CN105771087A - Rehabilitation training system based on music and myoelectricity feedback simulating - Google Patents
Rehabilitation training system based on music and myoelectricity feedback simulating Download PDFInfo
- Publication number
- CN105771087A CN105771087A CN201610209984.3A CN201610209984A CN105771087A CN 105771087 A CN105771087 A CN 105771087A CN 201610209984 A CN201610209984 A CN 201610209984A CN 105771087 A CN105771087 A CN 105771087A
- Authority
- CN
- China
- Prior art keywords
- signal
- unit
- music
- myoelectricity
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
- A61N1/36003—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation of motor muscles, e.g. for walking assistance
-
- 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
- A61B5/1118—Determining activity level
-
- 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
-
- 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]
-
- 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
-
- 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
- A61N1/3605—Implantable neurostimulators for stimulating central or peripheral nerve system
- A61N1/3606—Implantable neurostimulators for stimulating central or peripheral nerve system adapted for a particular treatment
- A61N1/36103—Neuro-rehabilitation; Repair or reorganisation of neural tissue, e.g. after stroke
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
- A61N1/3605—Implantable neurostimulators for stimulating central or peripheral nerve system
- A61N1/36128—Control systems
- A61N1/36135—Control systems using physiological parameters
- A61N1/36139—Control systems using physiological parameters with automatic adjustment
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Veterinary Medicine (AREA)
- Biomedical Technology (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Biophysics (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Medical Informatics (AREA)
- Pathology (AREA)
- Physics & Mathematics (AREA)
- Physiology (AREA)
- Radiology & Medical Imaging (AREA)
- Signal Processing (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Neurosurgery (AREA)
- Neurology (AREA)
- Psychiatry (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Rehabilitation Therapy (AREA)
- Physical Education & Sports Medicine (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
The invention relates to a rehabilitation training system based on music and myoelectricity feedback simulating. The system comprises a music treatment interaction module, a host control module, a myoelectricity acquisition module and a myoelectricity feedback simulating module. The host control module broadcasts music rhythm information of a played music song by the music treatment interaction module; the myoelectricity acquisition module collects an electric signal of motion of an upper limb uninjured side muscle on a music beat in real time and transmits the electric signal to the host control module to carry out an analysis and mode identification to obtain a feature parameter and a feature value of functional electrical simulation, and a corresponding relation between an upper limb uninjured side muscle motion mode and an affected side limb end electric simulation is established; and the myoelectricity feedback simulating module carries out low-frequency electric simulation on the affected side muscle of the upper limb based on the corresponding relation. According to the invention, the participation sense and the freedom degree of the patient in rehabilitation training can be improved effectively; and the system has the broad application prospects.
Description
Technical field
The present invention relates to the technology in a kind of rehabilitation of stroke patients training field, specifically a kind of rehabilitation training system stimulated based on music and EMG feedback.
Background technology
Apoplexy is second largest common cause of death and the third-largest reason that disables in global range, and the whole world there are about more than 550 ten thousand people every year and increases the weight of year by year because of Stroke Death, its economy caused and burden on society.Apoplexy is a kind of disease with higher incidence, case fatality rate and disability rate, and apoplexy easy deflection side obstacle of limb movement.Recently as the progress of Medical Technology, the survival rate of patients with cerebral apoplexy steps up, but there are about 3/4 in the patients with cerebral apoplexy of survival and leave dysfunction in various degree.According to statistics, after morbidity in 1 week in the patient of first aid survival, have 70%-80% that hemiplegia or monoplegia occur, wherein upper limb and hand movement function obstacle have a strong impact on as worn the clothes, the activity of daily living such as feed, and then affect the life quality of patient.Therefore, improving hemiplegic limb motor function as early as possible is recover the key that minimal invasive treatment takes care of oneself.
Along with medical model is to the conversion of physiology-psychology-social pattern, Medical treatment idea, also in continuous progress, is presented as that the target of disease treatment is not only extending life, also to improve the quality of life of patient.For the limb function rehabilitation of patients with cerebral apoplexy, statistics display often presents the feature that lower limb are fast compared with upper limb, near-end is easy compared with far-end, and the patients with cerebral apoplexy of 30-60% leaves over upper limb disorder in various degree, and wherein 10% disables for severe；Thus, the upper extremity exercise functional rehabilitation of patients with cerebral apoplexy has become as concern and the study hotspot of patients with cerebral apoplexy clinical rehabilitation.And joints of hand and carpal functional rehabilitation revert to master with the fine movement of complicated neural circuit, become the strong of upper limb big joint motion function rehabilitation and supplement.In recent years, emerge multiple treatment technology and method successively, mainly include both upper extremities training, mirror image therapy, wand training method, music therapy, Mental imagery therapy, upper limb rehabilitation robot, reality-virtualizing game, constraint-induce movement therapy, functional electric stimulation, electromyographic biofeedback ther apy, transcranial magnetic stimulation and neuromuscular facilitated technique.
