CN109567818A - The recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to - Google Patents
The recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to Download PDFInfo
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- CN109567818A CN109567818A CN201811383174.5A CN201811383174A CN109567818A CN 109567818 A CN109567818 A CN 109567818A CN 201811383174 A CN201811383174 A CN 201811383174A CN 109567818 A CN109567818 A CN 109567818A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/112—Gait analysis
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
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- 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
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
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- 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
Abstract
The recognition methods that a variety of walking step states adjustment based on hemoglobin information that the invention discloses a kind of is intended to.A kind of recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to of the present invention characterized by comprising to the cortex hemoglobin concentration that walking step state time adjustment is recorded, carry out the pretreatment of data；Wherein, the cortex hemoglobin concentration that the walking step state time adjustment is recorded refers to by " carrying out test experiments using near infrared spectrum brain imaging technique (NIRS), subject completes the task of corresponding walking step state adjustment in fixed area；" obtain；For pretreated cortex hemoglobin information, corresponding channel division is carried out according to the distribution in cerebral function region, and calculate and extract relevant parameter as feature；Application model recognizer establishes the detection model of four kinds of gait adjustments intention.The utility model has the advantages that present invention application near infrared spectrum brain imaging technique progress test experiments are simple and convenient.
Description
Technical field
The present invention relates to intelligent walk helps, rehabilitation training field, and in particular to a kind of a variety of rows based on hemoglobin information
Walk the recognition methods of gait adjustment intention.
Background technique
In recent years, more and more people suffer from decocting for dyskinesia.These people or some legs and feet are inconvenient
Old man, also or some experienced leads to disabled patient after accident, disease, natural calamity.Therefore, more and more sections
The worker of grinding is devoted to develop walk help or rehabilitation training equipment to help these people to restore ability to act.And brain-computer interface
Promising technology is gathered around as one, extensive and deep effect is played in rehabilitation field.Pass through brain-computer interface technology, energy
The brain autogenic movement for enough decoding user is intended to, and then these autogenic movements are intended to help him to control external equipment
Be trained and restore locomitivity.Therefore for these specific crowds of lower extremity motor function obstacle, it is based on brain-computer interface
The walk-aid equipment that technological development goes out, can preferably make up the deficiency of walk-aid equipment on Vehicles Collected from Market, meet lower extremity motor function barrier
The urgent need for the person of hindering.
Lower extremity movement often has bigger motion amplitude relative to upper extremity exercise, and is limited by more environmental factors
Influence, the walking movement of lower limb is even more so.Such motion mode may make some technologies brain signal collected not
Stablize and even fail, and actual conditions can not be applied to.Such as brain power technology (EEG), brain magnetic technology (MEG), functional magnetic is total
Vibration imaging (fMRI) etc..These technologies generally require a stable test environment, and equipment excessively it is huge be not suitable for
The walking of user and moved accordingly.Although having some researchs at present uses these above-mentioned technologies, to study row
Brain states when walking, but these researchs all carry out on a treadmill, this does not meet actual even in everyday situations.Lucky
It is that, by Near-infrared Brain imaging technique (fNIRS), can be effectively applied for such case.Due to fNIRS portability and
To the hyposensitivity of environment, in practical applications, user can carry fNIRS equipment, carry out long range in a natural environment
Walking, and their brain hemoglobin information during exercise are acquired simultaneously.Therefore, using the brain-computer interface based on fN I RS
Technology, the optimal selection that spontaneous gait adjustment is intended to when being research walking.
The achievement being intended in the world based on the spontaneous adjustment of brain-computer interface technical research at present is simultaneously few, it is most of all
Based on the elementary step.And it in many studies, is concentrated mainly on research to be intended to from resting state to the dynamic spontaneous adjustment of fortune, such as
From resting to stretching out one's hand, from rest to step etc..Although these researchs achieve certain achievement, in actual even in everyday situations
In, the spontaneous adjustment of user is intended to, and is frequently not but to move shape from some motion state to another from static to movement
State.Therefore in order to focus on the practicality, the spontaneous gait adjustment of research is intended that oneself from a gait to another gait
Hair adjustment is intended to.
