CN106901732A - The measuring method and measurement apparatus of muscular strength and Muscle tensility under mutation status - Google Patents
The measuring method and measurement apparatus of muscular strength and Muscle tensility under mutation status Download PDFInfo
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- CN106901732A CN106901732A CN201710244946.6A CN201710244946A CN106901732A CN 106901732 A CN106901732 A CN 106901732A CN 201710244946 A CN201710244946 A CN 201710244946A CN 106901732 A CN106901732 A CN 106901732A
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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
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/389—Electromyography [EMG]
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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
- A61B5/107—Measuring physical dimensions, e.g. size of the entire body or parts thereof
- A61B5/1071—Measuring physical dimensions, e.g. size of the entire body or parts thereof measuring angles, e.g. using goniometers
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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
- A61B5/22—Ergometry; Measuring muscular strength or the force of a muscular blow
- A61B5/224—Measuring muscular strength
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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
- A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
- A61B5/4519—Muscles
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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
- A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
- A61B5/4528—Joints
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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
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
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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
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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
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
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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
- A61B5/7253—Details of waveform analysis characterised by using transforms
Abstract
The invention discloses muscular strength under a kind of mutation status and the measuring method and measurement apparatus of Muscle tensility, the measuring method is comprised the following steps：Collection electromyographic signal corresponding with Muscle tensility with muscular strength to be determined；Framing is carried out to the surface electromyogram signal for collecting using the sliding window of regular length, the HHT marginal spectrum entropys calculated per frame signal are moved by frame；The number of the HHT marginal spectrum entropys of continuous effective is calculated, if number is more than setting value, the initial time for judging the HHT marginal spectrum entropys of continuous effective is muscular strength and Muscle tensility state mutation point；And muscular strength and Muscle tensility are measured according to the electromyographic signal of the preseting length after muscular strength and Muscle tensility state mutation point.The present invention realizes the identification of muscular strength and Muscle tensility mutation status point using the method that Time-Frequency Analysis are combined with nonlinear kinetics, time-domain analysis is carried out to electromyographic signal after catastrophe point simultaneously, realize the measurement of muscular strength or Muscle tensility under mutation status, individual difference can be eliminated, the accuracy of muscular strength and Muscle tensility measurement is improve.
Description
Technical field
The present invention relates to muscular strength under a kind of mutation status and the measuring method and measurement apparatus of Muscle tensility.
Background technology
In the analyzing and processing of electromyographic signal, state mutation point can with Muscle tensility (i.e. muscular strength and/or Muscle tensility) for identification muscular strength
For intention assessment, motion state monitoring, spasm detection etc., it is always the focus of research, while being also Research Challenges.
Conventional electromyographic signal analysis at present has two methods of time-domain and frequency-domain with treatment research method, due to electromyographic signal
A kind of complicated physiological signal, with non-stationary and non-linear, and its it is faint be easily disturbed, therefore simple time-domain analysis
Method is not enough to the analytic ability of electromyographic signal.
And conventional frequency-domain analysis method, such as FFT, it is adaptable to periodic signal, for this aperiodicity of electromyographic signal
Signal is not applied to simultaneously.Using Time Domain Analysis the identification of conventional state mutation point at present, it is contemplated that the spy of electromyographic signal more
Property, time-domain processing method easily causes erroneous judgement, it is impossible to ensure the accuracy of identification.And it is relatively specific for the side of electromyographic signal analysis
Although research of the method such as wavelet analysis in terms of electromyographic signal analyzing and processing is carried out for a long time, and has made some progress,
Due to there are problems that electromyographic signal is complicated, calculate complexity, real-time, and nobody is applied to muscular strength and Muscle tensility
The identification of state mutation point.
Existing muscular strength is only limitted to Time Domain Analysis with the recognition methods of Muscle tensility state mutation point, causes catastrophe point
Identification is not accurate enough, and real-time is even more and is difficult to ensure that, it is impossible to preferably meet the demands such as intention assessment, spasm detection.
