CN113426081A - Sitting and standing training control method and sitting and standing training system based on brain-computer interface - Google Patents
Sitting and standing training control method and sitting and standing training system based on brain-computer interfaceDownload PDFInfo
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Abstract
Description
Technical Field
The invention relates to a sitting and standing training control method and a sitting and standing training system based on a brain-computer interface. Is suitable for the field of rehabilitation training equipment.
Background
China is the country with the most old people in the world at present, 2.54 billion old people are already aged 60 years or more in 2019, 3 billion people are expected to be broken through in 2025, and the aging problem of the population is increasingly severe. The old people are generally faced with various chronic diseases and the decline of human body functions, and the most common problems are that the sitting and standing conversion function of the lower limbs is lost and the walking and standing ability is weakened. In addition, lower limb dysfunction patients such as stroke patients, hemiplegia patients, paraplegics, spinal cord injury patients and the like also need sitting and standing training urgently, so that the problems of muscular atrophy, joint stiffness, pressure sore and the like caused by long-term bed rest are solved, and preparation is made for subsequent walking training. It can be said that the sitting-standing conversion action is the conversion action of the human body from the sitting posture to other actions, and is also the basic action for the lower limb dysfunction patient to firstly recover and train. The recovery of the conversion function of the sitting and standing has very important significance for the patients with lower limb disorder.
The regular and scientific rehabilitation auxiliary training is matched with a proper medical auxiliary instrument, so that the lower limb sitting and standing conversion function is effectively recovered and improved, the limited limb function of a patient can be effectively recovered, and the daily life capacity of the patient is improved. The traditional rehabilitation training method has the problems of boring training content, unsatisfactory training effect, difficulty in quantifying rehabilitation data, limited treatment resources and the like.
In recent years, with the development of scientific technology, methods for assisting the training of patients through computer technology and multimedia technology have appeared. Although these methods can improve the interest of rehabilitation training to some extent, they lack direct participation of the cerebral nervous system and cannot play a role in the neurological rehabilitation work, resulting in an unsatisfactory rehabilitation effect. The brain-computer interface technology can enable a person to interact with the external environment under the condition that normal transmission paths of peripheral nerves and muscles do not exist, replace partial limb functions, effectively help the damaged brain function to be remodeled, and enhance the effect of rehabilitation training. The application of brain-computer interface technology to the field of rehabilitation training is a big trend in the future.
The common sitting and standing function training products in the market mostly depend on assistance of therapists, part of the products require higher muscle strength of lower limbs or require auxiliary force of upper limbs of patients to limit the using crowd, and part of the products are easy to pull pelvis to make the patients feel uncomfortable when weight reduction training is carried out through the suspension ropes. Furthermore, most products are not capable of automated evaluation of a patient's training data. At present, no active sitting and standing training product integrating assessment, training and monitoring is available in domestic and foreign markets.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the existing problems, a sitting and standing training control method and a sitting and standing training system based on a brain-computer interface are provided.
The technical scheme adopted by the invention is as follows: a sitting-standing training control method based on a brain-computer interface is characterized by comprising the following steps:
acquiring electroencephalogram data and sitting training data when a user performs sitting training by using sitting training equipment, wherein the sitting training data comprises self motion data of the user and pressure data of the user on the sitting training equipment;
evaluating and monitoring the active motor intention of the user based on the electroencephalogram data;
providing a user with multiple feedback stimuli that can enhance the user's training initiative based on the user's active motor intent;
monitoring the gravity center shift condition and the upper limb and healthy side compensation condition of the user based on the self motion data of the user and the pressure data of the sit-up training equipment;
controlling the sitting and standing training equipment according to the compensation conditions of the upper limbs and the healthy sides to provide assistance or resistance for assisting the user to finish sitting and standing training;
estimating the recovery condition of the user according to the electroencephalogram data and the sitting training data of the user, wherein the estimation of the recovery condition comprises sitting function estimation, brain function estimation and balance function estimation, the sitting function estimation is estimated according to the motion data in the training of the user, the brain function estimation is estimated according to the change of the electroencephalogram data of the user, and the balance function is estimated according to the gravity center shift condition.
