CN106901705A - A kind of unaware human Body Physiology Multi-parameter harvester and acquisition method and application - Google Patents
A kind of unaware human Body Physiology Multi-parameter harvester and acquisition method and application Download PDFInfo
- Publication number
- CN106901705A CN106901705A CN201710020196.4A CN201710020196A CN106901705A CN 106901705 A CN106901705 A CN 106901705A CN 201710020196 A CN201710020196 A CN 201710020196A CN 106901705 A CN106901705 A CN 106901705A
- Authority
- CN
- China
- Prior art keywords
- module
- pulse wave
- signal
- body temperature
- person
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 230000037086 body physiology Effects 0.000 title abstract 2
- 238000001514 detection method Methods 0.000 claims abstract description 77
- 230000036760 body temperature Effects 0.000 claims abstract description 68
- 239000008280 blood Substances 0.000 claims abstract description 53
- 210000004369 blood Anatomy 0.000 claims abstract description 50
- 230000036772 blood pressure Effects 0.000 claims abstract description 33
- 238000005259 measurement Methods 0.000 claims abstract description 29
- 238000012545 processing Methods 0.000 claims abstract description 6
- 238000001914 filtration Methods 0.000 claims description 42
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 28
- 229910052760 oxygen Inorganic materials 0.000 claims description 28
- 239000001301 oxygen Substances 0.000 claims description 28
- 230000003321 amplification Effects 0.000 claims description 26
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 26
- 230000035488 systolic blood pressure Effects 0.000 claims description 18
- 230000007613 environmental effect Effects 0.000 claims description 17
- 238000010521 absorption reaction Methods 0.000 claims description 14
- 238000004891 communication Methods 0.000 claims description 13
- 238000012417 linear regression Methods 0.000 claims description 11
- 230000035487 diastolic blood pressure Effects 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 10
- 230000005540 biological transmission Effects 0.000 claims description 8
- 238000009529 body temperature measurement Methods 0.000 claims description 7
- 230000001953 sensory effect Effects 0.000 claims description 7
- 102000001554 Hemoglobins Human genes 0.000 claims description 6
- 108010054147 Hemoglobins Proteins 0.000 claims description 6
- 238000002835 absorbance Methods 0.000 claims description 6
- 230000001965 increasing effect Effects 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 claims description 5
- 230000003287 optical effect Effects 0.000 claims description 5
- 238000002555 auscultation Methods 0.000 claims description 4
- 230000031700 light absorption Effects 0.000 claims description 4
- 206010047141 Vasodilatation Diseases 0.000 claims description 3
- 238000005286 illumination Methods 0.000 claims description 3
- 230000001678 irradiating effect Effects 0.000 claims description 3
- 230000008447 perception Effects 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 230000024883 vasodilation Effects 0.000 claims description 3
- 238000010183 spectrum analysis Methods 0.000 claims description 2
- 238000013461 design Methods 0.000 abstract description 9
- 230000036541 health Effects 0.000 abstract description 9
- 230000006870 function Effects 0.000 abstract description 4
- 238000004445 quantitative analysis Methods 0.000 abstract description 2
- 238000006213 oxygenation reaction Methods 0.000 abstract 1
- 238000012546 transfer Methods 0.000 abstract 1
- 210000001367 artery Anatomy 0.000 description 7
- 210000004204 blood vessel Anatomy 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 7
- 238000011156 evaluation Methods 0.000 description 7
- 230000002159 abnormal effect Effects 0.000 description 5
- 230000001939 inductive effect Effects 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 206010020772 Hypertension Diseases 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 210000001519 tissue Anatomy 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000001575 pathological effect Effects 0.000 description 2
- 230000036581 peripheral resistance Effects 0.000 description 2
- 230000002792 vascular Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000004872 arterial blood pressure Effects 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 230000000747 cardiac effect Effects 0.000 description 1
- 210000000748 cardiovascular system Anatomy 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000009982 effect on human Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 description 1
- 229910052753 mercury Inorganic materials 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- NJPPVKZQTLUDBO-UHFFFAOYSA-N novaluron Chemical compound C1=C(Cl)C(OC(F)(F)C(OC(F)(F)F)F)=CC=C1NC(=O)NC(=O)C1=C(F)C=CC=C1F NJPPVKZQTLUDBO-UHFFFAOYSA-N 0.000 description 1
- 238000002496 oximetry Methods 0.000 description 1
- 230000036513 peripheral conductance Effects 0.000 description 1
- 230000004962 physiological condition Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 210000003491 skin Anatomy 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 210000000707 wrist Anatomy 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Surgery (AREA)
- General Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- Pathology (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Cardiology (AREA)
- Physiology (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychiatry (AREA)
- Signal Processing (AREA)
- Pulmonology (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
Abstract
The present invention relates to a kind of unaware human Body Physiology Multi-parameter harvester and acquisition method and application,Using unaware detection technique,The unaware non-invasive measurement of physiological parameter can be automatically obtained,Design introduces ECG detecting module,Pulse wave measurement module and temperature check module,By the detection of each item data,Using brand-new data processing,Realize blood pressure information,Blood oxygenation information and body temperature information precise acquisition,Wherein,The computing formula that can be carried according to the data that collect and systems soft ware carries out quantitative analysis,Calculate,Accurately assess user's body situation,Have data exception warning function concurrently,The data transfer that will be collected by wireless network simultaneously is to smart machine terminal,Smart machine has the function of real-time dynamic memory and inquiry,It is capable of achieving real time record and the assessment of human body key physiological parameters,Realize being detected on the premise of user's normal life is not influenceed the routine health information of human body,With convenient,Fast,Degree of accuracy advantage higher.
Description
Technical Field
The invention relates to a non-sensing human body multi-physiological parameter acquisition device, an acquisition method and application, and belongs to the technical field of human body physiological sensing detection.
Background
With the continuous improvement of the scientific and technological level and the quality of life, people pay more and more attention to their health conditions nowadays, and the physiological parameters of human bodies such as heart rate, blood pressure, body temperature, blood oxygen saturation and the like can reflect the health conditions of the human bodies, so that the detection of the physiological parameters of the human bodies plays a key role in monitoring the health conditions of the people and finding diseases as soon as possible.
In the conventional physiological parameter detector, one device can only measure one parameter and cannot keep data for a long time, and the data measured historically cannot provide effective data reference for the current physical condition; and the traditional measurement methods are generally slow in measurement speed, and the measurement accuracy is greatly influenced by the measurement environment and measurement personnel, for example, in the traditional blood pressure measuring instrument, the measurement results of different medical personnel are different, and certain deviation exists, so that the traditional measurement methods cannot meet the measurement requirements along with the improvement of science and technology.
Aiming at the condition of human blood pressure, a small part of people can measure the blood pressure regularly or irregularly, and most people usually go to a hospital to check when the body is uncomfortable or even suffers from hypertension. However, in any case, special instruments or equipment must be used, and the patient must subconsciously examine the blood pressure condition, which is not positive to the early detection, prevention and timely treatment of hypertension.