Muscular strength has great importance with the measurement of Muscle tensility under mutation status, such as Athletess assessment of function, spasm
Qualitative assessment etc. be required to realize the measurement of muscular strength and Muscle tensility under mutation status.Muscular strength is corresponding to Muscle tensility mutation process
Muscle starts to raise electric signal, therefore electromyographic signal can reflect the state of muscular strength and Muscle tensility.
But the measuring method based on muscular strength and Muscle tensility conventional at present only considers overall electromyographic signal and muscular strength or flesh
The relation of tension force, does not account for being mutated the change procedure of front and rear electromyographic signal, causes the survey of muscular strength and Muscle tensility under mutation status
Amount result is inaccurate.
The content of the invention
It is an object of the invention to provide the measuring method of muscular strength under a kind of mutation status and Muscle tensility, with improve muscular strength with
The accuracy of Muscle tensility measurement.
Measurement apparatus the present invention also aims to provide muscular strength and Muscle tensility under a kind of mutation status, to improve muscular strength
The accuracy measured with Muscle tensility.
Therefore, one aspect of the present invention provides the measuring method of muscular strength and Muscle tensility under a kind of mutation status, using time-frequency
The method that domain analysis method is combined with nonlinear kinetics judges muscular strength and Muscle tensility state mutation point, recognizes state mutation point
Afterwards, the measurement for realizing muscular strength or Muscle tensility under mutation status is analyzed to electromyographic signal after catastrophe point, is comprised the following steps：Adopt
Collection electromyographic signal corresponding with Muscle tensility with muscular strength to be determined；Sliding window using regular length is believed the surface myoelectric for collecting
Number framing is carried out, the HHT marginal spectrum entropys calculated per frame signal are moved by frame；The number of the HHT marginal spectrum entropys of continuous effective is calculated,
If number is more than setting value, the initial time for judging the HHT marginal spectrum entropys of the continuous effective is muscular strength and Muscle tensility state
Catastrophe point；And muscular strength is measured with flesh according to the electromyographic signal of the preseting length after muscular strength and Muscle tensility state mutation point
Power.
Further, the number for calculating the HHT marginal spectrum entropys of continuous effective includes：Setting adaptive threshold, will be less than institute
The HHT marginal spectrums entropy for stating adaptive threshold is rejected as invalid marginal spectrum entropy, and remaining HHT marginal spectrums entropy is used as effective limit
Spectrum entropy is retained；And calculate the continuous number of effective marginal spectrum entropy.
Further, the number for calculating the HHT marginal spectrum entropys of continuous effective also includes：It is right before adaptive threshold is set
HHT marginal spectrum entropys are processed to improve sensitivity.
Further, processed HHT marginal spectrum entropys as follows to put forward highly sensitive mode：
Wherein,It is HHT marginal spectrum entropys, k is scale factor, and N is the n powers of amplitude.
Further, synchronous acquisition joint angles corresponding with electromyographic signal are gone back when electromyographic signal is gathered；And sentencing
Determine muscular strength with after Muscle tensility state mutation point, determine corresponding with Muscle tensility state mutation point with muscular strength joint angles.
According to another aspect of the present invention, there is provided the measurement apparatus of muscular strength and Muscle tensility under a kind of mutation status, including
Computer equipment, the computer equipment include memory, processor and storage on a memory and can run on a processor
Computer program, realize following steps during the computing device described program：Collection and muscular strength to be determined and Muscle tensility pair
The electromyographic signal answered；Framing is carried out to the surface electromyogram signal for collecting using the sliding window of regular length, is moved by frame and calculated
HHT marginal spectrum entropys per frame signal；The number of the HHT marginal spectrum entropys of continuous effective is calculated, if number is more than setting value, is judged
The initial time of the HHT marginal spectrum entropys of the continuous effective is muscular strength and Muscle tensility state mutation point；And according to muscular strength and flesh
The electromyographic signal of the preseting length after tension state catastrophe point measures muscular strength and Muscle tensility.
Further, the number of the HHT marginal spectrum entropys of above-mentioned calculating continuous effective includes：Setting adaptive threshold, will be low
Rejected as invalid marginal spectrum entropy in the HHT marginal spectrums entropy of the adaptive threshold, remaining HHT marginal spectrum entropy is used as effective
Marginal spectrum entropy is retained；And calculate the continuous number of effective marginal spectrum entropy.
