monitoring module (1213) comprises a pressure sensor module, a chest and abdomen belt module and a pressure data processing module;

The pressure sensor module is placed on the chest or the abdomen of a user, and pressure changes generated by the chest and the abdomen during respiration are sensed to obtain pressure data;

the chest and abdomen belt module is used for fixing the pressure sensor module at the chest or abdomen position of the user;

the pressure data processing module performs smoothing, filtering, normalization, feature extraction processing and analysis on the pressure data received from the pressure sensor module, and calculates to obtain respiratory frequency;

The pulse type respiratory rate monitoring module (1214) comprises a pulse blood oxygen sensor module and a pulse data processing module;

the pulse blood oxygen sensor module is placed at the fingertips, wrists and earlobes of a user and used for collecting pulse wave signals in respiratory motion;

The pulse data processing module performs smoothing, filtering, feature extraction processing and analysis on the acquired pulse wave signals, and calculates to obtain respiratory rate;

the mattress type respiratory frequency monitoring module (1215) comprises a piezoelectric film sensor module, a mattress module and a piezoelectric data processing module;

the piezoelectric film sensor module is embedded into the interior or the surface of the mattress module, senses the breathing action of a human body and obtains piezoelectric data;

The mattress module is used as a carrier of the piezoelectric film sensor module;

5. The portable buck treatment system of claim 1, wherein the wearable sensor module (1000) further includes a respiratory resistance adjustment module (1400), an ischemia pre-adaptation adjustment module (1500);

The respiratory resistance adjustment module (1400) comprises one or two of a peripheral resistance adjustment module (1410) and an oral-nasal airway resistance adjustment module (1420) in combination;

The peripheral resistance adjustment module (1410) comprises an elastic band module (1411), an elastic adjustment module (1412) and a resistance sensor module (1413);

the elastic band module (1411) is worn on the chest and abdomen of a user and is used for providing certain respiratory resistance for the user;

The tightness adjusting module (1412) is used for adjusting the tightness or length of the elastic band module (1411) so as to change the respiratory resistance;

The resistance sensor module (1413) is fixed on the elastic band module (1411) and is used for sensing the respiratory resistance and resistance change in the respiratory process;

The oral-nasal airway resistance adjustment module (1420) includes a flow sensor module (1421), a ventilation flow control module (1422), a mask module (1423);

the flow sensor module (1421) is used for monitoring the gas flow change of the user during the expiration and inspiration movements in real time;

the ventilation flow control module (1422) controls ventilation flow by controlling the valve size or the switching time of the airflow regulating valve according to preset ventilation parameters and real-time monitoring feedback of the flow sensor module (1421) so as to achieve respiratory resistance control;

The mask module (1423) is used as a carrier of the flow sensor module (1421) and is closely attached to the face of a user;

The ischemia pre-adaptation adjusting module (1500) comprises a sleeve belt module (1510), an air bag module (1520), an air pressure control module (1530) and an air pressure detection module (1540);

the cuff module (1510) fixes the airbag module (1520) to the arm and wrist of the user; the air pressure control module (1530) is fixed on the cuff module (1510);

The airbag module (1520) is for squeezing a user's arm portion and wrist portion;

The air pressure control module (1530) is used for performing pressurization and depressurization control on the air bag module (1520);

The air pressure control module (1530) includes a timer module and an air pump module;

the timer module is used for calculating the continuous compression time after the air bag module (1520) is pressurized to a preset pressure value and calculating the continuous recovery time after the air bag module (1520) is depressurized;

the air pump module comprises an air charging and discharging integrated air pump module, an air charging pump and a discharging valve module;

the inflation and deflation integrated air pump module is used for inflating and pressurizing or deflating and decompressing the air bag module (1520);

The inflator pump in the inflator pump and the air release valve module is used for inflating and pressurizing the air bag module (1520), and the air release valve in the inflator pump and the air release valve module is used for deflating and decompressing the air bag module (1520);

The air pressure detection module (1540) monitors the pressure condition of the air bag module (1520) in the pressurizing and depressurizing process through an air pressure sensor, and sends the pressure condition to the air pressure control module (1530).

6. The portable buck treatment system of claim 1, wherein the wearable sensor module (1000) further includes a power management module (1600), a wireless location module (1700);

the power management module (1600) comprises a power supply module and a charging module;

The power supply module supplies power to the wearable sensor module (1000);

the charging module charges the power supply module;

The wireless positioning module (1700) comprises a GPS antenna module (1710) or a Beidou satellite antenna module (1720) and a positioning signal processing module (1730);

The GPS antenna module (1710) is used for receiving or transmitting GPS navigation signals;

the Beidou satellite antenna module (1720) is used for receiving or sending Beidou satellite communication signals;

the positioning signal processing module (1730) calculates GPS navigation signals or Beidou satellite communication signals and obtains positioning.