Currently, existing monitoring or detecting equipment needs human intervention, and many patients are in the early stage of illness, for example, when the blood pressure of a human body is abnormal and the human body does not have abnormal reaction, the abnormal condition cannot be reproduced in the process of seeing a doctor, and the correct diagnosis of the doctor is delayed, so that the prior art is not enough in the aspect.
Disclosure of Invention
The invention aims to solve the technical problem of providing a non-sensing human body multi-physiological-parameter acquisition device which adopts a non-sensing detection technology, can automatically realize physiological parameter detection and has the advantages of convenience, rapidness and higher accuracy.
The invention adopts the following technical scheme for solving the technical problems: the invention designs a non-sensing human body multi-physiological parameter acquisition device, which comprises an electrocardio detection module, a pulse wave measurement module, a body temperature detection module, a total amplification and filtering module, a microprocessor, a communication module, a display module and a power supply module, wherein the electrocardio detection module is used for detecting the pulse wave of a human body; the power supply module is respectively connected with each module and supplies power to each module; the electrocardio detection module comprises a first electrode module, a second electrode module and an electrocardio detection processor, wherein the first electrode module and the second electrode module respectively comprise two electrodes, each electrode is respectively and fixedly contacted with the skin of a person to be detected, the four electrodes are respectively divided into two areas according to the first electrode module and the second electrode module, and each electrode is respectively connected with the input end of the electrocardio detection processor; the pulse wave measuring module comprises a dual-band transmitter, a signal receiver and a pulse wave detection processor, wherein the dual-band transmitter and the signal receiver are respectively in fixed contact with the skin of a person to be detected, and the dual-band transmitter and the signal receiver are respectively connected with the input end of the pulse wave detection processor; the body temperature detection module comprises a temperature sensor which is fixedly contacted with the skin of a person to be detected; the output end of the electrocardio detection processor, the output end of the pulse wave detection processor and the output end of the temperature sensor are respectively connected with the input end of the total amplification filtering module; the output end of the total amplification filtering module is connected with the microprocessor; and meanwhile, the microprocessor is connected with the display module through the communication module.
As a preferred technical scheme of the invention: the electrocardio detection module also comprises an electrocardio signal amplifying and filtering module, each electrode in the electrocardio detection module is respectively connected with the input end of the electrocardio signal amplifying and filtering module, and the output end of the electrocardio signal amplifying and filtering module is connected with the input end of the electrocardio detection processor; the pulse wave measuring module also comprises a pulse signal amplifying and filtering module, the dual-waveband transmitter and the signal receiver are respectively connected with the input end of the pulse signal amplifying and filtering module, and the output end of the pulse signal amplifying and filtering module is connected with the input end of the pulse wave detection processor; the body temperature detection module further comprises a body temperature signal amplification and filtering module, the temperature sensor is connected with the input end of the body temperature signal amplification and filtering module, and the output end of the body temperature signal amplification and filtering module is connected with the input end of the total amplification and filtering module.
As a preferred technical scheme of the invention: the device also comprises a storage module connected with the microprocessor.
As a preferred technical scheme of the invention: the temperature sensor is an infrared temperature sensor; the communication module is a wireless communication module.
Compared with the prior art, the non-sensory human body multi-physiological parameter acquisition device adopting the technical scheme has the following technical effects: the non-inductive human body multi-physiological parameter acquisition device adopts a non-inductive detection technology, is designed and introduced with the electrocardio detection module, the pulse wave measurement module and the body temperature detection module, can automatically realize physiological parameter detection, and has the advantages of convenience, rapidness and higher accuracy.
Correspondingly, the technical problem to be solved by the invention is to provide an acquisition method based on a non-sensing human body multi-physiological parameter acquisition device, which can automatically realize non-sensing non-invasive measurement of physiological parameters by adopting a non-sensing detection technology.
The invention adopts the following technical scheme for solving the technical problems: the invention designs an acquisition method based on an imperceptible human body multi-physiological parameter acquisition device, which comprises the following steps:
001, acquiring an electrocardiosignal, a pulse wave signal and a body temperature signal of a person to be detected through the electrocardio detection module, the pulse wave measurement module and the body temperature detection module respectively, processing the electrocardiosignal, the pulse wave signal and the body temperature signal through the total amplification and filtering module respectively, and uploading the processed signals to the microprocessor;
step 002, the microprocessor obtains the blood pressure information of the person to be detected according to the received electrocardio signals and the pulse wave signals, obtains the blood oxygen information of the person to be detected according to the received pulse wave signals, and obtains the body temperature information of the person to be detected according to the received body temperature signals;
and step 003, the microprocessor sends the blood pressure information, the blood oxygen information and the body temperature information of the person to be detected to the display module through the communication module for displaying.
As a preferred technical scheme of the invention: in the step 002, the microprocessor obtains the blood pressure information of the person to be detected according to the received electrocardio signal and the pulse wave signal, and includes the following processes:
the microprocessor obtains an electrocardiosignal and a pulse wave signal, firstly takes the R wave peak value point of each period of the electrocardiosignal as the starting point of the pulse wave conduction time PTT, takes the wave peak value point of the pulse wave signal as the end point of the pulse wave conduction time PTT, and according to the following formula:
pS＝a·PTT+b
obtaining the systolic pressure p of the blood pressure information of the person to be detectedSWherein a and b are constants; and the obtained systolic pressure p is measured by a plurality of groups of PTT values of the pulse wave conduction time and combined with an auscultatory methodSLinear regression is carried out, and then the systolic pressure p in the blood pressure information can be realizedSContinuous measurement of (2);
then, the microprocessor according to the pulse wave characteristic K value and the pulse period T according to the following formula:
fK,T＝mKT+n
establishing a relation equation fK,TWherein m and n are constants;
finally, the microprocessor is responsive to the systolic pressure pSThe time T of the falling edge of the pulse wave in the diastoledEquation of relationship fK,TAccording to the following formula:
obtaining the diastolic pressure p of the blood pressure information of the person to be detecteddWherein, the obtained diastolic pressure p is measured by a plurality of groups of pulse wave conduction time PTT values and combined with the auscultation methoddLinear regression is carried out, and the diastolic pressure p in the blood pressure information can be realizeddIs measured continuously.