Music belongs to rhythmicity auditory stimulus, and motor system is very sensitive for the reaction of this auditory stimulus.Rhythmicity auditory stimulus can directly improve the motor function of cerebrovascular disease patients with hemiplegia.The research of current musical therapy focuses primarily upon passive feeling music therapy, and the research of active musical therapy is relatively fewer.In application in rehabilitation of stroke patients focuses primarily upon alleviation anxiety-depression, aphasia, cognitive disorder etc., the research in Post stroke extremity motor function rehabilitation is less, for the researches of upper extremity exercise functional rehabilitation, needs further investigation badly.
Electromyographic biofeedback ther apy is a kind of emerging method of rehabilitation, the signal of telecommunication faint when it is by myoelectricity reception equipment record spontaneous contractions muscle, feedback signal is provided by vision or Auditory Pathway, it is appreciable vision or audible signal by the in vivo functionality change transitions of not easily perception, allow patient according to these signals by instructing and train association to control self nonvoluntary action, thus playing therapeutical effect.Physiology and psychotherapy are combined by EMG biofeedback treatment, improve patient and participate in the motility for the treatment of.The yoke that the organ that traditional theory of learning thinks that vegetative nervous system is arranged can not carry out learning, can not arbitrarily controlling has been broken in the research of biofeedback, opens " visceral learning " frontier.Pass through biofeedback training, thus it is possible to vary organic environment, change the duty of the systems such as nerve, circulation, breathing, digestion, provide new tool for treating multiple illness.This technology has had some successfully to apply in patients with cerebral apoplexy limb rehabilitating.
Functional electric stimulation is applied to clinical medicine nearly half a century.Since the sixties in 20th century, after American physician LIBERSON electricity irritation peroneal nerve has successfully corrected drop foot, functional electric stimulation effect in motor function recovery is subject to the attention of rehabilitation medicine worker and is widely used.The U.S., Britain, Israel and Japan and other countries successively develop functional electric stimulation system, the patient making limbs and the paralysis of hands function can complete to stand, walks, hands grabs thing, clench fist, write, have a meal, drink water, the action such as comb one's hair, thus improve the quality of life for the treatment of crowd.But, the muscle early fatigue that common activation and the huge energy expenditure of proximity of muscle cause is limited the raising of patient outcomes by functional electric stimulation.
Summary of the invention
The present invention is directed to prior art above shortcomings, a kind of rehabilitation training system stimulated based on music and EMG feedback is proposed, the signal of telecommunication of music motion is followed by playing the strong pleural muscle meat of music Real-time Collection, it is analyzed and pattern recognition, set up the corresponding relation of the strong pleural muscle meat motor pattern of upper limb and Ipsilateral acra electricity irritation, and carry out corresponding low-frequency electrostimulating, complete a circulation, thus reaching the effect of rehabilitation training.
The present invention is achieved by the following technical solutions:
The present invention includes: musicotherapy interactive module, host computer control module, myoelectricity acquisition module and EMG feedback stimulating module, wherein: host computer control module broadcasts the music rhythm information of the music track of broadcasting by musicotherapy interactive module, the signal of telecommunication of music rhythm information action followed by the strong pleural muscle meat of myoelectricity acquisition module Real-time Collection upper limb, and be sent to host computer control module and be analyzed and pattern recognition, obtain characteristic parameter and the eigenvalue of functional electric stimulation, set up the corresponding relation of the strong pleural muscle meat motor pattern of upper limb and Ipsilateral acra electricity irritation, the Ipsilateral muscle of upper limb is carried out low-frequency electrostimulating based on this corresponding relation by EMG feedback stimulating module.
Described music rhythm information refers to: in order to guide the visualization interface or voice message that user completes required movement.
The described signal of telecommunication includes: the motion signal of telecommunication and surface electromyogram signal.
Described characteristic parameter includes but not limited to: average absolute value, signal duration, average absolute value slope, wavelength and zero passage number of times.
Described muscular movement pattern includes but not limited to: concentric contraction, centrifugation contraction, etc. dynamic contraction and isometric contraction.
Described musicotherapy interactive module includes: music libraries unit, media play unit and beat display unit, wherein: media play unit plays the music track in music libraries unit, and beat display unit shows diaphone melody purpose beat in real time.
Described myoelectricity acquisition module includes: electrode unit, protected location, amplification filter unit, D/A conversion unit and the radio communication unit being sequentially connected.
Described myoelectricity acquisition module gathers the signal of telecommunication by the strong lateral electrode that strong pleural muscle meat is built-in.
Described host computer control module includes: reception memory element, signal processing unit, pattern recognition unit and the feedback control unit being sequentially connected, wherein: receive memory element and receive and store the signal of telecommunication of myoelectricity acquisition module output, and transmit to signal processing unit；Signal processing unit controls and myoelectricity threshold decision by carrying out surface electromyogram signal processing in real time to map for emg amplitude, utilize smooth Moving Window that the signal of telecommunication is carried out periodization segmentation, extract the characteristic parameter of surface electromyogram signal in each cycle, obtain the parameter that concrete functional electrical stimulation controls, and transmit to pattern recognition unit；Pattern recognition unit extracts the eigenvalue of the motion signal of telecommunication, sets up the strong pleural muscle meat motor pattern of patient and the corresponding relation of Ipsilateral acra electricity irritation, and transmits the result to feedback control unit；Feedback control unit is by corresponding control instruction transmission to EMG feedback module.
