CN105956372A - Remote multi-sensor monitoring medical system - Google Patents
Remote multi-sensor monitoring medical system Download PDFInfo
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- CN105956372A CN105956372A CN201610255537.1A CN201610255537A CN105956372A CN 105956372 A CN105956372 A CN 105956372A CN 201610255537 A CN201610255537 A CN 201610255537A CN 105956372 A CN105956372 A CN 105956372A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 45
- 238000003745 diagnosis Methods 0.000 claims abstract description 37
- 230000001225 therapeutic effect Effects 0.000 claims description 29
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 24
- 238000013528 artificial neural network Methods 0.000 claims description 23
- HVYWMOMLDIMFJA-DPAQBDIFSA-N cholesterol Chemical compound C1C=C2C[C@@H](O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2 HVYWMOMLDIMFJA-DPAQBDIFSA-N 0.000 claims description 22
- 238000001514 detection method Methods 0.000 claims description 18
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 15
- 239000008280 blood Substances 0.000 claims description 13
- 210000004369 blood Anatomy 0.000 claims description 13
- 230000036772 blood pressure Effects 0.000 claims description 13
- 201000010099 disease Diseases 0.000 claims description 13
- 238000011282 treatment Methods 0.000 claims description 13
- 239000010410 layer Substances 0.000 claims description 12
- 230000003750 conditioning effect Effects 0.000 claims description 10
- 238000011156 evaluation Methods 0.000 claims description 9
- 238000001914 filtration Methods 0.000 claims description 8
- 210000002569 neuron Anatomy 0.000 claims description 8
- 230000036391 respiratory frequency Effects 0.000 claims description 8
- 239000000203 mixture Substances 0.000 claims description 7
- 238000007596 consolidation process Methods 0.000 claims description 6
- 239000011159 matrix material Substances 0.000 claims description 6
- 208000024891 symptom Diseases 0.000 claims description 6
- 230000000474 nursing effect Effects 0.000 claims description 5
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000011157 data evaluation Methods 0.000 claims description 4
- 238000000034 method Methods 0.000 claims description 4
- 230000007935 neutral effect Effects 0.000 claims description 4
- 229910052760 oxygen Inorganic materials 0.000 claims description 4
- 239000001301 oxygen Substances 0.000 claims description 4
- 230000003321 amplification Effects 0.000 claims description 3
- 230000002612 cardiopulmonary effect Effects 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 235000013399 edible fruits Nutrition 0.000 claims description 3
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 3
- 238000002601 radiography Methods 0.000 claims description 3
- 238000003860 storage Methods 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 235000012000 cholesterol Nutrition 0.000 claims description 2
- 238000009826 distribution Methods 0.000 claims description 2
- 238000000605 extraction Methods 0.000 claims description 2
- 230000006870 function Effects 0.000 claims description 2
- 238000001746 injection moulding Methods 0.000 claims description 2
- 239000011229 interlayer Substances 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 claims description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 2
- 238000004891 communication Methods 0.000 claims 1
- 230000005611 electricity Effects 0.000 claims 1
- 230000002452 interceptive effect Effects 0.000 claims 1
- 230000010354 integration Effects 0.000 abstract 1
- 238000002558 medical inspection Methods 0.000 abstract 1
- 238000012806 monitoring device Methods 0.000 abstract 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
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- 238000005516 engineering process Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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Abstract
Provided is a remote multi-sensor monitoring medical system, characterized by comprising a hospital system, a home system, and a remote monitoring center. The hospital system comprises a medical inspection device, a patient state grading module, an intelligent diagnosis module, and a data integration server. The home system comprises a portable multi-sensor monitoring device.
Description
Technical field
The invention belongs to smart machine field, particularly to the medical system of a kind of long-range multisensor monitoring.
Background technology
Intelligent medical system utilizes computer analysis, retrieves, calculates science, rationally, comprehensively diagnose
As a result, pathological examination etc., the correlative factor needed for this disease is made a definite diagnosis in each disease offer to diagnostic result.