There are following technical problems for traditional technology:
But when how the detection model that established spontaneous tune is intended to being committed in practice, but there is another
Realistic problem.Traditional brain-computer interface technology, in practical application, needing to allow user to be tested accordingly in advance, to obtain
Brain signal is decoded modeling.This needs a large amount of time, the discontented mood that can cause.Therefore, based on existing
User data is decoded modeling, then directly carries out test for new user and provides as a result, being best solution.
Such method is known as I nter-BCI.But the model established in this way, before the precision often identified will be lower than
Person.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of, and a variety of walking step states based on hemoglobin information adjust meaning
The recognition methods of figure, the identification of gait adjustment when reaching to walking increases including respectively leg speed, leg speed reduces, step
Long increase reduces four kinds of gait adjustment states with step-length, to realize the intelligent rehabilitation medical treatment supplementary means based on brain-computer interface technology
The purpose to lay the foundation.
In order to solve the above-mentioned technical problems, the present invention provides a kind of a variety of walking step state tune based on hemoglobin information
The recognition methods of whole intention, comprising:
To the cortex hemoglobin concentration that walking step state time adjustment is recorded, the pretreatment of data is carried out；Wherein, institute
The cortex hemoglobin concentration that walking step state time adjustment is recorded is stated to refer to by " using near infrared spectrum brain imaging technique
(NIRS) test experiments are carried out, subject completes the task of corresponding walking step state adjustment in fixed area；" obtain；
For pretreated cortex hemoglobin information, corresponding channel is carried out according to the distribution in cerebral function region
It divides, and calculates and extract relevant parameter as feature；
Application model recognizer establishes the detection model of four kinds of gait adjustments intention.
In one of the embodiments, " test experiments, subject are carried out using near infrared spectrum brain imaging technique (NIRS)
The task of corresponding walking step state adjustment is completed in fixed area；" in, leg speed increases, leg speed reduces, step-length increases and step-length
Reduce four kinds of every kind of gait adjustments all to continuously perform 2 times, and the time of having a rest between task and task about 40 seconds.
It " to the cortex hemoglobin concentration that walking step state time adjustment is recorded, carries out in one of the embodiments,
The pretreatment of data；" to carry out pretreated method specific as follows:
Using the low-pass filter of Chebyshev, filter cutoff frequency 0.145Hz filters out the radio-frequency component in signal,
Retain the frequency content of neuron activity；
Using the method for morphologic filtering, the method for combining make and break filtering and opening and closing filtering carries out baseline to signal and rectifys
Just, drift is removed.
In one of the embodiments, " for pretreated cortex hemoglobin information, according to cerebral function region
Distribution carry out corresponding channel division, and calculate and extract relevant parameter as feature；" in, to pretreated brain skin
Layer hemoglobin information carries out the relevant operation of Feature Engineering.
In one of the embodiments, " for pretreated cortex hemoglobin information, according to cerebral function region
Distribution carry out corresponding channel division, and calculate and extract relevant parameter as feature；" specifically include:
Secondly with calculating each channel first comentropy calculates the weight in each channel, final root based on comentropy
The blood oxygen concentration value in corresponding region is obtained according to weighted mean method；
The corresponding parameter of hemoglobin, statistical nature, entropy feature and correlation including the oxygen content of blood are calculated to each brain area
The three categories feature such as feature includes mean value, energy, variance, very poor, comentropy and Pearson correlation coefficients, in this, as original
The feature space of beginning.
" application model recognizer establishes the detection model of four kinds of gait adjustments intention in one of the embodiments,."
