CN114146309B - Mirror neuron rehabilitation training system and method based on dynamic adjustment - Google Patents
Mirror neuron rehabilitation training system and method based on dynamic adjustment Download PDFInfo
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- 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
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- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
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- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
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- 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
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
- A61M2021/0005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
- A61M2021/0016—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus by the smell sense
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- A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
- A61M2021/0005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
- A61M2021/0027—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus by the hearing sense
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- A—HUMAN NECESSITIES
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- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
- A61M2021/0005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
- A61M2021/0044—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus by the sight sense
- A61M2021/005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus by the sight sense images, e.g. video
Abstract
The invention discloses a mirror image neuron rehabilitation training system based on dynamic adjustment, which is used for capturing the micro-motion of the limbs of a patient, amplifying the captured micro-motion, comparing the amplified micro-motion with the historical micro-motion under the same stimulation, and inputting the result to a trend prediction module; the trend prediction module evaluates rehabilitation degree data of a patient after receiving a comparison result of the current micro-action and the historical micro-action, and sends the rehabilitation degree data of the patient to the strategy adjusting module; the basic information and the rehabilitation expectation information of the patient are received in advance, and then the current rehabilitation training mode and the strength are adjusted according to the received rehabilitation degree data of the patient, so that the problems that the rehabilitation speeds of different patients are different, the effects of some patients are better, and some patients are unsatisfactory due to different stimulation sources which are different from the stimulation sources of different users and the excitation strength generated by the stimulation sources are different are solved.
Description
Technical Field
The invention relates to the technical field of medical rehabilitation equipment, in particular to a mirror neuron rehabilitation training system and method based on dynamic adjustment.
Background
Mirror Neuron (MNS) refers to a neuron with a special mapping function that can directly map actions, emotions, intentions, and the like of other people in the brain of an observer, and is widely present in a plurality of brain regions and participates in activities such as understanding, simulation, sympathy, social cognition, and the like of the actions. As a hotspot of the research on the cognitive neuroscience at home and abroad, researchers find that the mirror neurons play an important role in action recognition and simulation. As a special class of neurons, mirror neurons produce excitement not only when an individual performs a particular action, but may also produce similar excitement when the individual observes that other similar classes perform the same or similar actions.
The central nervous system lesion often causes the motor dysfunction of the human body, most commonly paralysis of the hemilateral limbs, greatly influences the work and the life of the patient, and also brings heavy burden to families and society. And the training by the mirror image neurons has a more positive effect.
At present, although some studies show that the training based on the mirror neurons has a certain effect on the rehabilitation of patients with dysfunction, and many reports of MNS treatment are reported clinically, in the aspect of hardware, equipment for performing rehabilitation training based on the mirror neurons is simple and crude, programmed automatic rehabilitation training equipment is not disclosed, and better treatment effect cannot be obtained by using the existing equipment.
Meanwhile, aiming at different rehabilitation patients, because different stimulation sources have different stimulation to different users, and further the generated excitation strength is different, the rehabilitation speeds of different patients are different, the effect of some patients is better, and some patients are not satisfactory, furthermore, the regulation and control strategy is usually carried out through the completion degree in the prior art, and the uncontrollable performance is more subjective.
For example, chinese patents: CN202010887847.1 discloses a self-adaptive training method for rehabilitation exercise, which is to calculate the current task completion value of a trainer in the current rehabilitation training mode; and calling a preset mode switching condition to adaptively adjust the difficulty level of the rehabilitation training mode based on the current task completion value and the functional state of the trainer in the current rehabilitation training mode. However, it requires the complete fitting of the patient, and is not well judged for the fitting condition of the patient.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention discloses a mirror image neuron rehabilitation training system based on dynamic adjustment, which comprises: the device comprises a nerve stimulation module, an electroencephalogram sensing module, a strategy generation module, a strategy adjustment module, a limb identification module and a trend prediction module; the nerve stimulation module comprises visual trigger, auditory trigger and olfactory trigger, stimulates a rehabilitation patient by generating different sensory triggers, and corresponds all the stimulation through the electroencephalogram sensing module, namely corresponds different stimulation and electroencephalogram fluctuation intensity; the electroencephalogram sensing module senses the electroencephalogram condition of the rehabilitation patient, performs noise elimination on the electroencephalogram signal, obtains a preprocessed signal after filtering blink and low-frequency noise interference, and classifies stimulation trigger sources corresponding to the preprocessed signal according to the amplitude of electroencephalogram fluctuation to obtain stimulation sources with different levels of stimulated nerve strength; the strategy generation module is used for pre-storing a standard rehabilitation cloud training template, wherein the regulation strategy based on different parameters and different types of multi-sensory stimulation sources are combined in advance to generate a plurality of rehabilitation trainings in different grades; the limb identification module captures the micro-motion of the limb of the patient, amplifies the captured micro-motion, compares the amplified micro-motion with the historical micro-motion under the same stimulation, and inputs the result to the trend prediction module; the trend prediction module evaluates rehabilitation degree data of a patient after receiving a comparison result of the current micro-action and the historical micro-action, and sends the rehabilitation degree data of the patient to the strategy adjustment module; and the strategy adjusting module receives the basic information and the rehabilitation expectation information of the patient in advance and adjusts the current rehabilitation training mode and intensity according to the received rehabilitation degree data of the patient.