But current intelligent medical system rests in the collection of patient's essential information and case history mostly, diagnoses and controls
Treatment scheme is all to have doctor to make, and working doctor amount is not mitigated, and lacks at home care prison
Control.
Summary of the invention
The technical problem to be solved in the present invention is how to be realized condition-inference and therapeutic scheme by algorithm
Assessment and formulation, provide the medical system that the long-range multisensor of a kind of medical treatment is guarded to this present invention, its bag
Include hospital system, home system and remote monitoring center,
Hospital system includes that medical investigative apparatus, patient condition diversity module, intelligent diagnostics module, data are whole
Hop server,
Home system includes Portable multi-sensor monitor device,
Attending doctor realizes the system of medical examination, diagnosis and therapeutic scheme to patient by hospital system
Fixed, attending doctor obtains, by the Portable multi-sensor monitor device of home system, the reality nursed the sick of being in
Time data, Portable multi-sensor monitor device also with remote monitoring center wireless connections, thus go out patient
Reply can be taked during existing emergency in time, and emergency is notified attending doctor simultaneously and uploads number
According to integrated service device,
When patient is in hospital system, the multinomial medical examination data of medical investigative apparatus detection patient, and
Input patient condition diversity module, patient condition diversity module uses assessment algorithm to comment the state of an illness of patient
Estimating, the doctor in charge then enters patient condition diversity module through authentication and the assessment result divided is carried out core
It is real, if the doctor in charge thinks that the assessment result divided is correct, then by relevant information and the medical examination of patient
Data are filed according to assessment result, and input intelligent diagnostics module, if the doctor in charge think divide
Assessment result is incorrect, then determined the assessment result of patient by the doctor in charge, then by the relevant information of patient and
Medical examination data are filed according to assessment result, and input intelligent diagnostics module；Intelligent diagnostics module root
Corresponding therapeutic scheme is automatically generated according to relevant information, medical examination data and the assessment result of patient, main
Control doctor therapeutic scheme to be examined, if the doctor in charge recognizes through authentication entrance intelligent diagnostics module
Correct for therapeutic scheme, then by the relevant information of patient, medical examination data, therapeutic scheme and assessment knot
Fruit is uploaded to data consolidation server, if the doctor in charge thinks that therapeutic scheme is incorrect, then by the doctor in charge
Reformulate therapeutic scheme, then by the relevant information of patient, medical examination data, therapeutic scheme and assessment
Result is uploaded to data consolidation server；
The assessment algorithm of patient condition diversity module particularly as follows:
Each medical examination data are carried out grade classification, then
Whole detection measured value is:
Wherein, OPM is whole detection measured value, TiIt is the grade point of i-th medical examination data,
I=1,2 ..., N, Ti=1,2 ..., M, M are greatest level value, M >=2, and N is total item of medical examination data
Number；
Maximum overall measured value is:
OPM_MAX is maximum overall measured value
Then the assessed value as patient's state of an illness of assessment result is:
Suggestion according to assessed value C and the doctor in charge determines whether patient can be in nursing, if assessed
Value is C >=0.4, then client need is in hospital；If assessed value is 0 ＜ C ＜ 0.1, such patient has fully recovered,
Without further diagnosis monitoring service；If assessed value is 0.1≤C ＜ 0.4 and the doctor in charge agrees to, then
Patient can carry out home care；
When patient is in home system, judge the basic diagnosis required for home care patients according to assessed value
Service, high level diagnostics service, diagnosis report form, attending doctor's type, monitoring period and monitoring cycle；
As 0.1≤C ＜ 0.2, such patient is slight patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate；
Service without high level diagnostics；
Diagnosis report form is web page notification and mail；
Attending doctor's type is the attending doctor of less than 10 years experiences；
Monitoring period is 1 day；
The monitoring cycle be 1 hour once；
As 0.2≤C ＜ 0.3, such patient is moderate patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate, blood pressure detecting,
Blood oxygen detects；
Service without high level diagnostics；
Diagnosis report form is web page notification and mail；
Attending doctor's type is the attending doctor of less than 10 years experiences；
Monitoring period is 7 days；
The monitoring cycle be 1 hour once；
As 0.3≤C ＜ 0.4, such patient is severe patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate, blood pressure detecting,
The detection of blood sugar test, cardiopulmonary, cholesterol levels detection, assessment aroused in interest, heart radiography；
High level diagnostics service is virtual heart, expert consultation；
Diagnosis report form is mobile phone, web page notification and mail；
Attending doctor's type is the attending doctor of more than 10 years experiences；
Monitoring period is 30 days；
The monitoring cycle is 1 minute；
Different treatments and nursing care mode can be taked for the state of an illness of different patients by above-mentioned classification,
Thus reasonable disposition medical resource, reduce medical treatment cost.