It specifically includes:
Examine whether the feature under different conditions is in same distribution using Kolmogorov-Smirnov, if should
Feature is in and is same as being distributed, then shows that this feature has no ability to differentiation state, should give rejecting, pass through the feature of such filtering type
Selection mode carries out preliminary screening, obtains proper subspace；
Principal component analysis is carried out to proper subspace, dimensionality reduction is carried out to feature, and choose the principal component of preceding 95% contribution rate,
Dimension reduction space as feature；
Using the Ensemble Learning Algorithms (stacking) of stacking, two layers of stacking supporting vector machine model is realized
(stacking-SVMs)；For the SVM model of first layer, dimension reduction space is picked out optimal using Annealing-Genetic Algorithm
15 groups of feature combinations, and 15 groups of SVM models are constructed with this；For the SVM model of the second layer, then 15 SVM moulds to upper one layer
Type with SVM is and base classifier Stacking algorithm is integrated, and still takes Annealing-Genetic Algorithm, carrys out the super of optimizing SVM
Parameter such as penalty coefficient；
It is detected according to the model of foundation, obtains testing result.
A kind of computer equipment can be run on a memory and on a processor including memory, processor and storage
The step of computer program, the processor realizes any one the method when executing described program.
A kind of computer readable storage medium, is stored thereon with computer program, realization when which is executed by processor
The step of any one the method.
A kind of processor, the processor is for running program, wherein described program executes described in any item when running
Method.
Beneficial effects of the present invention:
Present invention application near infrared spectrum brain imaging technique carries out test experiments, easy to operate, is easy to carry about with one, to outside
Environment it is of less demanding, it is low to the susceptibility of environmental noise, and any negative interaction will not be generated to subject.Entire test
Subject carries NIRS equipment in the process, and the task of corresponding gait adjustment is completed under natural environment, acquires corresponding big
Brain hemoglobin information, it follows that the recognition result of state be more advantageous to for walk help/rehabilitation equipment；Gait adjustment from
Main control to obtain cortex biological information under the Nature condition of cognitive activities, increases the practical application valence of recognizer
Value, to realize that the practicable walk-aid equipment based on brain-computer interface technology lays the foundation；
Present invention employs the methods of Mathematical Morphology Filtering combination Chebyshev's low-pass filtering, can be effectively removed low frequency
The noise element of frequency range interested keeps the morphological character of low frequency signal, while can also filter out the invalid radio-frequency component of redundancy, this
It is more advantageous to and guarantees that the stabilization of signal is effective, perform guarantee for subsequent identification；
The present invention calculates the hemoglobin concentration of brain area using entropy assessment instead of traditional method of average, by this method meter
The brain area hemoglobin concentration value of calculating has higher robustness, can effectively weaken the influence of individual difference；
The present invention is based on the Integrated Algorithms of stacking, propose two layers of SVM model, the model is relative to single SVM mould
Type has better Generalization Capability and higher recognition effect, can be effectively applied in the practical application of Inter-BCI.
Detailed description of the invention
Fig. 1 is the knowledge that a variety of walking step states adjustment disclosed by the embodiments of the present invention based on brain hemoglobin information is intended to
Four kinds of gait adjustment state timing charts in other method.
Fig. 2 is the knowledge that a variety of walking step states adjustment disclosed by the embodiments of the present invention based on brain hemoglobin information is intended to
Other method deutocerebrum cortex motion association region and TCH test channel distribution map.
Fig. 3 is the knowledge that a variety of walking step states adjustment disclosed by the embodiments of the present invention based on brain hemoglobin information is intended to
The effect picture of mathematical morphology filter combination Chebyshev low-pass filtering method is used in other method.
Fig. 4 is the knowledge that a variety of walking step states adjustment disclosed by the embodiments of the present invention based on brain hemoglobin information is intended to
The pattern-recognition frame figure of other method kind.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings and specific examples, so that those skilled in the art can be with
It more fully understands the present invention and can be practiced, but illustrated embodiment is not as a limitation of the invention.