Described radio communication unit is connected with receiving memory element.
Described EMG feedback stimulating module includes: wireless communication unit, voltage control unit, insulation blocking unit and the electrode unit being sequentially connected.
Described wireless communication unit is connected with feedback control unit.
Described EMG feedback stimulating module carries out low-frequency electrostimulating by the Ipsilateral electrode that Ipsilateral muscle is built-in.
Technique effect
Compared with prior art, the present invention passes through combining music therapy and electromyographic biofeedback ther apy, make patient participate under mental status actively and positively in the therapeutic process of disease, strengthen its enthusiasm and interactive, then reach the purpose of muscle of upper extremity dysfunction rehabilitation training；EMG feedback stimulating module combines the advantage of biofeedback and electricity irritation, not only has the effect that the cognition of biofeedback learns, promotes somesthetic sensibility to recover, and can strengthen the electricity irritation facilitation to human body.Meanwhile, the present invention meets current medical instrument to intelligent and miniaturization trend, can equally be well applied to family healthcare, has broad application prospects.
Accompanying drawing explanation
Fig. 1 is schematic diagram of the present invention；
Fig. 2 is present configuration schematic diagram；
Fig. 3 is that the present invention realizes rehabilitation training schematic diagram.
Detailed description of the invention
Below embodiments of the invention being elaborated, the present embodiment is carried out under premised on technical solution of the present invention, gives detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
Embodiment 1
As shown in Figure 1, the present embodiment includes: strong lateral electrode, Ipsilateral electrode, musicotherapy interactive module, host computer control module, myoelectricity acquisition module and EMG feedback stimulating module, wherein: host computer control module broadcasts the music rhythm information of the music track of broadcasting by musicotherapy interactive module to patient, myoelectricity acquisition module follows the signal of telecommunication of music rhythm information action by the strong pleural muscle meat of strong lateral electrode Real-time Collection patient's upper limb, and be sent to host computer control module and be analyzed and pattern recognition, obtain characteristic parameter and the eigenvalue of functional electric stimulation, set up the strong pleural muscle meat motor pattern of upper limb of patient and the corresponding relation of Ipsilateral acra electricity irritation, the Ipsilateral muscle of patient's upper limb is carried out low-frequency electrostimulating based on this corresponding relation by Ipsilateral electrode by EMG feedback stimulating module.
Described music rhythm information refers to: in order to guide patient complete required movement (as " beat time " action) and visualization interface or voice message.
The described signal of telecommunication includes: the motion signal of telecommunication and surface electromyogram signal.
The described acceleration signal that the motion signal of telecommunication is xyz three-dimensional.
The frequency separation of described surface electromyogram signal is 20～200Hz.
Described characteristic parameter includes but not limited to: average absolute value, signal duration, average absolute value slope, wavelength and zero passage number of times.
Described muscular movement pattern includes but not limited to: concentric contraction, centrifugation contraction, etc. dynamic contraction and isometric contraction.
Described strong lateral electrode and Ipsilateral electrode are built in strong pleural muscle meat and the Ipsilateral muscle of patient respectively.
Described musicotherapy interactive module includes: music libraries unit, media play unit and beat display unit, wherein: media play unit plays the music track in music libraries unit, and beat display unit shows diaphone melody purpose beat in real time.
Described music libraries unit, for setting up the music libraries selected according to the concrete physiology of patient and psychologic status, stores suitable treatment music.
Described myoelectricity acquisition module includes: electrode unit, protected location, amplification filter unit, D/A conversion unit and the radio communication unit being sequentially connected.
Described host computer control module includes: reception memory element, signal processing unit, pattern recognition unit and the feedback control unit being sequentially connected, wherein: receive memory element and receive and store the signal of telecommunication of myoelectricity acquisition module output, and transmit to signal processing unit；Signal processing unit controls and myoelectricity threshold decision by carrying out surface electromyogram signal processing in real time to map for emg amplitude, utilize smooth Moving Window that the signal of telecommunication is carried out periodization segmentation, extract the characteristic parameter of surface electromyogram signal in each cycle, obtain the parameter that concrete functional electrical stimulation controls, and transmit to pattern recognition unit；Pattern recognition unit extracts the eigenvalue of the motion signal of telecommunication, sets up the strong pleural muscle meat motor pattern of patient and the corresponding relation of Ipsilateral acra electricity irritation, and transmits the result to feedback control unit；Feedback control unit is by corresponding control instruction transmission to EMG feedback module.
Described radio communication unit is connected with receiving memory element.