Further, the number of the HHT marginal spectrum entropys of above-mentioned calculating continuous effective also includes：Setting adaptive threshold it
It is preceding that HHT marginal spectrum entropys are processed to improve sensitivity.
Further, following steps are also realized during above-mentioned computing device described program：Collection with muscular strength to be determined with
Synchronous acquisition joint angles corresponding with electromyographic signal are gone back during the corresponding electromyographic signal of Muscle tensility；And judging muscular strength with flesh
After power state mutation point, determine joint angles corresponding with Muscle tensility state mutation point with the muscular strength.
Further, above-mentioned measurement apparatus for spasm detect, wherein, the Muscle tensility state mutation point be spasm starting
Point, the corresponding joint angles of the spasm starting point are stretch reflex threshold value.
Further, the root mean square of the electromyographic signal of the preseting length after utilization state catastrophe point of the present invention realizes spasm
Evaluation.
The present invention realizes muscular strength and Muscle tensility mutation status using the method that Time-Frequency Analysis are combined with nonlinear kinetics
The identification of point, while carrying out time-domain analysis to electromyographic signal before and after catastrophe point, realizes the survey of muscular strength or Muscle tensility under mutation status
Amount, can eliminate individual difference, improve the accuracy of muscular strength and Muscle tensility measurement.
Wherein, muscular strength recognized with Muscle tensility mutation status point using the HHT marginal spectrums entropy of the continuous effective for setting number,
The accuracy of catastrophe point identification can be ensured.Further, processed by HHT marginal spectrum entropys, improve muscular strength and flesh
The sensitivity of tension state catastrophe point identification.It is poor that improved HHT marginal spectrums entropy solves the existing complicated real-time of entropy calculating
Problem.In combination with the measurement of joint angles, the detection of muscular strength and/or the corresponding angle position of Muscle tensility is capable of achieving.
In addition to objects, features and advantages described above, the present invention also has other objects, features and advantages.
Below with reference to figure, the present invention is further detailed explanation.
Brief description of the drawings
The Figure of description for constituting the part of the application is used for providing a further understanding of the present invention, of the invention to show
Meaning property and its illustrates, for explaining the present invention, not constitute inappropriate limitation of the present invention embodiment.In the accompanying drawings：
Fig. 1 is the flow chart of muscular strength and the measuring method of Muscle tensility under mutation status of the invention；
Fig. 2 is the computer program of muscular strength according to an embodiment of the invention and the recognition methods of Muscle tensility state mutation point
Algorithm flow chart；
Fig. 3 is that the waveform and HHT marginal spectrums entropy corresponding with it of electromyographic signal according to an embodiment of the invention pass through
The comparison diagram of the waveform after rectification；
Fig. 4 be electromyographic signal according to another embodiment of the present invention waveform and corresponding improvement after HHT limit
Compose comparison diagram of the entropy through the waveform after over commutation；And
Fig. 5 is the structured flowchart of muscular strength and the measurement apparatus of Muscle tensility under mutation status of the invention.
Specific embodiment
It should be noted that in the case where not conflicting, the feature in embodiment and embodiment in the application can phase
Mutually combination.Describe the present invention in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
After the present invention finds state mutation point according to electromyographic signal feature before and after mutation status, myoelectricity letter after analysis catastrophe point
Number, realize the measurement of muscular strength or Muscle tensility under mutation status.
Fig. 1 to Fig. 5 shows some embodiments of the invention.
As shown in figure 1, muscular strength of the invention is comprised the following steps with Muscle tensility measuring method：
S10, collection electromyographic signal corresponding with Muscle tensility with muscular strength to be measured；
When measuring method of the invention is used for intention assessment and motion state is monitored, in this step, preferential use is worn
Wear formula collecting device to gather electromyographic signal, such as Wearable movable bracelet disclosed in Chinese patent ZL201410001577.4,
It is worn on large arm or forearm, you can the corresponding electromyographic signal of collection；When measuring method of the invention is detected for spasm, except
Detection electromyographic signal, also detects joint angles simultaneously.