As a preferred technical scheme of the invention: in the step 002, the microprocessor obtains the blood oxygen information of the person to be detected according to the received pulse wave signal, including the following processes:
00201 according to the wavelength lambda of the light vertically irradiating the person to be detected, the light intensity I0According to the following formula (11):
obtaining the transmission light intensity I of vertical illumination passing through the human bodyDCWherein the total absorption coefficient, the concentration of the light absorbing substance, and the optical path length of the non-pulsating component in the tissue and the venous blood are expressed as follows0、C0And a combination of L and L,HbO in arterial blood2The absorption coefficient and the concentration of (a),Hb、CHbthe absorbance coefficient and concentration of Hb in arterial blood, respectively;
step (ii) of00202. According to the pulse and the vasodilatation of the artery, the optical path length of the artery blood is increased by delta L from L, and the corresponding transmitted light intensity is increased by IDCChange to IDC-IACThen, for the update of equation (11), equation (12) is obtained as follows:
next, equation (12) is transformed and logarithmized to obtain equation (13) as follows:
00203 using two beams of light with different wavelengths as incident light to perform time-sharing incidence, lambda1And λ2Representing the wavelengths of the two different wavelengths, equation (13) is converted to equation (14) as follows:
step 00204, dividing the formula (14) and the formula (15) to obtain the formula (16) as follows:
00205, performing Michaleline expansion on the left numerator denominator of the formula (16), and neglecting high-order terms to obtain the formula (17) as follows:
step 00206, substituting equation (17) into the formula for blood oxygen saturation:and modified to obtain formula (18) as follows:
00207 according to the wavelength lambda2Corresponding to oxygen and hemoglobin HbO2When the intersection of the absorbance coefficient curves with reduced hemoglobin Hb is selected, i.e.If so, equation (18) is updated to equation (19) as follows:
wherein,representing the absorption coefficient of Hb in arterial blood under red light,indicating HbO in arterial blood under Red light2The light absorption coefficient of (a) is,shows the absorption coefficient, lambda, of Hb in arterial blood under infrared light1Corresponding to red light, λ2Corresponding to the infrared light,all are constant, and are obtained by time domain or frequency domain spectral analysisObtaining;
step 00208 for equation (19), letThen equation (19) is updated to equation (20) as follows:
SpO2＝A-BD (20)
from this, the blood oxygen information SpO of the person to be detected is obtained2Wherein A, B is obtained by calibrating the calculated D value and the actual blood oxygen value through a linear programming,whereinRespectively represent the alternating current component of the red light signal and the alternating current component of the infrared signal in the pulse wave signal,respectively represent the direct current component of the red light signal and the direct current component of the infrared signal in the pulse wave signal, and the direct current components can be obtained by the collected pulse wave signal.
As a preferred technical scheme of the invention: in the step 002, the microprocessor obtains the body temperature information of the person to be detected according to the received body temperature signal, specifically: the microprocessor carries out temperature compensation on the received body temperature signal through a preset temperature field compensation model and the environment temperature obtained in advance, and obtains body temperature information of a person to be detected.
As a preferred technical scheme of the invention: the preset temperature field compensation model is obtained through the following processes:
firstly, recording body temperature measurement data and real body temperature data of a human body under different environmental temperatures, then carrying out multiple linear regression analysis on the various environmental temperatures and the body temperature measurement data and the real body temperature data of the human body corresponding to the various environmental temperatures respectively, and constructing a preset temperature field compensation model.
Compared with the prior art, the acquisition method based on the non-sensory human body multi-physiological parameter acquisition device has the following technical effects: the invention relates to a collecting method of a non-inductive human body multi-physiological parameter collecting device, which adopts a non-inductive detection technology to automatically realize non-inductive non-invasive measurement of physiological parameters, designs and introduces an electrocardio detection module, a pulse wave measurement module and a body temperature detection module, adopts brand new data processing to realize accurate collection of blood pressure information, blood oxygen information and body temperature information through detection of various data, wherein, quantitative analysis and calculation can be carried out according to the collected data and a calculation formula carried by system software, the physical condition of a user can be accurately evaluated, and the device has a data abnormity warning function, simultaneously the collected data is transmitted to an intelligent device terminal through a wireless network, the intelligent device has the functions of real-time dynamic storage and query, the real-time recording and evaluation of key physiological parameters of the human body can be realized, and the daily health information of the human body can be detected on the premise of not influencing the normal life of the user, has the advantages of convenience, quickness and higher accuracy.
Moreover, the technical problem to be solved by the invention is to provide an application of the non-sensing human body multi-physiological parameter acquisition device, the designed acquisition device is applied to a toilet seat, and the non-sensing detection technology is combined, so that the non-sensing non-invasive measurement of physiological parameters can be automatically realized, the accurate acquisition of blood pressure information, blood oxygen information and body temperature information is realized, and the device has the advantages of convenience, rapidness and higher accuracy.
The invention adopts the following technical scheme for solving the technical problems: the invention designs an application of a non-sensing human body multi-physiological parameter acquisition device, which comprises a toilet seat ring, wherein the non-sensing human body multi-physiological parameter acquisition device is arranged on the toilet seat ring, four electrodes in an electrocardio detection module are respectively embedded on the upper surface of the toilet seat ring, the four electrodes are divided into two areas according to a first electrode module and a second electrode module and are fixedly contacted with the skin of a person to be detected, and the surfaces of the four electrodes are flush with the upper surface of the toilet seat ring; the dual-band transmitter and the signal receiver in the pulse wave measuring module are embedded in the upper surface of the toilet seat ring, and the surface of the dual-band transmitter and the surface of the signal receiver are flush with the upper surface of the toilet seat ring; the temperature sensor in the body temperature detection module is embedded in the upper surface of the toilet seat ring, and the surface of the temperature sensor is flush with the upper surface of the toilet seat ring.
Compared with the prior art, the application of the device for collecting the multi-physiological parameters of the non-perception human body has the following technical effects by adopting the technical scheme: the invention is designed aiming at the application of a non-sensing human body multi-physiological parameter acquisition device, the designed acquisition device is applied to the pedestal pan seat ring, and the non-sensing detection technology is combined, so that the non-sensing non-invasive measurement of physiological parameters can be automatically realized, the accurate acquisition of blood pressure information, blood oxygen information and body temperature information is realized, and the invention has the advantages of convenience, rapidness and higher accuracy.
Drawings
FIG. 1 is a schematic block diagram of a non-sensing human multi-physiological parameter acquisition device designed according to the present invention;
FIG. 2 is a flow chart of a blood pressure algorithm applied to the non-perceptual human multi-physiological parameter acquisition device designed in accordance with the present invention;
FIG. 3 is a flow chart of an oximetry algorithm employed by the non-perceptual human multi-physiological parameter acquisition device of the present invention;
FIG. 4 is a flow chart of a body temperature algorithm applied to a non-perceptual human multi-physiological parameter acquisition device designed in accordance with the present invention;
fig. 5 is a flow chart of the intelligent evaluation applied to the non-perception human body multi-physiological parameter acquisition device designed by the invention.
Detailed Description
The following description will explain embodiments of the present invention in further detail with reference to the accompanying drawings.