Described signal processing unit includes: average reference mechanism altogether, adaptive-filtering mechanism, window events detection agency, event triggered mark mechanism and signal division mechanism, wherein: be total to average reference authorities brain electric analoging signal and by effective brain electric information output to signal division mechanism, myoelectricity digital signal after adaptive-filtering mechanism Filtering Processing carries out time sequence window labelling by window events detection agency simultaneously, event triggered mark mechanism carries out the detection of rising edge or trailing edge from the myoelectricity digital signal after labelling, and by myoelectricity validity event information output to signal division mechanism；Dimension-reduction treatment is split and carried out to effective brain electric information and myoelectricity validity event information from common average reference mechanism according to the triggered time by signal division mechanism, and exports to pattern recognition unit.
Described dimension-reduction treatment refers to: reduce the sample rate of signal and multi channel signals is spliced into one-dimensional signal.
Described adaptive-filtering mechanism includes: spectra calculation assembly, noise trap assembly and bandpass filtering assembly, wherein: spectra calculation module carries out spectra calculation after myoelectricity analogue signal is carried out analog digital conversion, and compare with built-in power spectrum threshold value, exporting calculated brain electricity and myoelectric information to noise trap assembly, noise trap assembly is filtered filtering the process exporting to window events detection agency after the denoising information obtained being filtered of making an uproar by bandpass filtering assembly.
Described window events detection agency includes: window moving assembly, root mean square calculation assembly and Threshold Detection assembly, wherein: window moving assembly receives the denoising information after bandpass filtering, and adopt rectangular window to carry out cutting process, signal after cutting is sequentially output to root mean square calculation assembly and carries out root mean square calculation, power signal after root mean square calculation is carried out threshold decision by Threshold Detection assembly, and by the root-mean-square/performance number of either window signal more than the window signal output of the preset multiple of the meansigma methods of signal root-mean-square/power in this window to event triggered mark mechanism.
Described event triggered mark mechanism includes: threshold calculations assembly, incident detection assembly and event flag assembly.
Described pattern recognition unit includes: pattern recognition component and event flag feedback component, wherein: pattern recognition component carries out pattern recognition according to the brain electric analoging signal after segmentation and obtains classification information, event flag feedback component provides human-computer interaction interface to carry out manually verification and update mark result and classification information for user, corresponding manual modification record in the model library being saved into pattern recognition component, will enable algorithm for pattern recognition constantly to store data and to improve identification accuracy.
Described pattern recognition adopts supervised learning algorithm, semi-supervised learning algorithm and unsupervised learning algorithm that event signal carries out pattern recognition and classification.
The described classification in classification information includes but not limited to: proper motion, non-autonomous motion, motion of trembling, psychological motor disorder, myasthenia type motor disorder and nerve motor disorder.
Described EMG feedback stimulating module includes: wireless communication unit, voltage control unit, insulation blocking unit and the electrode unit being sequentially connected.
Described wireless communication unit is connected with feedback control unit.
When carrying out rehabilitation training, host computer control module plays music by musicotherapy interactive module to patient, and show beat, strong pleural muscle meat patient be with musicotherapy interactive module output music rhythm information " beat time " and action carry out corresponding upper limb joint action time, the motion signal of telecommunication of the upper limb of myoelectricity acquisition module Real-time Collection patient strong side muscle arthrosis and surface electromyogram signal, transmit to host computer control module；Host computer control module extracts corresponding characteristic parameter and eigenvalue according to the motion signal of telecommunication collected and surface electromyogram signal, identifies the collapsed mode of the strong pleural muscle meat of upper limb of patient, sets up the corresponding relation of itself and Ipsilateral acra electricity irritation；The Ipsilateral muscle of patient is carried out corresponding low-frequency electrostimulating based on this corresponding relation and the collapsed mode identified by EMG feedback stimulating module, completes once to circulate.
Described signal processing unit and pattern recognition unit can be precisely carried out muscle and have an effect the Real time identification of time, and the motor pattern according to response, giving feedback in real time stimulates, and makes patient do not limited by fixed routine, there is higher degree of freedom, be conducive to efficient rehabilitation extremity motor function.
Described insulation blocking unit have employed insulating power supply and transformator, is absorbed by the leakage current on the signal path of the leakage current in circuit and power supply, it is possible to the effective safety ensureing human body.
The present embodiment chooses in January, 2015～JIUYUE in the medical first stroke 60 years old of Ruishiwo State Central Hospital and above patient 37 example, and case is made a definite diagnosis through head CT or MRI, and the course of disease 2 weeks～3 months, for side hemiplegia of limb；Without merging aphasia and cognitive dysfunction, it is proposed that the scoring of intelligent test scale AMT is be more than or equal to 7 points.
The 37 example patients that the present embodiment is chosen are randomly divided into 19 example rehabilitation group and 18 example matched groups, and two groups of patients all accept routine clinical Drug therapy in acute stage.Namely begin with after vital signs stable 48h and be trained for the exercise therapy of substance with Bobath technology, Brunnstrom technology and activity of daily living and occupational therapy carries out conventional rehabilitation.Rehabilitation group adds treats 4 weeks with rehabilitation training system described in the present embodiment.Rehabilitation group and matched group adopt skeleton symbol FUGL-MEYER to mark (FMA) before conventional rehabilitation with add-on after 4 weeks, activity of daily living (ADL) adopts Barthel index score respectively to evaluate once.