S20, framing is carried out to the surface electromyogram signal for collecting using the sliding window of regular length, moved by frame and calculate every
The HHT marginal spectrum entropys of frame signal；And
In this step, in some scenarios, electromyographic signal is selectively pre-processed, the pretreatment is mainly
Denoising, in other occasions, without being pre-processed to the electromyographic signal for gathering.
In this step, more than the length that frame is moved, the regular length of such as sliding window takes at 90 points to the regular length of sliding window,
The length that frame is moved takes at 3 points, and the frame moves length and chooses other values also dependent on needs.Wherein, points are according to amount of calculation and calculating
The degree of accuracy is chosen, and the calculating small for requiring amount of calculation can choose less point, otherwise should increase points.
The computational methods of the HHT marginal spectrum entropys per frame signal are as follows：
Hilbert-Huang transform (Hilbert-Huang transform, HHT) is a kind of new Time-Frequency Analysis Method, by
The characteristics of its adaptivity and time frequency resolution high, it is highly suitable for processing non-linear, non-stationary signal.And comentropy conduct
Complexity index, characterizes the general characteristic of information source from average, represents the average information of information source output.To a certain spy
Determine information source, comentropy is bigger, illustrate that signal component is more uniform, do not know bigger.
HHT is by empirical mode decomposition (Empirical Mode Decomposition, EMD) and Hilbert conversion compositions.
Decomposed by EMD, follow-up Hilbert conversion and tectonic knot function are carried out to each IMF components, signal x (t) can be expressed as：
Wherein, Re takes real part, ai(t)、f(t)、Instantaneous amplitude, instantaneous frequency and instantaneous phase are represented respectively.Definition
Hilbert-Huang time-frequency spectrums, the time of representation signal amplitude and frequency distribution：
(2) are carried out with the Hilbert marginal spectrums that time integral obtains signal：
Marginal spectrum is that the corresponding amplitude addition of CF that will be distributed in the whole time period is obtained, and expresses each
Amplitude accumulation of the signal frequency within the whole time period.
By the definition of marginal spectrum, for discrete Frequency point f=i Δ f, then have：
Wherein, n is frequency-distributed points of the signal in analysis frequency range.
According to the definition of comentropy, HHT marginal spectrum entropys are represented by：
In formula, pi=h (i)/∑ h (i), represents i-th probability of frequency correspondence amplitude.
It is to normalize in the range of [0,1] entropy, then has
HHE '=HHE/lnN------------------------------------ (6)
N is the sequence length of h (i).
The waveform and its HHT marginal spectrum entropys of the electromyographic signal of certain subject (upper limb spasm patient) are chosen after over commutation
Waveform figure 3 illustrates.
The number of S30, the HHT marginal spectrum entropys of calculating continuous effective, judges the continuous effective if more than setting value
The initial time of HHT marginal spectrum entropys is muscular strength and Muscle tensility state mutation point.
For the electromyographic signal of different parts, setting value is different, and setting value is typically chosen more than or equal to 50, for example, exist
Value in the range of 50-500.
S40, muscular strength and flesh are measured according to the electromyographic signal of the preseting length after muscular strength and Muscle tensility state mutation point
Power.
Preferably, in this step, Time Domain Processing is carried out to surface electromyogram signal after mutation status, flesh after catastrophe point is obtained
The root mean square of electric signal to realize the measurement of muscular strength and Muscle tensility under mutation status, in one example, with Muscle tensility adopt by the muscular strength
Characterized with magnitude of voltage (μ V), realize muscular strength and Muscle tensility Measurement and evaluation.Wherein, the preseting length of electromyographic signal is according to muscular strength and flesh
The mutation status of tension force set, for example, after Flexor spasticity patient's Muscle tensility catastrophe point the preseting length of electromyographic signal it is suitable
Span is 0.1-1.5 seconds.
The present invention recognizes muscular strength and Muscle tensility mutation status using the HHT marginal spectrums entropy of the continuous effective for setting number
Point, has quantified distinguishing indexes, it is ensured that the accuracy of catastrophe point identification.