Fig. 4 is arrived refering to fig. 1, and table 1 arrives table 3, a kind of a variety of gait adjustment intention assessments based on brain hemoglobin information
Method, the specific steps are as follows:
(1) application near infrared spectrum brain imaging technique (NIRS) carries out test experiments, and subject completes in fixed area
The task of corresponding walking step state adjustment；
(2) the cortex hemoglobin concentration that records walking step state time adjustment, carries out the pretreatment of data；
(3) carries out corresponding pretreated cortex hemoglobin information according to the distribution in cerebral function region
Channel divides, and calculates and extract relevant parameter as feature；
(4) application model recognizer establishes the detection model of four kinds of gait adjustments intention.
Present invention application near infrared spectrum brain imaging technique (NIRS) carries out test experiments, easy to operate, has portable
Advantage, it is low to the susceptibility of environmental noise to the of less demanding of external environment, and subject will not be generated any negative
Effect.Subject carries NIRS equipment in entire test process, and the task of corresponding gait adjustment is completed under natural environment,
Thus the recognition result of the state obtained is more advantageous to for walk help/rehabilitation equipment；The autonomous control of gait adjustment recognizing
Know acquisition cortex biological information under movable Nature condition, increases the practical application value of recognizer, it is practical to realize
The feasible walk-aid equipment based on brain-computer interface technology lays the foundation.
Preferably, leg speed increases in step (1), leg speed reduces, step-length increases and step-length reduces four kinds of gait adjustments
Every kind all continuously performs 2 times, and the time of having a rest between task and task about 40 seconds.
Preferably, to resulting oxygen-containing hemoglobin parameters are acquired in step (2), using morphologic filtering and Qie Bi
Snow husband filters the method combined, the pretreatment of Lai Shixian signal.The low-pass filter of Chebyshev, filter cutoff are used first
Frequency is 0.145Hz, filters out the radio-frequency component in signal, retains the frequency content of neuron activity.Then, using Mathematical morphology filter
The method of wave, the method for combination make and break filtering and opening and closing filtering, the correction of baseline is carried out to signal, removes drift.Such side
Method more can guarantee the morphological character of low frequency signal, effectively remove the noise element of low frequency frequency range interested, while can also filter superfluous
Remaining invalid radio-frequency component.
It is grasped preferably, step (3) carries out the related of Feature Engineering to pretreated cortex hemoglobin information
Make.
Preferably, step (3) specific implementation is as follows:
(3-1) carries out corresponding channel division according to the distribution in cerebral function region, and is counted according to the channel respectively contained
The blood oxygen concentration value of corresponding region is calculated, which calculates gained by entropy assessment.Steps are as follows for its calculating, with calculating each channel first
Secondly comentropy is calculated the weight in each channel based on comentropy, finally obtains corresponding region according to weighted mean method
Blood oxygen concentration value；
(3-2) calculates the corresponding parameter of hemoglobin, statistical nature, entropy feature including the oxygen content of blood to each brain area
With the three categories feature such as correlated characteristic, include mean value, energy, variance, very poor, comentropy and Pearson correlation coefficients etc..With
This is as original feature space.
Preferably, step (4) specific implementation is as follows:
(4-1) examines whether the feature under different conditions is in same distribution using Kolmogorov-Smirnov, if
This feature is in and is same as being distributed, then shows that this feature has no ability to differentiation state, should give rejecting, pass through the spy of such filtering type
Selection mode is levied, preliminary screening is carried out, obtains proper subspace.
(4-2) carries out principal component analysis to proper subspace, carries out dimensionality reduction to feature, and choose preceding 95% contribution rate
Principal component, the dimension reduction space as feature.