The all measurement datas of the present embodiment are with meanRepresenting, two groups of samples adopt t inspection (comparing with paired t-test before and after treatment) to carry out statistical procedures, and acquired results is as shown in Table 1 and Table 2.
FMA scoring before and after 1 liang of table group patientRelatively
| Group | N (number) | Before treatment | After treatment |
| Treatment group | 19 | 38.8±20.5 | 68.2 ± 25.6 △, △ △ △ |
| Matched group | 18 | 39.6±21.6 | 55.8±23.9△△ |
Wherein: △: P < 0.01；△ △: P < 0.05；△ △ △: P < 0.05 is compared between group after treatment.
Barthel scoring before and after 2 liang of table group patientRelatively
| Group | N (number) | Before treatment | After treatment |
| Treatment group | 19 | 41.5±18.5 | 73.9 ± 23.6 △, △ △ △ |
| Matched group | 18 | 42.6±19.6 | 61.3±21.6△△ |
Wherein: △: P < 0.01；△ △: P < 0.05；△ △ △: P < 0.05 is compared between group after treatment.
From table 1 and table 2, compared with before conventional rehabilitation, FMA and Barthel Scoring Index after treatment group 1 month (4 weeks) has bigger significant difference (P < 0.01), and FMA and the Barthel Scoring Index after matched group 1 month (4 weeks) has significant difference (P < 0.05)；Comparing between two groups, FMA and Barthel Scoring Index has significant difference (P < 0.05), and the curative effect for the treatment of group is substantially better than matched group.
It is indicated above, the comprehensive therapeutic plan that combining music is treated with EMG feedback stimulating system, more single the routine recovery training means, have bigger technical advantage to aspects such as improving and recover hemiplegic patient's motor function, raising ADL ability, improvement life quality as early as possible, suitable clinical expansion.
The present embodiment is by exporting visualizing music rhythm, patient is instructed to carry out " beat time " motion, allow patient can not only experience music, can also in the process appreciating music, the nervous system of people is affected by factors such as the melody of music, rhythm, harmony, musical sounds, play the beneficial effect of musical therapy, the psychology of patient is produced positive influences, be conducive to the signal of telecommunication of the strong pleural muscle meat of the Real-time Collection patient upper limb when patient's body and mind loosens.
Functional electric stimulation is coordinated biofeedback to carry out rehabilitation training in time by the present embodiment, it is different from the stimulating method of common low-frequency current signal, but the surface electromyogram signal of human body itself is carried out Real-time Feedback, patient carries out self regulation by learning control, so that the irritability of autonomic nerve reduces so that form positive feedback between human nerve and muscle, so that muscle contraction, strength strengthens, and not only makes patient reach the purpose of psychosomatic treatment in the process experience music；And it is actively engaged in musicotherapy process by patient, produce positive psychological effects, be beneficial to transfer patient's enthusiasm, be also beneficial to EMG biofeedback and obtain better curative effect.
The present embodiment gathers the acceleration signal of telecommunication and surface electromyogram signal simultaneously, it is possible to be obviously improved characteristic validity and the accuracy of identification of signal identification；And adopt the modeling of multi-feature extraction machine learning algorithm to identify, it is possible to significantly improve signal accuracy of identification.
Claims (8)
1. the rehabilitation training system stimulated based on music and EMG feedback, it is characterized in that, including: musicotherapy interactive module, host computer control module, myoelectricity acquisition module and the EMG feedback stimulating module of the signal of telecommunication is gathered by built-in strong lateral electrode, wherein: host computer control module broadcasts the music rhythm information of the music track of broadcasting by musicotherapy interactive module, the signal of telecommunication of music rhythm information action followed by the strong pleural muscle meat of myoelectricity acquisition module Real-time Collection upper limb, and be sent to host computer control module and be analyzed and pattern recognition, obtain characteristic parameter and the eigenvalue of functional electric stimulation, set up the corresponding relation of the strong pleural muscle meat motor pattern of upper limb and Ipsilateral acra electricity irritation, the Ipsilateral muscle of upper limb is carried out low-frequency electrostimulating based on this corresponding relation by EMG feedback stimulating module；
Described music rhythm information refers to: in order to guide the visualization interface or voice message that patient completes required movement；
Described characteristic parameter includes: average absolute value, signal duration, average absolute value slope, wavelength and zero passage number of times；
Described muscular movement pattern includes: concentric contraction, centrifugation contraction, etc. dynamic contraction and isometric contraction；
The described signal of telecommunication includes: the motion signal of telecommunication and surface electromyogram signal；
Described musicotherapy interactive module includes: music libraries unit, media play unit and beat display unit, wherein: media play unit plays the music track in music libraries unit, and beat display unit shows diaphone melody purpose beat in real time.
2. rehabilitation training system according to claim 1, is characterized in that, described myoelectricity acquisition module includes: electrode unit, protected location, amplification filter unit, D/A conversion unit and the radio communication unit being sequentially connected.