Wherein the pulse in basic diagnosis service, electrocardiogram, breathing rate are by Portable multi-sensor monitoring dress
Put realization,
Portable multi-sensor monitor device includes heart sound transducer, pulse transducer, respiration pickup, adopts
Collection modulate circuit, power management module, warning circuit, communicator, display, master controller, storage
Device and keyboard；
Heart sound transducer, pulse transducer, respiration pickup realize electrocardiogram, pulse, the survey of breathing rate
Amount；
Master controller is sensed from heart sound transducer, pulse transducer, breathing by acquisition and conditioning circuit collection
The data signal of device, and by communicator real-time Transmission to remote monitoring center；
By keyboard, the running parameter of Portable multi-sensor monitor device is adjusted, and passes through display
The physiological situation of display patient；
Memorizer is for storing the data message that the relevant information of patient, case history and master controller gather；
Power management module, for controlling the power supply supply to Portable multi-sensor monitor device, is just maintaining
Often in the case of work, reduce power consumption；
Acquisition and conditioning circuit is by signal acquisition circuit, one-level amplifying circuit, second amplifying circuit, low-pass filtering
Circuit, amplitude limiter circuit and A/D change-over circuit are sequentially connected with composition；
The amplification of signal, filtering and analog-to-digital conversion is realized by acquisition and conditioning circuit；
Warning circuit is reported to the police for sending sound and light signal when emergency occurs in patient.
Beneficial effects of the present invention:
(1) realize the evaluation to patient's state of an illness by assessment algorithm, thus be patient scheme and disease
The selection of people's Curing circumstance provides foundation；
(2) there is home system, thus ensure that the round-the-clock monitoring of patient's home care；
(3) introduce intelligent diagnostics mode, automatically generate therapeutic scheme, thus greatly reduce the labor of doctor
Fatigue resistance.
Accompanying drawing explanation
Fig. 1 is the system block diagram of the present invention；
Fig. 2 is the intelligent diagnostics module composition frame chart of the present invention；
Fig. 3 is the Portable multi-sensor monitor device composition frame chart of the present invention；
Detailed description of the invention
The present invention is further illustrated with embodiment below in conjunction with the accompanying drawings.
Embodiments of the invention show with reference to Fig. 1-3.
A kind of medical treatment long-range multisensor monitoring medical system, it include hospital system, home system and
Remote monitoring center,
Hospital system includes that medical investigative apparatus, patient condition diversity module, intelligent diagnostics module, data are whole
Hop server,
Home system includes Portable multi-sensor monitor device,
Attending doctor realizes the system of medical examination, diagnosis and therapeutic scheme to patient by hospital system
Fixed, attending doctor obtains, by the Portable multi-sensor monitor device of home system, the reality nursed the sick of being in
Time data, Portable multi-sensor monitor device also with remote monitoring center wireless connections, thus go out patient
Reply can be taked during existing emergency in time, and emergency is notified attending doctor simultaneously and uploads number
According to integrated service device,
When patient is in hospital system, the multinomial medical examination data of medical investigative apparatus detection patient, and
Input patient condition diversity module, patient condition diversity module uses assessment algorithm to comment the state of an illness of patient
Estimating, the doctor in charge then enters patient condition diversity module through authentication and the assessment result divided is carried out core
It is real, if the doctor in charge thinks that the assessment result divided is correct, then by relevant information and the medical examination of patient
Data are filed according to assessment result, and input intelligent diagnostics module, if the doctor in charge think divide
Assessment result is incorrect, then determined the assessment result of patient by the doctor in charge, then by the relevant information of patient and