As shown in figure 1, the invention designs a non-sensing human body multi-physiological parameter acquisition device, which comprises an electrocardio detection module, a pulse wave measurement module, a body temperature detection module, a total amplification and filtering module, a microprocessor, a wireless communication module, a display module, a power supply module and a storage module in practical application; the power supply module is respectively connected with each module and supplies power to each module; the electrocardio detection module comprises a first electrode module, a second electrode module and an electrocardio detection processor, wherein the first electrode module and the second electrode module respectively comprise two electrodes, each electrode is respectively and fixedly contacted with the skin of a person to be detected, the four electrodes are respectively divided into two areas according to the first electrode module and the second electrode module, and each electrode is respectively connected with the input end of the electrocardio detection processor; the pulse wave measuring module comprises a dual-band transmitter, a signal receiver and a pulse wave detection processor, wherein the dual-band transmitter and the signal receiver are respectively in fixed contact with the skin of a person to be detected, and the dual-band transmitter and the signal receiver are respectively connected with the input end of the pulse wave detection processor; the body temperature detection module comprises an infrared temperature sensor which is fixedly contacted with the skin of a person to be detected; the output end of the electrocardio detection processor, the output end of the pulse wave detection processor and the output end of the infrared temperature sensor are respectively connected with the input end of the total amplification filtering module; the output end of the total amplification filtering module is connected with the microprocessor; meanwhile, the microprocessor is connected with the display module through the wireless communication module, and the storage module is connected with the microprocessor; the electrocardio detection module also comprises an electrocardio signal amplification and filtering module, each electrode in the electrocardio detection module is respectively connected with the input end of the electrocardio signal amplification and filtering module, and the output end of the electrocardio signal amplification and filtering module is connected with the input end of the electrocardio detection processor; the pulse wave measuring module also comprises a pulse signal amplifying and filtering module, the dual-waveband transmitter and the signal receiver are respectively connected with the input end of the pulse signal amplifying and filtering module, and the output end of the pulse signal amplifying and filtering module is connected with the input end of the pulse wave detection processor; the body temperature detection module further comprises a body temperature signal amplification and filtering module, the infrared temperature sensor is connected with the input end of the body temperature signal amplification and filtering module, and the output end of the body temperature signal amplification and filtering module is connected with the input end of the total amplification and filtering module. In the practical application process, the designed non-sensing human body multi-physiological parameter acquisition device is applied to the toilet seat, namely the non-sensing human body multi-physiological parameter acquisition device is arranged on the toilet seat, wherein four electrodes in the electrocardio detection module are respectively embedded on the upper surface of the toilet seat, the four electrodes are divided into two areas according to the first electrode module and the second electrode module and are fixedly contacted with the skin of a person to be detected, and the surfaces of the four electrodes are flush with the upper surface of the toilet seat; the dual-band transmitter and the signal receiver in the pulse wave measuring module are embedded in the upper surface of the toilet seat ring, and the surface of the dual-band transmitter and the surface of the signal receiver are flush with the upper surface of the toilet seat ring; the temperature sensor in the body temperature detection module is embedded in the upper surface of the toilet seat ring, and the surface of the temperature sensor is flush with the upper surface of the toilet seat ring.
Aiming at the designed non-sensory human body multi-physiological parameter acquisition device, the invention further designs an acquisition method based on the non-sensory human body multi-physiological parameter acquisition device, and in practical application, the method specifically comprises the following steps:
and 001, acquiring an electrocardiosignal, a pulse wave signal and a body temperature signal of the person to be detected through the electrocardio detection module, the pulse wave measurement module and the body temperature detection module respectively, processing the electrocardiosignals, the pulse wave signal and the body temperature signal through the total amplification and filtering module respectively, and uploading the processed signals to the microprocessor.
And 002, the microprocessor obtains the blood pressure information of the person to be detected according to the received electrocardio signals and the pulse wave signals, obtains the blood oxygen information of the person to be detected according to the received pulse wave signals, and obtains the body temperature information of the person to be detected according to the received body temperature signals.
The magnitude of the systolic pressure is closely related to the transmission time PTT of the pulse wave, and the pulse wave is influenced by the tension degree of the artery vessel wall and the viscosity of blood when being transmitted along the artery vessel. The relationship between the pulse wave transmission velocity and the elasticity of the blood vessels can be expressed by using the Moens-Cottwey formula
In the formula (1), v is the pulse wave velocity, g is the gravitational acceleration, E is the elastic modulus of the blood vessel wall, a is the blood vessel wall thickness, and D is the inner diameter of the blood vessel wall in the equilibrium state.
The elastic modulus of the vessel wall and the pressure of the vessel wall are exponentially related:
in the formula (2), the elastic modulus at zero pressure is defined as the vascular wall pressure and as the systolic pressure. A value for a characteristic quantity of a blood vessel is generally between 0.016 and 0.018.
The pulse wave transit time PTT is the time taken for a pulse wave to travel from one point to another point through the arterial tree, and the velocity of the pulse wave can be expressed as:
s is the distance of pulse wave transmission.
Then the formulas (2) and (3) are substituted into the formula (1)
Deriving the PTT:
the change of the systolic pressure and the transmission time PTT of the pulse wave are known to be in a linear relation and can be simplified to
pS＝a·PTT+b (6)
According to the formula (6), the R wave peak point of each period of the acquired electrocardiosignals is used as the starting point of PTT, the wave peak point of the pulse waves is used as the end point of PTT, the obtained systolic pressure is linearly regressed by combining an auscultation method through a plurality of groups of measured PTT values, and then the continuous measurement of the systolic pressure can be realized.
As shown in fig. 2, in the above step 002, the microprocessor obtains the blood pressure information of the person to be detected according to the received electrocardio signal and pulse wave signal, and includes the following processes:
the microprocessor obtains an electrocardiosignal and a pulse wave signal, firstly takes the R wave peak value point of each period of the electrocardiosignal as the starting point of the pulse wave conduction time PTT, takes the wave peak value point of the pulse wave signal as the end point of the pulse wave conduction time PTT, and according to the following formula:
pS＝a·PTT+b
obtaining the systolic pressure p of the blood pressure information of the person to be detectedSWherein a and b are constants; and the obtained systolic pressure p is measured by a plurality of groups of PTT values of the pulse wave conduction time and combined with an auscultatory methodSLinear regression is carried out, and then the systolic pressure p in the blood pressure information can be realizedSContinuous measurement of (2);
according to the following relation between the diastolic pressure and the systolic pressure in the blood pressure information:
in the formula, TdThe time of the falling edge of the pulse wave in the diastole, R represents the peripheral resistance of the blood vessel, and C represents the compliance of the blood vessel;
according to the pulse characteristic K value theory, establishing a relation equation of peripheral vascular resistance R and vascular compliance C with respect to the pulse wave characteristic K value and the pulse period T, and recording as fK,TThen the above formula can be expressed as:
the pulse wave characteristic K value is closely related to cardiac output, peripheral resistance, and the like in the cardiovascular system. Defining the pulse wave characteristic quantity K value as follows according to the pulse wave waveform volume change:
in the formula, pmMean arterial pressure; in the actual calculation, the wave peak value of the pulse wave signal is taken as pSWith trough value as pdThe average amplitude of the signal in one period is taken as pmCalculating and converting a pulse wave characteristic quantity K value, and finding that the RC value and the KT value of the measured object are linearly related by analyzing data to obtain fK,TThe linear equation of (a):
fK,T＝mKT+n
then, the microprocessor according to the pulse wave characteristic K value and the pulse period T according to the following formula:
fK,T＝mKT+n
establishing a relation equation fK,TWhich isIn (1), m and n are constants;
finally, the microprocessor is responsive to the systolic pressure pSThe time T of the falling edge of the pulse wave in the diastoledEquation of relationship fK,TAccording to the following formula:
obtaining the diastolic pressure p of the blood pressure information of the person to be detecteddWherein, the obtained diastolic pressure p is measured by a plurality of groups of pulse wave conduction time PTT values and combined with the auscultation methoddLinear regression is carried out, and the diastolic pressure p in the blood pressure information can be realizeddIs measured continuously.