3. rehabilitation training system according to claim 1, it is characterized in that, described host computer control module includes: reception memory element, signal processing unit, pattern recognition unit and the feedback control unit being sequentially connected, wherein: receive memory element and receive and store the signal of telecommunication of myoelectricity acquisition module output, and transmit to signal processing unit；Signal processing unit controls and myoelectricity threshold decision by carrying out surface electromyogram signal processing in real time to map for emg amplitude, utilize smooth Moving Window that the signal of telecommunication is carried out periodization segmentation, extract the characteristic parameter of surface electromyogram signal in each cycle, obtain the parameter that concrete functional electrical stimulation controls, and transmit to pattern recognition unit；Pattern recognition unit extracts the eigenvalue of the motion signal of telecommunication, sets up the strong pleural muscle meat motor pattern of patient and the corresponding relation of Ipsilateral acra electricity irritation, and transmits the result to feedback control unit；Feedback control unit is by corresponding control instruction transmission to EMG feedback module.
4. rehabilitation training system according to claim 3, it is characterized in that, described signal processing unit includes: average reference mechanism altogether, adaptive-filtering mechanism, window events detection agency, event triggered mark mechanism and signal division mechanism, wherein: be total to average reference authorities brain electric analoging signal and by effective brain electric information output to signal division mechanism, myoelectricity digital signal after adaptive-filtering mechanism Filtering Processing carries out time sequence window labelling by window events detection agency simultaneously, event triggered mark mechanism carries out the detection of rising edge or trailing edge from the myoelectricity digital signal after labelling, and by myoelectricity validity event information output to signal division mechanism；Dimension-reduction treatment is split and carried out to effective brain electric information and myoelectricity validity event information from common average reference mechanism according to the triggered time by signal division mechanism, and exports to pattern recognition unit；
Described dimension-reduction treatment refers to: reduce the sample rate of signal and multi channel signals is spliced into one-dimensional signal.
5. rehabilitation training system according to claim 4, it is characterized in that, described adaptive-filtering mechanism includes: spectra calculation assembly, noise trap assembly and bandpass filtering assembly, wherein: spectra calculation module carries out spectra calculation after myoelectricity analogue signal is carried out analog digital conversion, and compare with built-in power spectrum threshold value, exporting calculated brain electricity and myoelectric information to noise trap assembly, noise trap assembly is filtered filtering the process exporting to window events detection agency after the denoising information obtained being filtered of making an uproar by bandpass filtering assembly.
6. rehabilitation training system according to claim 4, it is characterized in that, described window events detection agency includes: window moving assembly, root mean square calculation assembly and Threshold Detection assembly, wherein: window moving assembly receives the denoising information after bandpass filtering, and adopt rectangular window to carry out cutting process, signal after cutting is sequentially output to root mean square calculation assembly and carries out root mean square calculation, power signal after root mean square calculation is carried out threshold decision by Threshold Detection assembly, and by the root-mean-square/performance number of either window signal more than the window signal output of the preset multiple of the meansigma methods of signal root-mean-square/power in this window to event triggered mark mechanism.
7. rehabilitation training system according to claim 3, it is characterized in that, described pattern recognition unit includes: pattern recognition component and event flag feedback component, wherein: pattern recognition component carries out pattern recognition according to the brain electric analoging signal after segmentation and obtains classification information, event flag feedback component provides human-computer interaction interface to carry out manually verification and update mark result and classification information for user, corresponding manual modification record in the model library being saved into pattern recognition component, will enable algorithm for pattern recognition constantly to store data and to improve identification accuracy.
8. rehabilitation training system according to claim 1, is characterized in that, described EMG feedback stimulating module includes: wireless communication unit, voltage control unit, insulation blocking unit and the electrode unit being sequentially connected.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610209984.3A CN105771087A (en) | 2016-04-06 | 2016-04-06 | Rehabilitation training system based on music and myoelectricity feedback simulating |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610209984.3A CN105771087A (en) | 2016-04-06 | 2016-04-06 | Rehabilitation training system based on music and myoelectricity feedback simulating |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105771087A true CN105771087A (en) | 2016-07-20 |