Medical examination data are filed according to assessment result, and input intelligent diagnostics module；Intelligent diagnostics module root
Corresponding therapeutic scheme is automatically generated according to relevant information, medical examination data and the assessment result of patient, main
Control doctor therapeutic scheme to be examined, if the doctor in charge recognizes through authentication entrance intelligent diagnostics module
Correct for therapeutic scheme, then by the relevant information of patient, medical examination data, therapeutic scheme and assessment knot
Fruit is uploaded to data consolidation server, if the doctor in charge thinks that therapeutic scheme is incorrect, then by the doctor in charge
Reformulate therapeutic scheme, then by the relevant information of patient, medical examination data, therapeutic scheme and assessment
Result is uploaded to data consolidation server；
The assessment algorithm of patient condition diversity module particularly as follows:
Each medical examination data are carried out grade classification, then whole detection measured value is:
Wherein, OPM is whole detection measured value, TiIt is the grade point of i-th medical examination data,
I=1,2 ..., N, Ti=1,2 ..., M, M are greatest level value, M >=2, and N is total item of medical examination data
Number；
Maximum overall measured value is:
OPM_MAX is maximum overall measured value
Then the assessed value as patient's state of an illness of assessment result is:
Above-mentioned assessment calculates the state of an illness that can effectively assess patient, thus carries out Put on file.
Further, M=5, N=6
Medical investigative apparatus includes glucometer, ECG detecting device, respiratory frequency detector, cholesterol water
Flat detector, blood pressure instrument, X-ray production apparatus,
Medical examination data include blood sugar concentration, ECG data evaluation, respiratory frequency, cholesterol levels,
Blood pressure conditions, radioscopy evaluation,
Further,
Wherein, the opinion rating of blood sugar concentration divides as shown in the table；
| Grade | 1 | 2 | 3 | 4 | 5 |
| Blood sugar concentration (mg/DL) | <98 | 98-154 | 155-183 | 184-254 | >254 |
The opinion rating of respiratory frequency divides as shown in the table；
| Grade | 1 | 2 | 3 | 4 | 5 |
| Respiratory frequency (beat/min) | 12-18 | 9-11,19-21 | 6-8,22-24 | 3-5,25-27 | <3,>27 |
The opinion rating of cholesterol levels divides as shown in the table；
| Grade | 1 | 2 | 3 | 4 | 5 |
| Cholesterol levels (mmolg/l) | <5.2 | 5.2-5.5 | 5.6-5.8 | 5.9-6.0 | >6.0 |
The opinion rating of blood pressure conditions divides as shown in the table；
ECG data evaluation refers to the grade evaluation that doctor makes according only to electrocardiogram；
Radioscopy evaluation refers to the grade evaluation that doctor makes according only to X-ray；
Intelligent diagnostics module includes dynamic comprehensive data base, neural network learning module, inference machine, explanation mould
Block, sample knowledge storehouse, neural network structure knowledge base, clinical symptoms Description of Knowledge storehouse, disease knowledge storehouse,
Therapeutic scheme knowledge base, historical record knowledge base, knowledge data library management module,
Each knowledge base can be carried out to neural network learning module and by KBM module by expert
Adjust management, safeguard renewal；
Explanation module is the bridge linked up between system and attending doctor, is responsible for converting the diagnosis of attending doctor
The information being capable of identify that for system, and output result last for system is converted into attending doctor it will be appreciated that
Information；
Inference machine uses the own knowledge through possessing of system, in conjunction with the injection moulding process comprised in dynamic comprehensive data base
Specifying information make inferences, draw corresponding therapeutic scheme.Inference machine include ANN Reasoning module and
RBR module two parts.Reasoning between " clinical symptoms disease " uses neutral net
Module, uses RBR between " disease treatment scheme "；
Neural network learning module propose include the network number of plies, input, export, god including hidden node number
Through network structure, organize learning sample to be trained and Learning Algorithm, by sample knowledge storehouse
Extraction learns, and obtains weights distribution, completes knowledge acquisition.