The blood oxygen saturation detection is based on the principle that the absorption amount of light by arterial blood changes along with the fluctuation of arteries, and in the transmission type blood oxygen saturation detection, when artery blood vessels in a light-transmitting area pulsate, the absorption amount of light by arterial blood changes along with the fluctuation of the artery blood vessels, and the detection is called as a pulsating component or an Alternating Current (AC); while other tissues, such as skin, muscle, bone and venous blood, have a constant and constant absorption of light, called Direct Current (DC).
As shown in fig. 3, in step 002, the microprocessor obtains the blood oxygen information of the person to be detected according to the received pulse wave signal, which includes the following steps:
00201 according to the wavelength lambda of the light vertically irradiating the person to be detected, the light intensity I0According to the following formula (11):
obtaining the transmission light intensity I of vertical illumination passing through the human bodyDCWherein the total absorption coefficient, the concentration of the light absorbing substance, and the optical path length of the non-pulsating component in the tissue and the venous blood are expressed as follows0、C0And a combination of L and L,HbO in arterial blood2The absorption coefficient and the concentration of (a),Hb、CHbthe absorbance coefficient and concentration of Hb in arterial blood, respectively;
00202, increasing the light path length of arterial blood by delta L according to the pulse and vasodilatation of arterial blood, and correspondingly increasing the transmitted light intensity by IDCChange to IDC-IACThen, for the update of equation (11), equation (12) is obtained as follows:
next, equation (12) is transformed and logarithmized to obtain equation (13) as follows:
00203 using two beams of light with different wavelengths as incident light to perform time-sharing incidence, lambda1And λ2Representing the wavelengths of the two different wavelengths, equation (13) is converted to equation (14) as follows:
step 00204, dividing the formula (14) and the formula (15) to obtain the formula (16) as follows:
00205, performing Michaleline expansion on the left numerator denominator of the formula (16), and neglecting high-order terms to obtain the formula (17) as follows:
step 00206, substituting equation (17) into the formula for blood oxygen saturation:and modified to obtain formula (18) as follows:
00207 according to the wavelength lambda2Corresponding to oxygen and hemoglobin HbO2When the intersection of the absorbance coefficient curves with reduced hemoglobin Hb is selected, i.e.If so, equation (18) is updated to equation (19) as follows:
wherein,representing the absorption coefficient of Hb in arterial blood under red light,indicating HbO in arterial blood under Red light2The light absorption coefficient of (a) is,shows the absorption coefficient, lambda, of Hb in arterial blood under infrared light1Corresponding to red light, λ2Corresponding to the infrared light,all are constants, and are obtained by adopting a time domain or frequency domain spectral analysis method; in practical application, 660nm red light and 940nm infrared light-emitting diodes with small scattering effect on human bodies are selected as test light sources.
Step 00208 for equation (19), letThen equation (19) is updated to equation (20) as follows:
SpO2＝A-BD (20)
from this, the blood oxygen information SpO of the person to be detected is obtained2Wherein A, B is obtained by calibrating the calculated D value and the actual blood oxygen value through a linear programming,whereinRespectively represent the alternating current component of the red light signal and the alternating current component of the infrared signal in the pulse wave signal,respectively represent the direct current component of the red light signal and the direct current component of the infrared signal in the pulse wave signal, and the direct current components can be obtained by the collected pulse wave signal.
The invention designs a non-sensing human body multi-physiological parameter acquisition device, because the non-contact measurement is adopted, the infrared sensor measures the body surface temperature of a human body, the body surface temperature of the human body is easily influenced by the environmental temperature, the body surface temperatures measured by different environmental temperatures are different, in order to reduce the influence of the environmental temperature, the infrared sensor is designed to measure the temperature under the condition of different environmental temperatures, the measurement data under different environmental temperatures and the real temperature data of the human body are recorded, the measured data are analyzed and compared, a temperature field compensation model is established, the body temperature of the human body is compensated under different environmental temperatures, and the high-precision measurement is achieved.
As shown in fig. 4, in step 002, the microprocessor obtains the body temperature information of the person to be detected according to the received body temperature signal, specifically: the microprocessor carries out temperature compensation on the received body temperature signal through a preset temperature field compensation model and the pre-obtained environmental temperature to obtain body temperature information of a person to be detected; the preset temperature field compensation model is obtained through the following processes:
firstly, recording body temperature measurement data and real body temperature data of a human body under different environmental temperatures, then carrying out multiple linear regression analysis on the various environmental temperatures and the body temperature measurement data and the real body temperature data of the human body corresponding to the various environmental temperatures respectively, and constructing a preset temperature field compensation model.
The process is characterized in that a series of experimental researches are carried out on the temperature measuring effect of the infrared thermometer at different environmental temperatures. The experimental scheme is that under the indoor environment of no wind, the infrared measurement distance is fixed to be 2cm invariable, a plurality of temperature nodes are arranged from 15 degrees to 30 degrees in the indoor environment to collect data, a human body infrared temperature measurement system is used for measuring the current environment temperature and the body surface temperature of human legs under each temperature node, a mercury thermometer is used for measuring the armpit temperature of a human body, and the data collected each time are recorded.
The analysis finds that the environment temperature and the real temperature of the human body have strong correlation (r is more than 0.9), and the real temperature values of the human body under different environment temperatures can be accurately reflected by using a linear regression method.
The assumed ambient temperature, the assumed body surface temperature and the assumed real human body temperature are x ═ x respectively1,x2,x3,···xN}、y＝{y1,y2,y3,···yNZ ═ z1,z2,z3,···zNAnd establishing a multiple linear regression model among three parameter sequences, namely:
z＝a+bx+cy (21)
wherein a, b and c are regression coefficients, and the following can be obtained by a least square method:
and step 003, the microprocessor sends the blood pressure information, the blood oxygen information and the body temperature information of the person to be detected to a display module through the wireless communication module for displaying.
The invention designs a non-sensory human body multi-physiological parameter acquisition device which is provided with analysis software for identifying the health condition of a user, can set three physiological parameters, normal parameter range values and pathological parameter range values according to the existing data values of the health condition, the non-health condition, the typical case characteristic and the like, and realizes the objective evaluation of the human body physiological condition by combining the characteristics of self-organization, self-learning, self-adaption and nonlinear mapping based on an artificial neural network comprehensive evaluation method.