Still further, the basic information of the patient further includes: the age, sex, degree of acroparalysis of the patient; the rehabilitation desire information further comprises: the extent to which the patient desires recovery and the time to which the patient desires rehabilitation training.
Further, comparing the captured micromotion after amplification with the historical micromotion under the same stimulus further comprises: and if the result is in oscillation, evaluating the rehabilitation confidence of the patient, judging whether the expectation of the patient is changed or not, and inputting the possibly changed expectation to the strategy adjusting module again to dynamically adjust the current rehabilitation training mode and intensity.
Further, after assessing the patient's rehabilitation confidence, if the patient's expectations do not change over a period of time, training completion is introduced for additional strategy adjustments.
Still further, the training completeness further comprises a completion rate of the patient when performing rehabilitation training of the current strategy.
The invention further discloses a mirror image neuron rehabilitation training method based on dynamic adjustment, which is applied to the system and comprises the following steps:
step 1, performing visual trigger on a patient through video playing, performing auditory trigger on the patient through audio playing, performing olfactory trigger on the patient through generating different tastes, stimulating a rehabilitation patient through generating different sensory triggers, and corresponding different stimulation and electroencephalogram fluctuation intensity;
step 2, sensing the electroencephalogram condition of the rehabilitation patient, performing noise elimination on the electroencephalogram signal, obtaining a preprocessed signal after filtering out blink and low-frequency noise interference, and grading the stimulation trigger sources corresponding to the preprocessed signal according to the amplitude of electroencephalogram fluctuation to obtain stimulation sources of different levels of stimulated nerve intensity;
step 3, pre-storing a reference rehabilitation cloud training template, and combining a regulation strategy based on different parameters and different types of multi-sensory stimulation sources in advance to generate a plurality of rehabilitation trainings with different grades; capturing the micro-motion of the limb of the patient, amplifying the captured micro-motion, and comparing the amplified micro-motion with the historical micro-motion under the same stimulation to obtain a comparison result;
and 4, after receiving the comparison result of the current micro-motion and the historical micro-motion, evaluating the rehabilitation degree data of the patient, sending the rehabilitation degree data of the patient to a strategy adjusting module, receiving the basic information and the rehabilitation expectation information of the patient in advance, and adjusting the current rehabilitation training mode and intensity according to the received rehabilitation degree data of the patient.
Preferably, the basic information of the patient further includes: the age, sex, degree of acroparalysis of the patient; the rehabilitation desire information further includes: the extent to which the patient desires recovery and the time to which the patient desires to undergo rehabilitation training.
Preferably, comparing the captured micromotion amplified to the historical micromotion under the same stimulus further comprises: and if the result is in oscillation, evaluating the rehabilitation confidence of the patient, judging whether the expectation of the patient is changed or not, and inputting the possibly changed expectation to the strategy adjusting module again to dynamically adjust the current rehabilitation training mode and intensity.
Preferably, after assessing the patient's rehabilitation confidence, if the patient's expectations do not change over a certain time, then training completion is introduced for auxiliary strategy adjustments.
Preferably, the training completion further comprises a completion rate of the patient in performing rehabilitation training of the current strategy.
Compared with the prior art, the invention has the following beneficial effects: the problem of to different recovered patients, because different stimulation source is different to the stimulation of different users, and then the excitation intensity that produces is also different, lead to different patients ' recovered speed also inconsistent, some patient's effect is better, some patients are then not satisfactory, and furthermore, usually carry out the regulation and control strategy through the degree of completion among the prior art, wherein have the problem of more subjective uncontrollable nature, carry out the fine motion to patient's recovered action and judge, the recovered information of patient is analyzed simultaneously, with the execution strategy of this dynamic adjustment recovered plan and system. Different from the change of the rehabilitation strategy depending on the completion degree of the rehabilitation project in the prior art, the method adjusts the strategy by an objective comparison method under the condition of eliminating the subjective emotion problem of the patient as much as possible, and analyzes the emotion state of the patient to change the strategy of the rehabilitation training to stimulate the patient.