Further, the method that neural network structure is combined by fuzzy logic and neutral net realizes, god
It is BP algorithm through Learning Algorithms.
Sample knowledge storehouse, neural network structure knowledge base, clinical symptoms Description of Knowledge storehouse, disease knowledge storehouse,
Scheme of curing the disease knowledge base, historical record knowledge base deposit corresponding knowledge data respectively.
Knowledge data library management module has complete database manipulation function, and expert passes through knowledge data depositary management
Each knowledge base is inquired about, adds and is deleted and revise by reason module,
Dynamic comprehensive data base receives and stores the relevant information of patient, medical examination data and assessment knot
Really；
The work process of inference machine is as follows:
(1) relevant information of patient, medical examination data and assessment result are carried out Fuzzy processing, and
Input pattern in this, as each sub neural network；
(2) from neural network structure knowledge base, read in the weight matrix of each sub neural network；
(3) combine the weight matrix between each sub neural network input layer, hidden layer, calculate each sub neural network defeated
Enter the output of layer neuron, and will be output as the input of hidden neuron；
(4) combine each sub neural network hidden layer, the weight matrix of output interlayer, calculate output layer neuron
Output valve；
(5) according to the output valve of output layer neuron, carry out in conjunction with the relevant information in dynamic comprehensive data base
The reasoning of rule-based reasoning module, assigns a cause for an illness, and provides credibility；
(6) according to the reason finally determined, the treatment side corresponding to the concrete cause of disease is provided in conjunction with relevant information
Case；
It is truly realized intelligent diagnostics by intelligent diagnostics module, can be that doctor provides full and accurate treatment side
Case, and then reduce its working strength.
Suggestion according to assessed value C and the doctor in charge determines whether patient can be in nursing, if assessed
Value is C >=0.4, then client need is in hospital；If assessed value is 0 ＜ C ＜ 0.1, such patient has fully recovered,
Without further diagnosis monitoring service；If assessed value is 0.1≤C ＜ 0.4 and the doctor in charge agrees to, then
Patient can carry out home care；
When patient is in home system, judge the basic diagnosis required for home care patients according to assessed value
Service, high level diagnostics service, diagnosis report form, attending doctor's type, monitoring period and monitoring cycle；
As 0.1≤C ＜ 0.2, such patient is slight patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate；
Service without high level diagnostics；
Diagnosis report form is web page notification and mail；
Attending doctor's type is the attending doctor of less than 10 years experiences；
Monitoring period is 1 day；
The monitoring cycle be 1 hour once；
As 0.2≤C ＜ 0.3, such patient is moderate patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate, blood pressure detecting,
Blood oxygen detects；
Service without high level diagnostics；
Diagnosis report form is web page notification and mail；
Attending doctor's type is the attending doctor of less than 10 years experiences；
Monitoring period is 7 days；
The monitoring cycle be 1 hour once；
As 0.3≤C ＜ 0.4, such patient is severe patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate, blood pressure detecting,
The detection of blood sugar test, cardiopulmonary, cholesterol levels detection, assessment aroused in interest, heart radiography；
High level diagnostics service is virtual heart, expert consultation；
Diagnosis report form is mobile phone, web page notification and mail；
Attending doctor's type is the attending doctor of more than 10 years experiences；
Monitoring period is 30 days；
The monitoring cycle is 1 minute；
Different treatments and nursing care mode can be taked for the state of an illness of different patients by above-mentioned classification,
Thus reasonable disposition medical resource, reduce medical treatment cost.