As shown in fig. 5, an Artificial Neural Network (ANN) is a model for establishing a special nonlinear relationship between a weight description variable and an object, and a judgment analysis of the object must be performed through a learning or training process. Aiming at the human physiological parameter evaluation of the example, the normal range value of a certain human physiological parameter is set as xi～[A,B]Then the physiological parameterThe average values are:
the physiological parameter deviation values are:
the normal parameter limit deviation values are:
when P is presenti≤PmIf so, indicating that the physiological parameters of the human body are normal;
when P is presenti>PmAnd if so, indicating that the physiological parameters of the human body are abnormal.
The intelligent evaluation system can judge the current physical condition of the user according to various physiological data of the user detected in real time, evaluate the physical health of the user, for example, the conditions of hypertension, abnormal blood oxygen, high body temperature and the like, and can timely find and give related prompts; if the user is found to have obvious pathological features or diseases for a long time, the result of recent evaluation can be automatically generated and analyzed to be pushed to the user intelligent terminal, warning and alarming are carried out on a software interface, the user can download all recent physiological data through the client, and reference is provided for the user to carry out more comprehensive examination and diagnosis and treatment of medical staff in a hospital.
In practical application, compared with the traditional device which can only measure pulse wave signals of fingers and wrists of a human body, the device can accurately measure the pulse wave signals of thick fat parts of the human body, establishes a collection and processing model of optical signals at the thick fat parts, and meanwhile, the device is arranged on the surface of a toilet bowl, so that errors caused by artificial movement to the measurement result can be avoided, the continuous measurement of the signals is realized, and the reliability and the accuracy of the system are improved.
The embodiments of the present invention have been described in detail with reference to the drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (10)
1. The utility model provides a no perception human many physiological parameters collection system which characterized in that: the pulse wave measuring device comprises an electrocardio detecting module, a pulse wave measuring module, a body temperature detecting module, a total amplifying and filtering module, a microprocessor, a communication module, a display module and a power supply module; the power supply module is respectively connected with each module and supplies power to each module; the electrocardio detection module comprises a first electrode module, a second electrode module and an electrocardio detection processor, wherein the first electrode module and the second electrode module respectively comprise two electrodes, each electrode is respectively and fixedly contacted with the skin of a person to be detected, the four electrodes are respectively divided into two areas according to the first electrode module and the second electrode module, and each electrode is respectively connected with the input end of the electrocardio detection processor; the pulse wave measuring module comprises a dual-band transmitter, a signal receiver and a pulse wave detection processor, wherein the dual-band transmitter and the signal receiver are respectively in fixed contact with the skin of a person to be detected, and the dual-band transmitter and the signal receiver are respectively connected with the input end of the pulse wave detection processor; the body temperature detection module comprises a temperature sensor which is fixedly contacted with the skin of a person to be detected; the output end of the electrocardio detection processor, the output end of the pulse wave detection processor and the output end of the temperature sensor are respectively connected with the input end of the total amplification filtering module; the output end of the total amplification filtering module is connected with the microprocessor; and meanwhile, the microprocessor is connected with the display module through the communication module.
2. The device for collecting the multi-physiological parameters of the non-sensing human body according to claim 1, wherein: the electrocardio detection module also comprises an electrocardio signal amplifying and filtering module, each electrode in the electrocardio detection module is respectively connected with the input end of the electrocardio signal amplifying and filtering module, and the output end of the electrocardio signal amplifying and filtering module is connected with the input end of the electrocardio detection processor; the pulse wave measuring module also comprises a pulse signal amplifying and filtering module, the dual-waveband transmitter and the signal receiver are respectively connected with the input end of the pulse signal amplifying and filtering module, and the output end of the pulse signal amplifying and filtering module is connected with the input end of the pulse wave detection processor; the body temperature detection module further comprises a body temperature signal amplification and filtering module, the temperature sensor is connected with the input end of the body temperature signal amplification and filtering module, and the output end of the body temperature signal amplification and filtering module is connected with the input end of the total amplification and filtering module.
3. The device for collecting the multi-physiological parameters of the non-sensing human body according to claim 1, wherein: the device also comprises a storage module connected with the microprocessor.
4. The device for collecting the multi-physiological parameters of the non-sensing human body according to claim 1, wherein: the temperature sensor is an infrared temperature sensor; the communication module is a wireless communication module.
5. An acquisition method of the non-sensory human body multi-physiological parameter acquisition device according to any one of claims 1 to 4, characterized by comprising the following steps:
001, acquiring an electrocardiosignal, a pulse wave signal and a body temperature signal of a person to be detected through the electrocardio detection module, the pulse wave measurement module and the body temperature detection module respectively, processing the electrocardiosignal, the pulse wave signal and the body temperature signal through the total amplification and filtering module respectively, and uploading the processed signals to the microprocessor;
step 002, the microprocessor obtains the blood pressure information of the person to be detected according to the received electrocardio signals and the pulse wave signals, obtains the blood oxygen information of the person to be detected according to the received pulse wave signals, and obtains the body temperature information of the person to be detected according to the received body temperature signals;
and step 003, the microprocessor sends the blood pressure information, the blood oxygen information and the body temperature information of the person to be detected to the display module through the communication module for displaying.
6. The collecting method of claim 5, wherein in step 002, the microprocessor obtains the blood pressure information of the person to be detected according to the received electrocardio signals and pulse wave signals, and comprises the following steps:
the microprocessor obtains an electrocardiosignal and a pulse wave signal, firstly takes the R wave peak value point of each period of the electrocardiosignal as the starting point of the pulse wave conduction time PTT, takes the wave peak value point of the pulse wave signal as the end point of the pulse wave conduction time PTT, and according to the following formula:
pS＝a·PTT+b
obtaining the systolic pressure p of the blood pressure information of the person to be detectedSWherein a and b are constants; and the obtained systolic pressure p is measured by a plurality of groups of PTT values of the pulse wave conduction time and combined with an auscultatory methodSLinear regression is carried out, and then the systolic pressure p in the blood pressure information can be realizedSContinuous measurement of (2);
then, the microprocessor according to the pulse wave characteristic K value and the pulse period T according to the following formula:
fK,T＝mKT+n
establishing a relation equation fK,TWherein m and n are constants;
finally, the microprocessor is responsive to the systolic pressure pSThe time T of the falling edge of the pulse wave in the diastoledEquation of relationship fK,TAccording to the following formula:
obtaining the diastolic pressure p of the blood pressure information of the person to be detecteddWherein, the obtained diastolic pressure p is measured by a plurality of groups of pulse wave conduction time PTT values and combined with the auscultation methoddLinear regression is carried out, and the diastolic pressure p in the blood pressure information can be realizeddIs measured continuously.