7. The portable buck treatment system of claim 1, wherein the buck treatment module (2200) includes a respiratory training treatment module (2210), a musical treatment module (2220), an ischemia pre-adaptation training treatment module (2230), a treatment status detection module (2240), a treatment intelligent control module (2250);

the respiratory training treatment module (2210) comprises an auditory respiratory guidance module (2211) and a visual respiratory guidance module (2212);

the hearing breathing guiding module (2211) plays voice or background music according to the instruction signal so as to prompt a user to perform inspiration and expiration actions;

The visual breathing guiding module (2212) plays an inspiration and expiration rhythm guiding picture according to the instruction signal so as to prompt a user to perform inspiration and expiration actions;

the music treatment module (2220) comprises a slow rhythm music module (2221) and a traditional Chinese medicine five-tone music module (2222);

the slow-rhythm music module (2221) plays slow-rhythm music according to the instruction signal, wherein the music style of the slow-rhythm music comprises classical music, light music and natural music;

The traditional Chinese medicine five-tone music module (2222) plays traditional Chinese medicine five-tone music according to the instruction signal, music debugging takes the characteristic tone as a main part and takes palace, quotient, angle and feather as auxiliary parts;

the ischemia pre-adaptation training treatment module (2230) performs ischemia pre-adaptation training on the user according to the instruction signal;

The ischemia pre-adaptation training is performed by pressing the arm part or the wrist part of the user by adopting a single cuff, or by pressing the arm part or the wrist part of the user by adopting a double cuff;

the treatment state detection module (2240) is used for analyzing the physiological parameter data monitored by the physiological parameter monitoring module (1200) to obtain the current treatment state of the user;

The intelligent treatment control module (2250) controls the blood pressure reduction treatment system to perform blood pressure reduction treatment on the user according to the treatment state detected by the treatment state detection module (2240);

After the user falls asleep or feels tired, the treatment intelligent control module (2250) controls the blood pressure reducing treatment system to automatically stop working and be in a standby state; when the user wakes up or fatigue is relieved before the set treatment time is over, the treatment intelligent control module (2250) controls the depressurization treatment system to automatically start to continue treatment;

During the treatment process, if the physiological parameter data monitored by the physiological parameter monitoring module (1200) is abnormal, the treatment intelligent control module (2250) stops the operation of the blood pressure reduction treatment system.

8. The portable buck treatment system of claim 1, wherein the buck treatment effect assessment module (2300) includes a heart rate variability calculation module (2310), a heart variability calculation module (2320), a respiratory sinus arrhythmia calculation module (2330), a fatigue and concentration calculation analysis module (2340), a respiratory guidance effect calculation module (2350), a physiological state calculation module (2360), a treatment effect calculation analysis module (2370);

The heart rate variability calculation module (2310) calculates standard deviation of RR intervals according to electrocardiosignals of a user, so as to obtain heart rate variability indexes;

the heart rate variability index comprises a heart rate total standard deviation SDNN;

The heart rate total standard deviation SDNN is as follows:

Wherein i represents RR interval sequence number; n represents the total number of RR intervals; RR _i denotes the length of the i-th RR interval; Representing the average of all RR interval lengths;

the heart variability calculation module (2320) is used for analyzing heart sound signals and calculating to obtain heart variability indexes;

The heart variability index comprises an amplitude ratio S1/S2 of the first heart sound and the second heart sound, a left ventricular contraction time LVST and a time limit ratio D/S of a diastole period and a systole period;

The respiratory sinus arrhythmia calculation module (2330) calculates respiratory sinus arrhythmia RSA parameters according to the electrocardiosignals and respiratory signals of the user, and the respiratory sinus arrhythmia RSA parameters are calculated as follows:

Wherein RSA is a respiratory sinus arrhythmia RSA parameter, RR _max is the maximum RR interval in the expiration process of one respiratory cycle; RR _min is the minimum RR interval during inspiration in one breathing cycle;

the fatigue and concentration calculation and analysis module (2340) calculates alpha wave, beta wave and theta wave signals in the electroencephalogram signals according to the electroencephalogram signals of the user, and analyzes the fatigue degree and concentration degree of the user;

The breath guiding effect calculation module (2350) comprises an effective training duration ratio analysis module, a target frequency completion duration ratio analysis module and a breath stability analysis module;