In one embodiment, the number for calculating the HHT marginal spectrum entropys of continuous effective includes：Setting adaptive threshold, will be low
Rejected as invalid marginal spectrum entropy in the HHT marginal spectrums entropy of the adaptive threshold, remaining HHT marginal spectrum entropy is used as effective
Marginal spectrum entropy is retained；And calculate the continuous number of effective marginal spectrum entropy.In the present embodiment, can be by Muscle tensility catastrophe point
Recognition quantitative, it is to avoid the subjectivity of state mutation point identification is random.
In one embodiment, the Processing Algorithm of electromyographic signal is as shown in Figure 2：90 o'clock sliding windows minute are carried out to electromyographic signal
Frame, it is 3 points that frame is moved, and calculates the HHT marginal spectrum entropy per frame signal and is designated as MSEn.Setting adaptive threshold is to marginal spectrum entropy afterwards
Carry out rectification and obtain En, the MsEn values that will be less than Th set to 0, remain larger than the MsEn values of Th.En values after certain moment rectification are big
In 0, and the 50 En values for continuing are when being all higher than 0, and the moment is to be judged to Muscle tensility catastrophe point.This embodiment gives
Application of this measuring method in the identification of spasm starting point, i.e., using the reality of bicipital muscle of arm sEMG signal identification spasm starting points
Example.
Wherein, above-mentioned adaptive threshold Th determines according to below equation：
Th=min (MsEn)+λ [max (MsEn)-min (MsEn)] --- --- --- --- --- --- --- (7)
In one embodiment, min (MsEn) is the minimum value of HHT marginal spectrum entropys in all frames, and [max (MsEn) is all
The minimum value of HHT marginal spectrums entropy in frame, λ takes 0.3.
Although before and after muscular strength and Muscle tensility state mutation point there is certain otherness in the entropy of electromyographic signal, but set
Threshold value carries out occurring in that repeatedly continuous is not 0 point in basal signal of the entropy after rectification before state mutation point that influence is led
Open the accuracy of reflection myoelectricity threshold determination.For before searching out and more significantly can reflecting muscular strength and Muscle tensility state mutation point
The index of the change of signal, improves the accuracy of recognizer afterwards, and above-mentioned entropy acquiring method is accordingly improved, before and after making
Signal entropy value difference alienation is more obvious.
In improving embodiment one, the number for calculating the HHT marginal spectrum entropys of continuous effective includes：First to HHT marginal spectrum entropys
Processed to improve sensitivity；Setting adaptive threshold, to the HHT marginal spectrum entropys after the treatment less than the adaptive threshold
Rejected as invalid marginal spectrum entropy, the HHT marginal spectrums entropy after remaining treatment is retained as effective marginal spectrum entropy；And
Calculate the continuous number of effective marginal spectrum entropy.
The feature of HHT marginal spectrum entropys is analyzed, due to reasons such as normalization, entropy is finally limited in the range of (0,1), difficult
So that the difference before and after signal is significantly depicted, based on this, the thought using amplitude Nth power and scale factor k is proposed, and removal is returned
One changes, and the computational methods to HHT marginal spectrum entropys are improved, sensitive with what Muscle tensility state mutation point was recognized to improve muscular strength
Degree:
Analysis entropy scope and experimental result, this time test certainty factor coefficient N=2, k=0.5 best results.
The waveform (waveform rectification) of the HHT marginal spectrum entropys after the waveform of same electromyographic signal and its improvement is in fig. 4
Show, comparison diagram 3 and Fig. 4, the entropy otherness of electromyographic signal becomes big before and after state mutation point P, and significant difference, given threshold is entered
Entropy after the row rectification almost all in basal signal is 0, illustrate that the algorithm after improvement increased the accuracy of interpretation threshold value
And sensitiveness.
As shown in figure 5, muscular strength includes with the measurement apparatus of Muscle tensility under mutation status of the invention：Computer sets
Standby, the computer equipment includes memory 31, processor 32, display 33 and storage on memory 31 and can process
The computer program run on device 32, also including surface myoelectric signal collection apparatus 20, surface electromyogram signal acquisition module includes
Surface electromyogram signal sensor and electromyographic signal processing module, the electromyographic signal processing module include and angular transducer electricity
Property connection modulate circuit and modulate circuit connection A/D modular converters and be connected with A/D modular converters signal transmission mould
Block.