(4-3) realizes two layers of stacking supporting vector machine model using the Ensemble Learning Algorithms (stacking) stacked
(stacking-SVMs).For the SVM model of first layer, dimension reduction space is picked out optimal using Annealing-Genetic Algorithm
15 groups of feature combinations, and 15 groups of SVM models are constructed with this.For the SVM model of the second layer, then 15 SVM moulds to upper one layer
Type with SVM is and base classifier Stacking algorithm is integrated, and still takes Annealing-Genetic Algorithm, carrys out the super of optimizing SVM
Parameter such as penalty coefficient.
(4-4) is detected according to the model of foundation, obtains testing result.
The subregion channel number of 1 further division of table
| Subregion title | Channel number | Subregion title | Channel number |
| PFClu | (Isosorbide-5-Nitrae, 5) | PFClw | (3,5,8) |
| PFCll | (1,3,8) | PFCmw | (5,6,9) |
| PFClr | (1,5,8) | PFCwl1 | (5,8,9) |
| PFCul | (1,2,5) | PRFrw | (6,7,10) |
| PFCmu | (2,5,6) | PFCwr | (6,9,10) |
| PFCml | (2,5,9) | PMCll | (11,14,18) |
| PFCmr | (2,6,9) | SMAuu | (12,15,16) |
| PFCur | (2,3,6) | SMAll | (12,15,19) |
| PFCru | (2,6,7) | SMArr | (12,16,19) |
| PFCrl | (2,6,10) | PMCrr | (13,17,20) |
| PFCrr | (2,7,10) | SMAww | (15,16,19) |
1. data normalization of calculation formula of 2 sub-district thresholding of table normalizes formula using minimax:
The channel For j=1 to M:
2. the weight in each channel in zoning:
The channel For j=1 to M
2.1 calculate the probability of each sampled point:
2.2 calculate the comentropy in each channel:
2.3 calculate the weight in each channel
3. zoning blood oxygen levels:
The calculation formula of 3 three categories feature of table
A kind of computer equipment can be run on a memory and on a processor including memory, processor and storage
The step of computer program, the processor realizes any one the method when executing described program.
A kind of computer readable storage medium, is stored thereon with computer program, realization when which is executed by processor
The step of any one the method.
A kind of processor, the processor is for running program, wherein described program executes described in any item when running
Method.
Embodiment described above is only to absolutely prove preferred embodiment that is of the invention and being lifted, protection model of the invention
It encloses without being limited thereto.Those skilled in the art's made equivalent substitute or transformation on the basis of the present invention, in the present invention
Protection scope within.Protection scope of the present invention is subject to claims.
Claims (9)
1. a kind of recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to characterized by comprising
To the cortex hemoglobin concentration that walking step state time adjustment is recorded, the pretreatment of data is carried out；Wherein, the row
The cortex hemoglobin concentration that gait time adjustment is recorded is walked to refer to by " using near infrared spectrum brain imaging technique
(NIRS) test experiments are carried out, subject completes the task of corresponding walking step state adjustment in fixed area；" obtain；
For pretreated cortex hemoglobin information, corresponding channel is carried out according to the distribution in cerebral function region and is drawn
Point, and calculate and extract relevant parameter as feature；
Application model recognizer establishes the detection model of four kinds of gait adjustments intention.
2. the recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to as described in claim 1, special
Sign is, " carries out test experiments using near infrared spectrum brain imaging technique (N I RS), subject completes phase in fixed area
The task for the walking step state adjustment answered；" in, leg speed increases, leg speed reduces, step-length increases and step-length four kinds of gait adjustments of reduction are every
Kind all continuously performs 2 times, and the time of having a rest between task and task about 40 seconds.
3. the recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to as described in claim 1, special
Sign is, " to the cortex hemoglobin concentration that walking step state time adjustment is recorded, carries out the pretreatment of data；" carry out in advance
The method of processing is specific as follows:
Using the low-pass filter of Chebyshev, filter cutoff frequency 0.145Hz filters out the radio-frequency component in signal, retains
The frequency content of neuron activity；
Using the method for morphologic filtering, the method for combining make and break filtering and opening and closing filtering carries out the correction of baseline to signal, goes
Except drift.