Wherein the pulse in basic diagnosis service, electrocardiogram, breathing rate are by Portable multi-sensor monitoring dress
Put realization,
Portable multi-sensor monitor device includes heart sound transducer, pulse transducer, respiration pickup, adopts
Collection modulate circuit, power management module, warning circuit, communicator, display, master controller, storage
Device and keyboard；
Heart sound transducer, pulse transducer, respiration pickup realize electrocardiogram, pulse, the survey of breathing rate
Amount；
Master controller is sensed from heart sound transducer, pulse transducer, breathing by acquisition and conditioning circuit collection
The data signal of device, and by communicator real-time Transmission to remote monitoring center；
By keyboard, the running parameter of Portable multi-sensor monitor device is adjusted, and passes through display
The physiological situation of display patient；
Memorizer is for storing the data message that the relevant information of patient, case history and master controller gather；
Power management module, for controlling the power supply supply to Portable multi-sensor monitor device, is just maintaining
Often in the case of work, reduce power consumption；
Acquisition and conditioning circuit is by signal acquisition circuit, one-level amplifying circuit, second amplifying circuit, low-pass filtering
Circuit, amplitude limiter circuit and A/D change-over circuit are sequentially connected with composition；
The amplification of signal, filtering and analog-to-digital conversion is realized by acquisition and conditioning circuit；
Warning circuit is reported to the police for sending sound and light signal when emergency occurs in patient.
The above embodiment only have expressed one embodiment of the present invention, but can not therefore understand
For limitation of the scope of the invention.It should be pointed out that, for the person of ordinary skill of the art, do not taking off
On the premise of present inventive concept, it is also possible to make some deformation and improvement, these broadly fall into the guarantor of the present invention
Protect scope.
Claims (9)
1. the medical system of a long-range multisensor monitoring, it is characterised in that: it includes hospital system, family
Front yard system and remote monitoring center,
Hospital system includes that medical investigative apparatus, patient condition diversity module, intelligent diagnostics module, data are whole
Hop server,
Home system includes Portable multi-sensor monitor device,
Attending doctor realizes the system of medical examination, diagnosis and therapeutic scheme to patient by hospital system
Fixed, attending doctor obtains, by the Portable multi-sensor monitor device of home system, the reality nursed the sick of being in
Time data, Portable multi-sensor monitor device also with remote monitoring center wireless connections, thus go out patient
Reply can be taked during existing emergency in time, and emergency is notified attending doctor simultaneously and uploads number
According to integrated service device,
When patient is in hospital system, the multinomial medical examination data of medical investigative apparatus detection patient, and
Input patient condition diversity module, patient condition diversity module uses assessment algorithm to comment the state of an illness of patient
Estimating, the doctor in charge then enters patient condition diversity module through authentication and the assessment result divided is carried out core
It is real, if the doctor in charge thinks that the assessment result divided is correct, then by relevant information and the medical examination of patient
Data are filed according to assessment result, and input intelligent diagnostics module, if the doctor in charge think divide
Assessment result is incorrect, then determined the assessment result of patient by the doctor in charge, then by the relevant information of patient and
Medical examination data are filed according to assessment result, and input intelligent diagnostics module；Intelligent diagnostics module root
Corresponding therapeutic scheme is automatically generated according to relevant information, medical examination data and the assessment result of patient, main
Control doctor therapeutic scheme to be examined, if the doctor in charge recognizes through authentication entrance intelligent diagnostics module
Correct for therapeutic scheme, then by the relevant information of patient, medical examination data, therapeutic scheme and assessment knot
Fruit is uploaded to data consolidation server, if the doctor in charge thinks that therapeutic scheme is incorrect, then by the doctor in charge
Reformulate therapeutic scheme, then by the relevant information of patient, medical examination data, therapeutic scheme and assessment
Result is uploaded to data consolidation server；
The assessment algorithm of patient condition diversity module particularly as follows:
Each medical examination data are carried out grade classification, then
Whole detection measured value is:
Wherein, OPM is whole detection measured value, TiIt is the grade point of i-th medical examination data,