The processor 32 realizes following steps when performing described program：S10, collection and muscular strength to be determined and Muscle tensility pair
The electromyographic signal answered；After S20, the signal to gathering are pre-processed, using the sliding window of regular length to the surface that collects
Electromyographic signal carries out framing, and the HHT marginal spectrum entropys calculated per frame signal are moved by frame；S30, the HHT limits for calculating continuous effective
The number of entropy is composed, the initial time that the HHT marginal spectrum entropys of the continuous effective are judged if more than setting value is muscular strength and flesh
Power state mutation point；And S40, flesh is measured according to the electromyographic signal of the preseting length after muscular strength and Muscle tensility state mutation point
Power and Muscle tensility.
Measuring method of the invention and device can be additionally used in the identification and stretch reflex of spasm starting point (spasm catastrophe point)
The determination of threshold value and spasm ranking is realized according to the root mean square of the electromyographic signal after spasm catastrophe point.
Spasm evaluation plays vital effect, such as formulation of rehabilitation scheme, anti-spasm in clinical and scientific research
Adjustment of drug dose etc., is required to doctor and objective, accurate evaluation is made to Muscle tensility.Conventional grade formula spasm clinical at present
Scale is MAS (improvement Ashworth scale, Modified Ashworth Scale), and its evaluation result relies primarily on evaluation person
Subjective judgement, division description of the scale for spasm grade in itself is also relatively fuzzyyer, category sxemiquantitative description, it is difficult to accurately reflect
Spasm situation, and data are not easy to maintain, can not meet objective, accurate, quantitative evaluation requirement.
Existing document proves that electromyographic signal can effectively symbolize stretch reflex threshold value.But it is currently based on leading for sEMG signals
Open reflex threshold detection method and be based primarily upon artificial vision's method and time domain relevant parameter method.Artificial vision's method passes through vision-based detection
SEMG change points, subjectivity is big, it is impossible to which the spasm evaluation for meeting accurate objective is required.Additionally, due to diverse location motor unit
Electromyographic signal, the time that action potential reaches collection point experience is different, shows different phase and amplitude, these phases and width
The different signal of value is unordered to be superimposed with regard to the non-stationary of sEMG much of that.There is scholar to point out simultaneously, muscle is in not
Under same pattern and motion state, the kinesitherapy nerve unit of muscle activity is participated in discharge time, quantity and conduction speed
Difference can be all shown in rate, these phenomenons are referred to as the change of motion complexity in terms of dynamics.And electromyographic signal is faint easily
It is disturbed, therefore simple time domain and frequency-domain analysis method can be not enough to the analytic ability of electromyographic signal.
Therefore, the HHT marginal spectrums entropy and articulation angle judgement spasm catastrophe point of present invention proposition combination muscle sEMG,
The spasm Measurement and evaluation device of stretch reflex threshold value, spasm grade.
Again as shown in figure 5, above-mentioned measurement apparatus combination angle acquisition device 10 of the invention is (for gathering measured's Ipsilateral
Joint angles of the elbow joint in passive stretch motion process), it is capable of achieving to judge that stretching is anti-based on surface myoelectric HHT marginal spectrums entropy
Penetrate threshold value (being defined as the corresponding joint angles of Flexor spasticity patient's Muscle tensility catastrophe point).The angle acquisition device is passed including angle
Sensor and signal processing module, the signal processing module include the modulate circuit being electrically connected with angular transducer and conditioning
The A/D modular converters of circuit connection and the signal transmitting module being connected with A/D modular converters.
Wherein, following steps are realized when the processor 32 performs described program：In measured's Ipsilateral elbow joint from flexing
Up to acquisition joint angles and bicipital muscle of arm surface in maximum angle to the passive stretch motion process stretched up to maximum angle
Electromyographic signal；Framing is carried out to the surface electromyogram signal for collecting using the sliding window of regular length, is moved by frame and calculated per frame
The HHT marginal spectrum entropys of signal；The number of the HHT marginal spectrum entropys of continuous effective is calculated, judges described continuous if more than setting value
The initial time of effective HHT marginal spectrum entropys is spasm starting point；The corresponding joint angle angle value of spasm starting point is found out, that is, is obtained
Stretch reflex threshold value；And it is used for the grade of spasm according to the electromyographic signal root mean square of the preseting length after spasticity catastrophe point
Evaluation.