Drawings
The invention will be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. In the drawings, like reference numerals designate corresponding parts throughout the different views.
FIG. 1 is a block diagram of a mirror neuron rehabilitation training system based on dynamic modulation of the present invention;
fig. 2 is a flowchart of a mirror neuron rehabilitation training method based on dynamic adjustment according to an embodiment of the present invention.
Detailed Description
Example one
As shown in fig. 1, the present invention discloses a mirror neuron rehabilitation training system based on dynamic adjustment, the system includes: the device comprises a nerve stimulation module, an electroencephalogram sensing module, a strategy generation module, a strategy adjustment module, a limb identification module and a trend prediction module; the nerve stimulation module comprises visual trigger, auditory trigger and olfactory trigger, stimulates a rehabilitation patient by generating different sensory triggers, and corresponds all the stimulation through the electroencephalogram sensing module, namely corresponds different stimulation and the strength of electroencephalogram fluctuation; the brain sensing module senses the brain condition of the rehabilitation patient, performs noise elimination on the brain signals, obtains preprocessed signals after filtering out blink and low-frequency noise interference, and classifies stimulation trigger sources corresponding to the preprocessed signals according to the amplitude of brain wave fluctuation to obtain stimulation sources of different levels of stimulated nerve intensity; the strategy generation module is used for pre-storing a reference rehabilitation cloud training template, wherein regulation and control strategies based on different parameters and different types of multi-sensory stimulation sources are combined in advance to generate a plurality of rehabilitation trainings in different grades; the limb recognition module captures the micro-motion of the limb of the patient, amplifies the captured micro-motion, compares the amplified micro-motion with historical micro-motion under the same stimulation, and inputs the result to the trend prediction module; the trend prediction module evaluates rehabilitation degree data of a patient after receiving a comparison result of the current micro-action and the historical micro-action, and sends the rehabilitation degree data of the patient to the strategy adjustment module; and the strategy adjusting module receives the basic information and the rehabilitation expectation information of the patient in advance and adjusts the current rehabilitation training mode and intensity according to the received rehabilitation degree data of the patient.
Still further, the basic information of the patient further includes: the age, sex, degree of acroparalysis of the patient; the rehabilitation desire information further comprises: the extent to which the patient desires recovery and the time to which the patient desires rehabilitation training.
Further, comparing the captured micromotion after amplification with the historical micromotion under the same stimulus further comprises: and if the result is in oscillation, evaluating the rehabilitation confidence of the patient, judging whether the expectation of the patient is changed or not, and inputting the possibly changed expectation to the strategy adjusting module again to dynamically adjust the current rehabilitation training mode and intensity.
Further, after assessing the patient's rehabilitation confidence, if the patient's expectations do not change over a period of time, training completion is introduced for additional strategy adjustments.
Still further, the training completeness further comprises a completion rate of the patient when performing rehabilitation training of the current strategy.
Example two
As shown in fig. 2, this embodiment explains the inventive concept of the present invention from the perspective of an implementation method, and further discloses a mirror neuron rehabilitation training method based on dynamic adjustment, which is applied to the above system, and the method includes:
step 1, performing visual trigger on a patient through video playing, performing auditory trigger on the patient through audio playing, performing olfactory trigger on the patient through generating different tastes, stimulating a rehabilitation patient through generating different sensory triggers, and corresponding different stimulation and electroencephalogram fluctuation intensity;
step 2, sensing the electroencephalogram condition of the rehabilitation patient, performing noise elimination processing on the electroencephalogram signal, obtaining a preprocessed signal after filtering out blink and low-frequency noise interference, and grading stimulation trigger sources corresponding to the preprocessed signal according to the amplitude of electroencephalogram fluctuation to obtain stimulation sources with different levels of stimulated nerve strength;
step 3, pre-storing a reference rehabilitation cloud training template, and combining a regulation strategy based on different parameters and different types of multi-sensory stimulation sources in advance to generate a plurality of rehabilitation trainings with different grades; capturing the micro-motion of the limb of the patient, amplifying the captured micro-motion, and comparing the amplified micro-motion with the historical micro-motion under the same stimulation to obtain a comparison result;
and 4, after receiving the comparison result of the current micro-motion and the historical micro-motion, evaluating the rehabilitation degree data of the patient, sending the rehabilitation degree data of the patient to a strategy adjusting module, receiving the basic information and the rehabilitation expectation information of the patient in advance, and adjusting the current rehabilitation training mode and intensity according to the received rehabilitation degree data of the patient.
Preferably, the basic information of the patient further includes: the age, sex, degree of acroparalysis of the patient; the rehabilitation desire information further comprises: the extent to which the patient desires recovery and the time to which the patient desires rehabilitation training.