I=1,2 ..., N, Ti=1,2 ..., M, M are greatest level value, M >=2, and N is total item of medical examination data
Number；
Maximum overall measured value is:
OPM_MAX is maximum overall measured value
Then the assessed value as patient's state of an illness of assessment result is:
Suggestion according to assessed value C and the doctor in charge determines whether patient can be in nursing, if assessed
Value is C >=0.4, then client need is in hospital；If assessed value is 0 ＜ C ＜ 0.1, such patient has fully recovered,
Without further diagnosis monitoring service；If assessed value is 0.1≤C ＜ 0.4 and the doctor in charge agrees to, then
Patient can carry out home care；
When patient is in home system, judge the basic diagnosis required for home care patients according to assessed value
Service, high level diagnostics service, diagnosis report form, attending doctor's type, monitoring period and monitoring cycle；
As 0.1≤C ＜ 0.2, such patient is slight patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate；
Service without high level diagnostics；
Diagnosis report form is web page notification and mail；
Attending doctor's type is the attending doctor of less than 10 years experiences；
Monitoring period is 1 day；
The monitoring cycle be 1 hour once；
As 0.2≤C ＜ 0.3, such patient is moderate patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate, blood pressure detecting,
Blood oxygen detects；
Service without high level diagnostics；
Diagnosis report form is web page notification and mail；
Attending doctor's type is the attending doctor of less than 10 years experiences；
Monitoring period is 7 days；
The monitoring cycle be 1 hour once；
As 0.3≤C ＜ 0.4, such patient is severe patient,
Basic diagnosis service is patient's essential information, case history, pulse, electrocardiogram, breathing rate, blood pressure detecting,
The detection of blood sugar test, cardiopulmonary, cholesterol levels detection, assessment aroused in interest, heart radiography；
High level diagnostics service is virtual heart, expert consultation；
Diagnosis report form is mobile phone, web page notification and mail；
Attending doctor's type is the attending doctor of more than 10 years experiences；
Monitoring period is 30 days；
The monitoring cycle is 1 minute；
Wherein the pulse in basic diagnosis service, electrocardiogram, breathing rate are by Portable multi-sensor monitoring dress
Put realization,
Portable multi-sensor monitor device includes heart sound transducer, pulse transducer, respiration pickup, adopts
Collection modulate circuit, power management module, warning circuit, communicator, display, master controller, storage
Device and keyboard；
Heart sound transducer, pulse transducer, respiration pickup realize electrocardiogram, pulse, the survey of breathing rate
Amount；
Master controller is sensed from heart sound transducer, pulse transducer, breathing by acquisition and conditioning circuit collection
The data signal of device, and by communicator real-time Transmission to remote monitoring center；
By keyboard, the running parameter of Portable multi-sensor monitor device is adjusted, and passes through display
The physiological situation of display patient；
Memorizer is for storing the data message that the relevant information of patient, case history and master controller gather；
Power management module, for controlling the power supply supply to Portable multi-sensor monitor device, is just maintaining
Often in the case of work, reduce power consumption；
Acquisition and conditioning circuit is by signal acquisition circuit, one-level amplifying circuit, second amplifying circuit, low-pass filtering
Circuit, amplitude limiter circuit and A/D change-over circuit are sequentially connected with composition；
The amplification of signal, filtering and analog-to-digital conversion is realized by acquisition and conditioning circuit；
Warning circuit is reported to the police for sending sound and light signal when emergency occurs in patient.
The medical system of a kind of long-range multisensor the most according to claim 1 monitoring, it is characterised in that:
M=5, N=6,
Medical investigative apparatus includes glucometer, ECG detecting device, respiratory frequency detector, cholesterol water
Flat detector, blood pressure instrument, X-ray production apparatus,
Medical examination data include blood sugar concentration, ECG data evaluation, respiratory frequency, cholesterol levels,
Blood pressure conditions, radioscopy evaluation.
3. the medical system of a kind of long-range multisensor monitoring stated according to claim 2, it is characterised in that:
The grade classification of blood sugar concentration is as shown in the table,
The grade classification of respiratory frequency is as shown in the table,
The grade classification of cholesterol levels is as shown in the table,
The grade classification of blood pressure conditions is as shown in the table,
ECG data evaluation refers to the evaluation that doctor makes according only to electrocardiogram；
Radioscopy evaluation refers to the evaluation that doctor makes according only to X-ray.