An embodiment of the invention realizes the measurement of upper limbs Flexor spasticity patient's stretch reflex threshold value.Specific steps
It is as follows：
The present embodiment realizes the evaluation of upper limbs Flexor spasticity patient's Muscle tensility.Comprise the following steps that：
(1) collection of bicipital muscle of arm sEMG signals uses the differential input of bikini.Use alcohol wipe skin removed skin
After surface grease and scurf, it is placed at belly of muscle along muscle fibre direction as two electrode slices of the differential input end of myoelectricity,
Another electrode slice is reference ground, is placed on without at muscle activity.Two electrode centers are at a distance of 20mm.Conducting wire is suitably solid
It is fixed, the interference that conducting wire is rocked in reduction action process as far as possible.
To reduce influence of the environmental factor to spasm patient's Ashworth score result, each tester is evaluated same every time
Time period, same place, 25 DEG C of room temperature, each subject takes sedentary posture ensures that in relaxation state evaluation could be received.Comment
Appraisal result is recorded after the completion of fixed, gives researcher to carry out data statistic analysis.
(2) in detection process, the data that each sensor will be detected are processed by modulate circuit, then carry out analog-to-digital conversion
Send afterwards to the display of computer equipment, display can in real time show bicipital muscle of arm surface electromyogram signal during upper extremity exercise
And carry out real-time data memory.
(3) after the above method obtains surface myoelectric data, treatment obtains Muscle tensility catastrophe point, according to the bicipital muscle of arm
The HHT marginal spectrums entropy of sEMG judges Muscle tensility catastrophe point：
Specifically, 90 sliding windows are carried out to original electromyographic signal or by the electromyographic signal that amplitude zero averaging is processed
Framing, it is 3 points that frame is moved, and calculates the HHT marginal spectrum entropy per frame signal and is designated as En.Setting adaptive threshold is to marginal spectrum entropy afterwards
Carry out rectification and obtain MsEn, the MsEn values that will be less than Th set to 0, remain larger than the MsEn values of Th.En values after certain moment rectification
More than 0, and the 50 En values for continuing are when being all higher than 0, and the moment is to be judged to Muscle tensility catastrophe point.
It is pointed out that for some surface myoelectric signal collection apparatus, the original electromyographic signal for being gathered is needed
Zero averaging treatment is carried out, the treatment only integrated regulation amplitude size does not influence on waveform.
(4) after determining Muscle tensility catastrophe point, the electromyographic signal root mean square of regular length after Muscle tensility catastrophe point, root are calculated
According to the quantitative assessment of root mean square information realization Muscle tensility.
The survey for being implemented in combination with stretch reflex threshold value and Muscle tensility that this method passes through surface myoelectric data and joint angles
Amount, realizes the quantitative assessment of spasm, solves the problems, such as that current spasm detection subjectivity is larger.The method is equally applicable to
The assessment of limb extensor spasm, wrist joint spasm and lower limb knee joint and ankle-joint spasm.
The preferred embodiments of the present invention are the foregoing is only, is not intended to limit the invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.It is all within the spirit and principles in the present invention, made any repair
Change, equivalent, improvement etc., should be included within the scope of the present invention.
Claims (10)
1. under a kind of mutation status muscular strength and Muscle tensility measuring method, it is characterised in that using Time-Frequency Analysis method with it is non-
The method that linear dynamics is combined judges muscular strength and Muscle tensility state mutation point, after identification state mutation point, to flesh after catastrophe point
Electric signal is analyzed the measurement for realizing muscular strength or Muscle tensility under mutation status, comprises the following steps：
Collection electromyographic signal corresponding with Muscle tensility with muscular strength to be determined；
Framing is carried out to the surface electromyogram signal for collecting using the sliding window of regular length, is moved by frame and calculated per frame signal
HHT marginal spectrum entropys；
The number of the HHT marginal spectrum entropys of continuous effective is calculated, if number is more than setting value, the HHT of the continuous effective is judged
The initial time of marginal spectrum entropy is muscular strength and Muscle tensility state mutation point；And
Electromyographic signal according to the preseting length after muscular strength and Muscle tensility state mutation point measures muscular strength and Muscle tensility.