Preferably, comparing the captured micromotion amplified to the historical micromotion under the same stimulus further comprises: and if the result is in oscillation, evaluating the rehabilitation confidence of the patient, judging whether the expectation of the patient is changed or not, and inputting the possibly changed expectation to the strategy adjusting module again to dynamically adjust the current rehabilitation training mode and intensity.
Preferably, after assessing the patient's rehabilitation confidence, if the patient's expectations do not change over a period of time, a training completeness is introduced for assisting in the strategy adjustment.
In this embodiment, the captured micro motion is amplified and then compared with the historical micro motion under the same stimulus, and the rehabilitation status of the patient is determined by adopting a plurality of objective determination methods, for example, by video recording, the collected motion amplitude is amplified in equal proportion, and is compared with the historical micro motion after being amplified by the same multiple, and for example, in a vibration feedback manner, a plurality of vibration sensors are arranged at the end of the limb of the patient, and after receiving the vibration, the vibration sensors compare the amplified vibration signal to perform the determination.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus comprising the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Although the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications can be made without departing from the scope of the invention. It is therefore intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention. The above examples are to be construed as merely illustrative and not limitative of the remainder of the disclosure. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
Claims (3)
1. A mirror neuron rehabilitation training system based on dynamic adjustment, the system comprising: the device comprises a nerve stimulation module, an electroencephalogram sensing module, a strategy generation module, a strategy adjustment module, a limb identification module and a trend prediction module; the nerve stimulation module comprises visual trigger, auditory trigger and olfactory trigger, stimulates a rehabilitation patient by generating different sensory triggers, and corresponds all the stimulation through the electroencephalogram sensing module, namely corresponds different stimulation and the strength of electroencephalogram fluctuation; the electroencephalogram sensing module senses the electroencephalogram condition of the rehabilitation patient, performs noise elimination on the electroencephalogram signal, obtains a preprocessed signal after filtering blink and low-frequency noise interference, and classifies stimulation trigger sources corresponding to the preprocessed signal according to the amplitude of electroencephalogram fluctuation to obtain stimulation sources with different levels of stimulated nerve strength; the strategy generation module is used for pre-storing a standard rehabilitation cloud training template, wherein the regulation strategy based on different parameters and different types of multi-sensory stimulation sources are combined in advance to generate a plurality of rehabilitation trainings in different grades; the limb recognition module captures the micro-motion of the limb of the patient, amplifies the captured micro-motion, compares the amplified micro-motion with historical micro-motion under the same stimulation, and inputs the result to the trend prediction module; the trend prediction module evaluates rehabilitation degree data of a patient after receiving a comparison result of the current micro-action and the historical micro-action, and sends the rehabilitation degree data of the patient to the strategy adjustment module; the strategy adjusting module receives the basic information and the rehabilitation expectation information of the patient in advance and adjusts the current rehabilitation training mode and intensity according to the received rehabilitation degree data of the patient;
comparing the captured micromotion amplified with the historical micromotion under the same stimulus further comprises: if the result is in oscillation, evaluating the rehabilitation confidence of the patient, judging whether the expectation of the patient is changed or not, and inputting the changed expectation to the strategy adjusting module again to dynamically adjust the current rehabilitation training mode and intensity;
after assessing the patient's rehabilitation confidence, if the patient's expectations do not change over a period of time, then a training completion is introduced for auxiliary strategy adjustments.
2. The dynamic adjustment-based mirror neuron rehabilitation training system of claim 1, wherein the basic information of the patient further comprises: the age, sex, degree of acroparalysis of the patient; the rehabilitation desire information further comprises: the extent to which the patient desires recovery and the time to which the patient desires rehabilitation training.
3. The neuron-based rehabilitation training system for mirror image neurons based on dynamic adjustment of claim 1, wherein the training completion further comprises a completion rate of the patient in performing rehabilitation training of the current strategy.
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| CN108245763A (en) * | 2017-12-28 | 2018-07-06 | 中国科学院宁波材料技术与工程研究所 | Brain-machine interaction rehabilitation training system and method |
| CN110993056A (en) * | 2019-10-29 | 2020-04-10 | 浙江迈联医疗科技有限公司 | Hybrid active rehabilitation method and device based on mirror image neurons and brain-computer interface |
| CN112017750A (en) * | 2020-08-28 | 2020-12-01 | 中国科学院宁波材料技术与工程研究所慈溪生物医学工程研究所 | Self-adaptive training method and device for rehabilitation exercise, medium and rehabilitation robot |
| CN112244774A (en) * | 2020-10-19 | 2021-01-22 | 西安臻泰智能科技有限公司 | Brain-computer interface rehabilitation training system and method |
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