7. The method as claimed in claim 5, wherein in step 002, the microprocessor obtains the blood oxygen information of the person to be detected according to the received pulse wave signal, which comprises the following steps:
00201 according to the wavelength lambda of the light vertically irradiating the person to be detected, the light intensity I0According to the following formula (11):
obtaining the transmission light intensity I of vertical illumination passing through the human bodyDCWherein the total absorption coefficient, the concentration of the light absorbing substance, and the optical path length of the non-pulsating component in the tissue and the venous blood are expressed as follows0、C0And a combination of L and L,HbO in arterial blood2The absorption coefficient and the concentration of (a),Hb、CHbthe absorbance coefficient and concentration of Hb in arterial blood, respectively;
00202, increasing the light path length of arterial blood by delta L according to the pulse and vasodilatation of arterial blood, and correspondingly increasing the transmitted light intensity by IDCChange to IDC-IACThen, for the update of equation (11), equation (12) is obtained as follows:
next, equation (12) is transformed and logarithmized to obtain equation (13) as follows:
00203 using two beams of light with different wavelengths as incident light to perform time-sharing incidence, lambda1And λ2Representing the wavelengths of the two different wavelengths, equation (13) is converted to equation (14) as follows:
step 00204, dividing the formula (14) and the formula (15) to obtain the formula (16) as follows:
00205, performing Michaleline expansion on the left numerator denominator of the formula (16), and neglecting high-order terms to obtain the formula (17) as follows:
step 00206, substituting equation (17) into the formula for blood oxygen saturation:and modified to obtain formula (18) as follows:
00207 according to the wavelength lambda2Corresponding to oxygen and hemoglobin HbO2When the intersection of the absorbance coefficient curves with reduced hemoglobin Hb is selected, i.e.If so, equation (18) is updated to equation (19) as follows:
wherein,representing the absorption coefficient of Hb in arterial blood under red light,indicating HbO in arterial blood under Red light2The light absorption coefficient of (a) is,shows the absorption coefficient, lambda, of Hb in arterial blood under infrared light1Corresponding to red light, λ2Corresponding to the infrared light, all are constants, and are obtained by adopting a time domain or frequency domain spectral analysis method;
step 00208 for equation (19), letThen equation (19) is updated to equation (20) as follows:
SpO2＝A-BD (20)
from this, the blood oxygen information SpO of the person to be detected is obtained2Wherein A, B is obtained by calibrating the calculated D value and the actual blood oxygen value through a linear programming,whereinRespectively represent the alternating current component of the red light signal and the alternating current component of the infrared signal in the pulse wave signal,respectively represent the direct current component of the red light signal and the direct current component of the infrared signal in the pulse wave signal, and the direct current components can be obtained by the collected pulse wave signal.
8. The collecting method according to claim 5, wherein in step 002, the microprocessor obtains the body temperature information of the person to be detected according to the received body temperature signal, specifically: the microprocessor carries out temperature compensation on the received body temperature signal through a preset temperature field compensation model and the environment temperature obtained in advance, and obtains body temperature information of a person to be detected.
9. The acquisition method based on the sensorless human multi-physiological parameter acquisition device according to claim 8, wherein the preset temperature field compensation model is obtained by the following processes:
firstly, recording body temperature measurement data and real body temperature data of a human body under different environmental temperatures, then carrying out multiple linear regression analysis on the various environmental temperatures and the body temperature measurement data and the real body temperature data of the human body corresponding to the various environmental temperatures respectively, and constructing a preset temperature field compensation model.
10. The use of the non-sensory human multi-physiological parameter acquisition device according to any one of claims 1 to 4, wherein: the device is characterized by further comprising a toilet seat ring, wherein the non-sensing human body multi-physiological parameter acquisition device is arranged on the toilet seat ring, four electrodes in the electrocardio detection module are respectively embedded in the upper surface of the toilet seat ring, the four electrodes are divided into two areas according to a first electrode module and a second electrode module and are fixedly contacted with the skin of a person to be detected, and the surfaces of the four electrodes are flush with the upper surface of the toilet seat ring; the dual-band transmitter and the signal receiver in the pulse wave measuring module are embedded in the upper surface of the toilet seat ring, and the surface of the dual-band transmitter and the surface of the signal receiver are flush with the upper surface of the toilet seat ring; the temperature sensor in the body temperature detection module is embedded in the upper surface of the toilet seat ring, and the surface of the temperature sensor is flush with the upper surface of the toilet seat ring.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710020196.4A CN106901705A (en) | 2017-01-11 | 2017-01-11 | A kind of unaware human Body Physiology Multi-parameter harvester and acquisition method and application |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710020196.4A CN106901705A (en) | 2017-01-11 | 2017-01-11 | A kind of unaware human Body Physiology Multi-parameter harvester and acquisition method and application |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106901705A true CN106901705A (en) | 2017-06-30 |
Family
ID=59206946
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710020196.4A Pending CN106901705A (en) | 2017-01-11 | 2017-01-11 | A kind of unaware human Body Physiology Multi-parameter harvester and acquisition method and application |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106901705A (en) |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107582030A (en) * | 2017-08-25 | 2018-01-16 | 天津大学 | Human body surface skin temperature field measurement method based on BP neural network |
| CN108113662A (en) * | 2017-11-20 | 2018-06-05 | 深圳市德正智能有限公司 | Wearable ECG detecting equipment |
| CN108309267A (en) * | 2018-01-14 | 2018-07-24 | 深圳市舟海科技有限公司 | A kind of monitoring method and device of cardiovascular health |
| CN108464825A (en) * | 2018-05-16 | 2018-08-31 | 北京交通大学 | Railroader's heart rate remote monitor device under a kind of High aititude operation condition |
| CN108567416A (en) * | 2018-02-01 | 2018-09-25 | 张玲玲 | A kind of cardio-vascular clinical pulse detecting device |
| CN108836290A (en) * | 2018-07-16 | 2018-11-20 | 郑州大学 | A kind of wearable Metro Passenger comfort level and health intelligent perceive bracelet |
| CN109091126A (en) * | 2018-09-14 | 2018-12-28 | 李思楠 | A kind of human body physiological state differentiation method for visualizing and equipment based on multisensor |
| CN109199349A (en) * | 2018-09-21 | 2019-01-15 | 杭州电子科技大学 | A kind of electrocardiograph pulse monitoring closestool and its blood pressure acquisition methods |