4. the medical system of a kind of long-range multisensor monitoring described in claim 1, it is characterised in that: intelligence
Dynamic comprehensive data base, neural network learning module, inference machine, explanation module, sample can be included by diagnostic module
This knowledge base, neural network structure knowledge base, clinical symptoms Description of Knowledge storehouse, disease knowledge storehouse, treatment side
Case knowledge base, historical record knowledge base, knowledge data library management module,
Each knowledge base can be carried out to neural network learning module and by KBM module by expert
Adjust management, safeguard renewal；
Explanation module is the bridge linked up between system and attending doctor, is responsible for converting the diagnosis of attending doctor
The information being capable of identify that for system, and output result last for system is converted into attending doctor it will be appreciated that
Information；
Inference machine uses the own knowledge through possessing of system, in conjunction with the injection moulding process comprised in dynamic comprehensive data base
Specifying information make inferences, draw corresponding therapeutic scheme.Inference machine include ANN Reasoning module and
RBR module two parts.Reasoning between " clinical symptoms disease " uses neutral net
Module, uses RBR between " disease treatment scheme "；
Neural network learning module propose include the network number of plies, input, export, god including hidden node number
Through network structure, organize learning sample to be trained and Learning Algorithm, by sample knowledge storehouse
Extraction learns, and obtains weights distribution, completes knowledge acquisition.
The medical system of a kind of long-range multisensor the most according to claim 4 monitoring, it is characterised in that: god
The method combined by fuzzy logic and neutral net through network structure is realized, and Learning Algorithm is BP
Algorithm.
Sample knowledge storehouse, neural network structure knowledge base, clinical symptoms Description of Knowledge storehouse, disease knowledge storehouse,
Scheme of curing the disease knowledge base, historical record knowledge base deposit corresponding knowledge data respectively.
Knowledge data library management module has complete database manipulation function, and expert passes through knowledge data depositary management
Each knowledge base is inquired about, adds and is deleted and revise by reason module,
Dynamic comprehensive data base receives and stores the relevant information of patient, medical examination data and assessment knot
Really.
6. the medical system of a kind of long-range multisensor monitoring stated according to claim 5, it is characterised in that:
The work process of inference machine is as follows:
(1) relevant information of patient, medical examination data and assessment result are carried out Fuzzy processing, and
Input pattern in this, as each sub neural network；
(2) from neural network structure knowledge base, read in the weight matrix of each sub neural network；
(3) combine the weight matrix between each sub neural network input layer, hidden layer, calculate each sub neural network defeated
Enter the output of layer neuron, and will be output as the input of hidden neuron；
(4) combine each sub neural network hidden layer, the weight matrix of output interlayer, calculate output layer neuron
Output valve；
(5) according to the output valve of output layer neuron, carry out in conjunction with the relevant information in dynamic comprehensive data base
The reasoning of rule-based reasoning module, assigns a cause for an illness, and provides credibility；
(6) according to the reason finally determined, the treatment side corresponding to the concrete cause of disease is provided in conjunction with relevant information
Case.
The medical system of a kind of long-range multisensor the most according to claim 1 monitoring, it is characterised in that:
Pulse wave detection module includes pulse wave sensor, pulse wave signal modulate circuit；Pulse wave signal conditioning electricity
Route one-level amplifying circuit, second amplifying circuit, low-pass filter circuit and amplitude limiter circuit are sequentially connected with composition.
The medical system of a kind of long-range multisensor the most according to claim 1 monitoring, it is characterised in that:
ECG detecting module includes electrode, band filter, trap circuit, leg drive circuit；Band filter
For filtering interfering, frequency range is 0.3-120Hz, and band filter is by low-pass filter circuit and high-pass filtering
Circuit is constituted, and the cut-off frequency of low-pass filter circuit is 120Hz.
The medical system of a kind of long-range multisensor the most according to claim 1 monitoring, it is characterised in that:
CPU module gathers from pulse wave detection module, ECG detecting module, blood pressure detecting module, blood
The data signal of oxygen saturation detection module, and by communication module real-time Transmission to remote monitoring center；
By touch screen module the running parameter of Portable multi-sensor monitor device it is adjusted and shows
The physiological situation of patient；
Memory module is for storing the number that the relevant information of patient, case history and CPU module gather
It is believed that breath；
Power management module, for controlling the power supply supply to Portable multi-sensor monitor device, is just maintaining
Often in the case of work, reduce power consumption.
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