4. the recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to as described in claim 1, special
Sign is, " for pretreated cortex hemoglobin information, carries out corresponding channel according to the distribution in cerebral function region
It divides, and calculates and extract relevant parameter as feature；" in, pretreated cortex hemoglobin information is carried out special
Levy the relevant operation of engineering.
5. the recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to as described in claim 1, special
Sign is, " for pretreated cortex hemoglobin information, carries out corresponding channel according to the distribution in cerebral function region
It divides, and calculates and extract relevant parameter as feature；" specifically include:
With calculating each channel first comentropy, secondly calculates the weight in each channel based on comentropy, and final basis adds
Weight average method obtains the blood oxygen concentration value in corresponding region；
The corresponding parameter of hemoglobin, statistical nature, entropy feature and correlated characteristic including the oxygen content of blood are calculated to each brain area
Equal three categories feature, includes mean value, energy, variance, very poor, comentropy and Pearson correlation coefficients, in this, as original
Feature space.
6. the recognition methods that a variety of walking step states adjustment based on hemoglobin information is intended to as described in claim 1, special
Sign is that " application model recognizer establishes the detection model of four kinds of gait adjustments intention." specifically include:
Examine whether the feature under different conditions is in same distribution using Kolmogorov-Smirnov, if this feature
In being same as being distributed, then shows that this feature has no ability to differentiation state, should give rejecting, pass through the feature selecting of such filtering type
Mode carries out preliminary screening, obtains proper subspace；
Principal component analysis is carried out to proper subspace, dimensionality reduction is carried out to feature, and choose the principal component of preceding 95% contribution rate, as
The dimension reduction space of feature；
Using the Ensemble Learning Algorithms (stacking) of stacking, two layers of stacking supporting vector machine model (stacking- is realized
SVMs)；For the SVM model of first layer, 15 groups of optimal feature groups are picked out using Annealing-Genetic Algorithm to dimension reduction space
It closes, and 15 groups of SVM models is constructed with this；For the SVM model of the second layer, then with SVM be to upper one layer of 15 SVM models and
Base classifier Stacking algorithm is integrated, and still takes Annealing-Genetic Algorithm, and the hyper parameter for carrying out optimizing SVM, which is such as punished, is
Number；
It is detected according to the model of foundation, obtains testing result.
7. a kind of computer equipment including memory, processor and stores the meter that can be run on a memory and on a processor
Calculation machine program, which is characterized in that the processor realizes any one of claims 1 to 6 the method when executing described program
Step.
8. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
The step of any one of claims 1 to 6 the method is realized when row.
9. a kind of processor, which is characterized in that the processor is for running program, wherein right of execution when described program is run
Benefit requires 1 to 6 described in any item methods.
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| CN109710065A (en) * | 2018-12-18 | 2019-05-03 | 苏州大学 | Walking based on brain hemoglobin information adjusts the recognition methods being intended to |
| CN110384506A (en) * | 2019-06-06 | 2019-10-29 | 苏州布芮恩智能科技有限公司 | The recognition methods that walking based on brain hemoglobin information is intended to |
| CN111950441A (en) * | 2020-08-10 | 2020-11-17 | 苏州大学 | FNIRS real-time decoding method and system for upper limb movement intention |
| CN112022136A (en) * | 2020-09-11 | 2020-12-04 | 国家康复辅具研究中心 | Near-infrared brain function and gait parameter based assessment method and system |
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| CN113647938A (en) * | 2021-08-18 | 2021-11-16 | 苏州大学 | Method and system for advanced detection of motion state change based on physiological signals |
| CN114423341A (en) * | 2019-07-16 | 2022-04-29 | 纽洛斯公司 | System and method for camera-based quantification of blood biomarkers |
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