2. under mutation status according to claim 1 muscular strength and Muscle tensility measuring method, it is characterised in that calculate continuous
The number of effective HHT marginal spectrum entropys includes：Setting adaptive threshold, will be less than the HHT marginal spectrum entropys of the adaptive threshold
Rejected as invalid marginal spectrum entropy, remaining HHT marginal spectrums entropy is retained as effective marginal spectrum entropy；And calculate effective
The continuous number of marginal spectrum entropy.
3. under mutation status according to claim 2 muscular strength and Muscle tensility measuring method, it is characterised in that calculate continuous
The number of effective HHT marginal spectrum entropys also includes：HHT marginal spectrum entropys are processed before adaptive threshold is set improve
Sensitivity.
4. under mutation status according to claim 3 muscular strength and Muscle tensility measuring method, it is characterised in that to HHT sides
Border spectrum entropy is processed as follows to put forward highly sensitive mode：
Wherein,It is HHT marginal spectrum entropys, k is scale factor, and N is the n powers of amplitude.
5. under mutation status according to claim 1 muscular strength and Muscle tensility measuring method, it is characterised in that in collection flesh
Synchronous acquisition joint angles corresponding with electromyographic signal are gone back during electric signal；And judging muscular strength and Muscle tensility state mutation point
Afterwards, joint angles corresponding with Muscle tensility state mutation point with the muscular strength are determined.
6. under a kind of mutation status muscular strength and Muscle tensility measurement apparatus, including computer equipment, the computer equipment include
Memory, processor and the computer program that store on a memory and can run on a processor, it is characterised in that the place
Reason device realizes following steps when performing described program：
Collection electromyographic signal corresponding with Muscle tensility with muscular strength to be determined；
Framing is carried out to the surface electromyogram signal for collecting using the sliding window of regular length, is moved by frame and calculated per frame signal
HHT marginal spectrum entropys；
The number of the HHT marginal spectrum entropys of continuous effective is calculated, if number is more than setting value, the HHT of the continuous effective is judged
The initial time of marginal spectrum entropy is muscular strength and Muscle tensility state mutation point；And
Electromyographic signal according to the preseting length after muscular strength and Muscle tensility state mutation point measures muscular strength and Muscle tensility.
7. under mutation status according to claim 6 muscular strength and Muscle tensility measurement apparatus, it is characterised in that calculate continuous
The number of effective HHT marginal spectrum entropys includes：Setting adaptive threshold, will be less than the HHT marginal spectrum entropys of the adaptive threshold
Rejected as invalid marginal spectrum entropy, remaining HHT marginal spectrums entropy is retained as effective marginal spectrum entropy；And calculate effective
The continuous number of marginal spectrum entropy.
8. under mutation status according to claim 7 muscular strength and Muscle tensility measurement apparatus, it is characterised in that calculate continuous
The number of effective HHT marginal spectrum entropys also includes：HHT marginal spectrum entropys are processed before adaptive threshold is set improve
Sensitivity.
9. under mutation status according to claim 7 muscular strength and Muscle tensility measurement apparatus, it is characterised in that the treatment
Device also realizes following steps when performing described program：It is also same when electromyographic signal corresponding with Muscle tensility with muscular strength to be determined is gathered
Step collection joint angles corresponding with electromyographic signal；And after muscular strength and Muscle tensility state mutation point is judged, determination with it is described
Muscular strength joint angles corresponding with Muscle tensility state mutation point.
10. under mutation status according to claim 9 muscular strength and Muscle tensility measurement apparatus, it is characterised in that the survey
Device is measured to be detected for spasm, wherein, the Muscle tensility state mutation point is spasm starting point, and the spasm starting point is corresponding
Joint angles are stretch reflex threshold value.
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