| CN109381170A (en) * | 2018-12-06 | 2019-02-26 | 王�琦 | Pressure sensor, noninvasive continuous monitoring blood pressure device and system |
| CN109602402A (en) * | 2018-06-22 | 2019-04-12 | 中国矿业大学(北京) | A kind of extreme high and low temperature environment human Body Physiology Multi-parameter monitoring warning device and method |
| CN110215191A (en) * | 2019-06-25 | 2019-09-10 | 杨安素 | Control method, device and the storage medium of pregnancy period health monitoring wearable device |
| CN110537926A (en) * | 2019-08-27 | 2019-12-06 | 河南大学 | Needle, device and method for detecting hemoglobin concentration and blood oxygen saturation |
| CN110638442A (en) * | 2019-10-10 | 2020-01-03 | 沃立(常州)医疗科技有限公司 | Electrocardio monitoring system and electrocardio monitoring method |
| CN111436948A (en) * | 2019-04-28 | 2020-07-24 | 上海爱德赞医疗科技有限公司 | Non-invasive method and equipment for monitoring blood component concentration of human body |
| CN113100759A (en) * | 2021-04-01 | 2021-07-13 | 北京雪扬科技有限公司 | Wearable device-based oxyhemoglobin saturation detection method |
| CN114431843A (en) * | 2022-01-25 | 2022-05-06 | 华中科技大学 | Portable intelligent medical measuring equipment |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101006915A (en) * | 2006-01-26 | 2007-08-01 | 香港中文大学 | Non-contact measurement method of key physiological parameters |
| CN102008296A (en) * | 2010-12-24 | 2011-04-13 | 吉林大学 | Device and method for measuring arterial blood pressures based on pulse wave signals and electrocardiosignals |
-
2017
- 2017-01-11 CN CN201710020196.4A patent/CN106901705A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101006915A (en) * | 2006-01-26 | 2007-08-01 | 香港中文大学 | Non-contact measurement method of key physiological parameters |
| CN102008296A (en) * | 2010-12-24 | 2011-04-13 | 吉林大学 | Device and method for measuring arterial blood pressures based on pulse wave signals and electrocardiosignals |
Non-Patent Citations (2)
| Title |
|---|
| 洋洋等: "基于心电脉搏信号的无创血压算法研究", 《微型机与应用》 * |
| 渠立亮等: "基于近红外的血氧含量监测系统", 《黑龙江大学自然科学学报》 * |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107582030A (en) * | 2017-08-25 | 2018-01-16 | 天津大学 | Human body surface skin temperature field measurement method based on BP neural network |
| CN108113662A (en) * | 2017-11-20 | 2018-06-05 | 深圳市德正智能有限公司 | Wearable ECG detecting equipment |
| CN108309267A (en) * | 2018-01-14 | 2018-07-24 | 深圳市舟海科技有限公司 | A kind of monitoring method and device of cardiovascular health |
| CN108567416A (en) * | 2018-02-01 | 2018-09-25 | 张玲玲 | A kind of cardio-vascular clinical pulse detecting device |
| CN108464825A (en) * | 2018-05-16 | 2018-08-31 | 北京交通大学 | Railroader's heart rate remote monitor device under a kind of High aititude operation condition |
| CN109602402A (en) * | 2018-06-22 | 2019-04-12 | 中国矿业大学(北京) | A kind of extreme high and low temperature environment human Body Physiology Multi-parameter monitoring warning device and method |
| CN108836290A (en) * | 2018-07-16 | 2018-11-20 | 郑州大学 | A kind of wearable Metro Passenger comfort level and health intelligent perceive bracelet |
| CN109091126A (en) * | 2018-09-14 | 2018-12-28 | 李思楠 | A kind of human body physiological state differentiation method for visualizing and equipment based on multisensor |
| CN109199349A (en) * | 2018-09-21 | 2019-01-15 | 杭州电子科技大学 | A kind of electrocardiograph pulse monitoring closestool and its blood pressure acquisition methods |
| CN109199349B (en) * | 2018-09-21 | 2023-08-22 | 杭州电子科技大学 | Electrocardiogram pulse monitoring closestool and blood pressure acquisition method thereof |
| CN109381170A (en) * | 2018-12-06 | 2019-02-26 | 王�琦 | Pressure sensor, noninvasive continuous monitoring blood pressure device and system |
| CN111436948A (en) * | 2019-04-28 | 2020-07-24 | 上海爱德赞医疗科技有限公司 | Non-invasive method and equipment for monitoring blood component concentration of human body |
| WO2020221265A1 (en) * | 2019-04-28 | 2020-11-05 | 上海爱德赞医疗科技有限公司 | Noninvasive human blood component concentration monitoring method and apparatus |
| CN110215191A (en) * | 2019-06-25 | 2019-09-10 | 杨安素 | Control method, device and the storage medium of pregnancy period health monitoring wearable device |
| CN110215191B (en) * | 2019-06-25 | 2022-07-01 | 杨安素 | Control method and device for wearable equipment for pregnancy health monitoring and storage medium |
| CN110537926B (en) * | 2019-08-27 | 2021-04-20 | 河南大学 | Needle, device and method for detecting hemoglobin concentration and blood oxygen saturation |
| CN110537926A (en) * | 2019-08-27 | 2019-12-06 | 河南大学 | Needle, device and method for detecting hemoglobin concentration and blood oxygen saturation |
| CN110638442A (en) * | 2019-10-10 | 2020-01-03 | 沃立(常州)医疗科技有限公司 | Electrocardio monitoring system and electrocardio monitoring method |
| CN113100759A (en) * | 2021-04-01 | 2021-07-13 | 北京雪扬科技有限公司 | Wearable device-based oxyhemoglobin saturation detection method |
| CN114431843A (en) * | 2022-01-25 | 2022-05-06 | 华中科技大学 | Portable intelligent medical measuring equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106901705A (en) | A kind of unaware human Body Physiology Multi-parameter harvester and acquisition method and application | |
| CN103385702B (en) | A kind of non-invasive blood pressure continuous detection apparatus and method | |
| KR20210005644A (en) | Method for estimating blood pressure and arterial stiffness based on light volumetric variability recording (PPG) signal | |
| Chacon et al. | A wearable pulse oximeter with wireless communication and motion artifact tailoring for continuous use | |
| US20060224073A1 (en) | Integrated physiological signal assessing device | |
| Zhang et al. | Health monitoring of human multiple physiological parameters based on wireless remote medical system | |
| JP7247444B2 (en) | device for measuring blood pressure | |
| Liu et al. | Cuffless blood pressure measurement using smartwatches: a large-scale validation study | |
| CN115500800A (en) | Wearable physiological parameter detection system | |
| JP2006158974A (en) | Integral type physiologic signal evaluation apparatus | |
| Kavya et al. | Photoplethysmography—A modern approach and applications | |
| CN210408412U (en) | Portable dynamic cardiovascular parameter acquisition equipment | |
| Priyadarshini et al. | Review of PPG signal using machine learning algorithms for blood pressure and glucose estimation | |
| CN113040738B (en) | Blood pressure detecting device | |
| CN117045217B (en) | Cuff-free blood pressure measurement method and related equipment thereof | |
| Gohlke et al. | An IoT based low-cost heart rate measurement system employing PPG sensors | |
| Guo et al. | Combining local PWV and quantified arterial changes for calibration-free cuffless blood pressure estimation: A clinical validation | |
| CN115251866A (en) | Continuous blood pressure detection method and system adopting millimeter wave radar and wearable device | |
| Alqudah et al. | Multiple time and spectral analysis techniques for comparing the PhotoPlethysmography to PiezoelectricPlethysmography with electrocardiography | |
| Liu et al. | Wearable monitoring system with multiple physiological parameters | |
| Jayadevappa et al. | Design and development of electro-optical system for acquisition of PPG signals for the assessment of cardiovascular system | |
| CN114343596A (en) | Continuous blood pressure measuring system and method based on reverse blood flow propagation time | |
| Morales et al. | Respiratory rate estimation on embedded system | |
| CN114587307A (en) | Non-contact blood pressure detector and method based on capacitive coupling electrode | |
| Jegan et al. | Methodological role of mathematics to estimate human blood pressure through biosensors |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20170630 |