Family
ID=56395758
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610209984.3A Pending CN105771087A (en) | 2016-04-06 | 2016-04-06 | Rehabilitation training system based on music and myoelectricity feedback simulating |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105771087A (en) |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106730348A (en) * | 2017-02-26 | 2017-05-31 | 曹亮明 | The smart machine and its control method of a kind of thermoelectricity acousto-optic therapeutic alliance |
| CN107589831A (en) * | 2017-07-19 | 2018-01-16 | 华南理工大学 | A kind of Virtual force field interactive system and method stimulated based on myoelectricity |
| CN107638629A (en) * | 2017-09-29 | 2018-01-30 | 北京联合大学 | A kind of double auxiliary hand function rehabilitation training systems of double feedbacks |
| WO2018023235A1 (en) * | 2016-07-31 | 2018-02-08 | 杨洁 | Method for music and user interaction and music player |
| CN107862302A (en) * | 2017-11-29 | 2018-03-30 | 合肥赑歌数据科技有限公司 | A kind of human motion detecting system and method based on semi-supervised learning |
| CN108089468A (en) * | 2018-01-11 | 2018-05-29 | 尚健静 | A kind of medical examination equipment control sequential visualized generation method |
| CN108814597A (en) * | 2018-04-16 | 2018-11-16 | 龚映清 | A kind of rehabilitation training evaluating method interacted based on motion information with myoelectricity and system |
| CN109077726A (en) * | 2018-10-29 | 2018-12-25 | 博睿康科技（常州）股份有限公司 | A kind of checking with EMG method device and myoelectricity recognition methods |
| CN109192278A (en) * | 2018-08-28 | 2019-01-11 | 齐辉 | Interactive approach and system based on virtual reality |
| CN109771216A (en) * | 2019-01-25 | 2019-05-21 | 王晶 | A kind of patients with cerebral apoplexy rehabilitation fes signal accurate positioning method |
| CN109864740A (en) * | 2018-12-25 | 2019-06-11 | 北京津发科技股份有限公司 | A kind of the surface electromyogram signal acquisition sensor and equipment of motion state |
| US10448888B2 (en) | 2016-04-14 | 2019-10-22 | MedRhythms, Inc. | Systems and methods for neurologic rehabilitation |
| CN110354387A (en) * | 2019-08-15 | 2019-10-22 | 上海理工大学 | The intelligent electro photoluminescence hand trainer and method of more triggering modes |
| CN110694172A (en) * | 2019-10-14 | 2020-01-17 | 上海交通大学 | Intelligent upper limb rehabilitation training system based on functional electrical stimulation |
| CN111938991A (en) * | 2020-07-21 | 2020-11-17 | 燕山大学 | Hand rehabilitation training device and training method in double active control modes |
| CN114984451A (en) * | 2022-06-02 | 2022-09-02 | 天津赋力博智能科技有限公司 | Rehabilitation training method and system for cooperatively controlling upper limb movement function by two arms |
| CN115363604A (en) * | 2022-10-19 | 2022-11-22 | 山东海天智能工程有限公司 | Electrode discharge automatic regulating system based on electroencephalogram signals, medium and electronic equipment |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0938216A (en) * | 1995-08-01 | 1997-02-10 | Nec Corp | Electric stimulating device |
| CN101658712A (en) * | 2008-08-29 | 2010-03-03 | 复旦大学附属华山医院 | Electric stimulation therapeutic apparatus with signal prompt |
| CN103212156A (en) * | 2013-04-03 | 2013-07-24 | 重庆绿色智能技术研究院 | Hemiplegic patient self-recovery meter based on body mirror image theory |
| CN104107134A (en) * | 2013-12-10 | 2014-10-22 | 中山大学 | Myoelectricity feedback based upper limb training method and system |
| CN105148404A (en) * | 2015-09-16 | 2015-12-16 | 燕铁斌 | Electrical stimulation training system and training method based on health-side limb electromyographic signal trigger |
| CN105361880A (en) * | 2015-11-30 | 2016-03-02 | 上海乃欣电子科技有限公司 | Muscle movement event recognition system and method |
-
2016
- 2016-04-06 CN CN201610209984.3A patent/CN105771087A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0938216A (en) * | 1995-08-01 | 1997-02-10 | Nec Corp | Electric stimulating device |
| CN101658712A (en) * | 2008-08-29 | 2010-03-03 | 复旦大学附属华山医院 | Electric stimulation therapeutic apparatus with signal prompt |
| CN103212156A (en) * | 2013-04-03 | 2013-07-24 | 重庆绿色智能技术研究院 | Hemiplegic patient self-recovery meter based on body mirror image theory |
| CN104107134A (en) * | 2013-12-10 | 2014-10-22 | 中山大学 | Myoelectricity feedback based upper limb training method and system |
| CN105148404A (en) * | 2015-09-16 | 2015-12-16 | 燕铁斌 | Electrical stimulation training system and training method based on health-side limb electromyographic signal trigger |
| CN105361880A (en) * | 2015-11-30 | 2016-03-02 | 上海乃欣电子科技有限公司 | Muscle movement event recognition system and method |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10448888B2 (en) | 2016-04-14 | 2019-10-22 | MedRhythms, Inc. | Systems and methods for neurologic rehabilitation |
| US11779274B2 (en) | 2016-04-14 | 2023-10-10 | MedRhythms, Inc. | Systems and methods for neurologic rehabilitation |
| WO2018023235A1 (en) * | 2016-07-31 | 2018-02-08 | 杨洁 | Method for music and user interaction and music player |
| CN106730348A (en) * | 2017-02-26 | 2017-05-31 | 曹亮明 | The smart machine and its control method of a kind of thermoelectricity acousto-optic therapeutic alliance |