The effective training duration ratio analysis module is used for calculating an effective training duration ratio ERTR;

The effective training duration ratio ERTR represents the ratio of effective training time ERTT to total training time TRTT; the effective training time ERTT is an effective slow breathing duration with a breathing frequency of 10 or less;

The target frequency completion time length ratio analysis module is used for calculating a target frequency completion time length ratio TRFR; the target frequency completion duration ratio TRFR is equal to the ratio of the cumulative training duration TFTT to the total training time TRTT to reach the target frequency;

The breath stability analysis module is used for calculating breath stability RS, and the breath stability RS is used for measuring fluctuation conditions of the breath frequency during breath training;

The respiratory guidance effect calculation module (2350) calculates a respiratory guidance effect score RG _score according to the effective training duration ratio ERTR, the target frequency completion duration ratio TRFR and the respiratory stability RS of the user, as follows:

Where σ _RF is the standard deviation of the respiratory rate over a period of time, B ₁、b₂、b₃ are weight factors, and b ₁+b₂+b₃ =1;

The physiological state calculation module (2360) calculates a physiological state score PI _score of the user according to the systolic pressure SBP, the diastolic pressure DBP, the heart rate variability SDNN, the respiratory sinus arrhythmia RSA, the heart rate HR, and the blood oxygen saturation SpO2 before and after treatment of the user, as follows:

Wherein Δsbp, Δdbp, Δsdnn, Δrsa, Δhr, Δspo2 are parameter variation values before and after treatment of systolic pressure SBP, diastolic pressure DBP, heart rate variability SDNN, respiratory sinus arrhythmia RSA, heart rate HR, blood oxygen saturation SpO2, respectively; SBP ₀、DBP₀、SDNN₀、RSA₀、HR₀、SpO2₀ is the parameter variation range value before and after the treatment of the systolic pressure SBP, the diastolic pressure DBP, the heart rate variability SDNN, the respiratory sinus arrhythmia RSA, the heart rate HR and the blood oxygen saturation SpO 2; c ₁、c₂、c₃、c₄、c₅、c₆ are all weight factors, and c ₁+c₂+c₃+c₄+c₅+c₆ =1;

The treatment effect calculation and analysis module (2370) calculates a blood pressure reduction treatment effect score DP _score according to the respiratory guidance effect score and the physiological state score, as follows:

DP_score＝RG_score*b+PI_score*c (5)

Wherein b and c are weight factors, and b+c=1;

9. The portable buck treatment system of claim 1, wherein the human-machine interaction module (2100) includes a sensor module interaction control module (2110), a personalized treatment plan formulation module (2120), a data display module (2130);

the sensor module interaction control module (2110) is used for generating an instruction signal and controlling the wearable sensor module (1000) to work;

The personalized treatment scheme making module (2120) comprises a breathing training treatment scheme module (2121), a music treatment scheme module (2122) and an ischemia pre-adaptation training treatment scheme module (2123);

the breath training treatment scheme module (2121) comprises a breath training mode selection module and a breath training mode selection module;

The respiratory training mode selection module comprises a simple treatment scheme module and a feedback treatment scheme module;

the simple treatment scheme module guides the user to perform respiratory training based on a constant respiratory guidance frequency or a constant varying respiratory guidance frequency;

the feedback treatment scheme module is used for guiding the user to adjust the breathing rhythm according to the real-time breathing frequency of the user and carrying out breathing training;

The breath training mode selection module is used for selecting one of an abdominal breath training method, a lip contraction breath training method, a deep breath training method, a rapid-breathing and slow-breathing training method and an active breath circulation technology training method to guide a user to perform breath training;

the music treatment scheme module (2122) is used for setting the type and the track of the music treatment of the user;

The ischemia pre-adaptation training treatment scheme module (2123) is used for setting a pressure value, a compression time and a recovery time for ischemia pre-adaptation training of a user;

The data display module (2130) is used for displaying treatment data and blood pressure reduction treatment effect evaluation data of a user;

10. The portable buck treatment system of claim 1, further comprising a cloud platform (3000);

the cloud platform (3000) comprises a cloud data storage module (3100) and a cloud data processing module (3200);

The cloud data storage module (3100) is used for storing analysis results of the cloud data processing module (3200);

the cloud data processing module (3200) receives and analyzes data transmitted by the intelligent terminal (2000) to obtain data of the cloud platform (3000);

the data of the cloud platform (3000) comprises physiological parameter data, control instruction data, treatment data and blood pressure reduction treatment effect evaluation data.