| CN107589831A (en) * | 2017-07-19 | 2018-01-16 | 华南理工大学 | A kind of Virtual force field interactive system and method stimulated based on myoelectricity |
| CN107638629A (en) * | 2017-09-29 | 2018-01-30 | 北京联合大学 | A kind of double auxiliary hand function rehabilitation training systems of double feedbacks |
| CN107862302A (en) * | 2017-11-29 | 2018-03-30 | 合肥赑歌数据科技有限公司 | A kind of human motion detecting system and method based on semi-supervised learning |
| CN108089468A (en) * | 2018-01-11 | 2018-05-29 | 尚健静 | A kind of medical examination equipment control sequential visualized generation method |
| CN108814597A (en) * | 2018-04-16 | 2018-11-16 | 龚映清 | A kind of rehabilitation training evaluating method interacted based on motion information with myoelectricity and system |
| CN109192278A (en) * | 2018-08-28 | 2019-01-11 | 齐辉 | Interactive approach and system based on virtual reality |
| CN109077726A (en) * | 2018-10-29 | 2018-12-25 | 博睿康科技（常州）股份有限公司 | A kind of checking with EMG method device and myoelectricity recognition methods |
| CN109864740A (en) * | 2018-12-25 | 2019-06-11 | 北京津发科技股份有限公司 | A kind of the surface electromyogram signal acquisition sensor and equipment of motion state |
| CN109771216B (en) * | 2019-01-25 | 2021-05-14 | 深圳睿瀚医疗科技有限公司 | Accurate positioning method for rehabilitation FES (feed forward system) signal of stroke patient |
| CN109771216A (en) * | 2019-01-25 | 2019-05-21 | 王晶 | A kind of patients with cerebral apoplexy rehabilitation fes signal accurate positioning method |
| CN110354387A (en) * | 2019-08-15 | 2019-10-22 | 上海理工大学 | The intelligent electro photoluminescence hand trainer and method of more triggering modes |
| CN110694172A (en) * | 2019-10-14 | 2020-01-17 | 上海交通大学 | Intelligent upper limb rehabilitation training system based on functional electrical stimulation |
| CN110694172B (en) * | 2019-10-14 | 2022-10-04 | 上海交通大学 | Intelligent upper limb rehabilitation training system based on functional electrical stimulation |
| CN111938991A (en) * | 2020-07-21 | 2020-11-17 | 燕山大学 | Hand rehabilitation training device and training method in double active control modes |
| CN114984451A (en) * | 2022-06-02 | 2022-09-02 | 天津赋力博智能科技有限公司 | Rehabilitation training method and system for cooperatively controlling upper limb movement function by two arms |
| CN115363604A (en) * | 2022-10-19 | 2022-11-22 | 山东海天智能工程有限公司 | Electrode discharge automatic regulating system based on electroencephalogram signals, medium and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105771087A (en) | Rehabilitation training system based on music and myoelectricity feedback simulating | |
| CN107315478B (en) | A kind of Mental imagery upper limb intelligent rehabilitation robot system and its training method | |
| CN109925582B (en) | Dual-mode brain-computer interactive motor nerve feedback training device and method | |
| CN104000586B (en) | Patients with cerebral apoplexy rehabilitation training system and method based on brain myoelectricity and virtual scene | |
| Rak et al. | Brain-computer interface as measurement and control system the review paper | |
| CN102886102B (en) | Mirror movement neuromodulation system | |
| CN104978035B (en) | Brain machine interface system and its implementation based on body-sensing electric stimulus inducing P300 | |
| CN107928980A (en) | A kind of autonomous rehabilitation training system of the hand of hemiplegic patient and training method | |
| CN106377252A (en) | Biologic information feedback system based on virtual reality | |
| CN101391129B (en) | Brain-machine interface intelligentized upper-limb recovery training device based on P300 signal and signal processing method | |
| CN105054927A (en) | Biological quantitative assessment method for active participation degree in lower limb rehabilitation system | |
| CN104825159A (en) | Electrocerebral co-frequency detection method, electrocerebral co-frequency stimulation method and device | |
| CN111110982A (en) | Hand rehabilitation training method based on motor imagery | |
| CN101947356A (en) | Injured brain function rehabilitation device based on brain-computer interaction | |
| CN105920735A (en) | Physical and psychological recovery feedback training device | |
| CN100525854C (en) | Intelligent paralytic patient recovering aid system | |
| CN107562191A (en) | The online brain-machine interface method of fine Imaginary Movement based on composite character | |
| CN103301002B (en) | Based on maincenter-peripheral nervous recovery training method and the system of optics Brian Imaging | |
| CN103300853A (en) | Diagnosis and treatment system based on surface myoelectricity | |
| CN104307101A (en) | Method and device for generating simulated current for driving gastrointestinal pace-making system | |
| CN104887198A (en) | Pain quantitative analysis system and method based on human body physiological signal multi-parameter fusion | |
| McHugh et al. | Epidural spinal cord stimulation for motor recovery in spinal cord injury: A systematic review | |
| CN101927052A (en) | Drug-detoxifying apparatus based on brain wave biofeedback | |
| CN108919947A (en) | A kind of brain machine interface system realized by visual evoked potential and method | |
| CN113713333B (en) | Dynamic virtual induction method and system for lower limb rehabilitation full training process |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160720 |
|
| RJ01 | Rejection of invention patent application after publication |