The motion data of the user comprises the muscle strength condition of the user for sitting and standing training, the time for finishing sitting and standing actions, the joint angle of the sitting and standing actions, the sitting and standing action speed and the gravity center displacement.
The pressure data of the user on the training device at the sitting station comprises the pressure of the soles of the user on the device, the pressure of the user on the seat cushion and the pressure of the user on the armrests.
The multiple feedback stimulation comprises multiple feedback controlled according to the active motor intention of the user and/or multiple stimulation for assisting the user to perform the autonomous motor imagery when the active motor intention is weaker.
The utility model provides a sit and stand training controlling means based on brain machine interface which characterized in that:
the data acquisition module is used for acquiring electroencephalogram data and sitting training data when a user performs sitting training by using the sitting training equipment, and the sitting training data comprises self motion data of the user and pressure data of the user on the sitting training equipment;
the intention evaluation module is used for evaluating and monitoring the active movement intention of the user based on the electroencephalogram data;
the feedback stimulation module is used for providing multiple feedback stimulations capable of enhancing the training initiative of the user for the user based on the active movement intention of the user;
the training monitoring module is used for monitoring the gravity center offset condition and the upper limb and healthy side compensation condition of the user based on the self motion data of the user and the pressure data of the sit-up training equipment;
the auxiliary control module is used for controlling the sitting and standing training equipment to provide assistance or resistance for assisting the user in finishing sitting and standing training according to the compensation conditions of the upper limbs and the healthy sides;
the recovery evaluation module is used for evaluating the recovery condition of the user according to the electroencephalogram data and the sitting training data of the user, the evaluation of the recovery condition comprises sitting function evaluation, brain function evaluation and balance function evaluation, wherein the sitting function evaluation is evaluated according to the motion data in the training of the user, the brain function evaluation is evaluated according to the change of the electroencephalogram data of the user, and the balance function is evaluated according to the gravity center shift condition.
The motion data of the user comprises the muscle strength condition of the user for sitting and standing training, the time for finishing sitting and standing actions, the joint angle of the sitting and standing actions, the sitting and standing action speed and the gravity center displacement.
The pressure data of the user on the training device at the sitting station comprises the pressure of the soles of the user on the device, the pressure of the user on the seat cushion and the pressure of the user on the armrests.
The multiple feedback stimulation comprises multiple feedback controlled according to the active motor intention of the user and/or multiple stimulation for assisting the user to perform the autonomous motor imagery when the active motor intention is weaker.
A storage medium having stored thereon a computer program executable by a processor, the computer program comprising: the computer program when executed implements any of the steps of the brain-computer interface based sit-stand training control method.
A sit-stand training system based on a brain-computer interface, comprising:
the electroencephalogram acquisition equipment is used for acquiring electroencephalogram data of a user;
the sitting and standing training equipment is used for assisting a user to finish sitting and standing training and collecting sitting and standing training data in the sitting and standing training process of the user;
a feedback stimulation device for providing multiple feedback stimuli to a user;
the data analysis equipment is electrically connected with the electroencephalogram acquisition equipment, the sitting and standing training equipment and the feedback stimulation equipment, and is provided with a memory and a processor, a computer program capable of being executed by the processor is stored in the memory, and when the computer program is executed, any one step of the sitting and standing training control method based on the brain-computer interface is realized.
The invention has the beneficial effects that: the invention combines the brain-computer interface technology with the sitting-standing rehabilitation training, helps the user to carry out early active rehabilitation and reduces complications. The invention emphasizes the consciousness that the user actively participates in the training, is beneficial to stimulating the remodeling of the motor nerve channel of the user and effectively promotes the brain function recombination.
The invention can intelligently adjust the resistance or the assistance of the sitting-standing training equipment to the sitting-standing training of the user according to the self condition of the patient, carries out targeted progressive training, and can effectively improve the training efficiency of the patient, enhance the muscle strength of the patient and improve the rehabilitation confidence.
According to the invention, through analyzing the electroencephalogram data and the motion data of the user, the active participation condition and the gravity center shift condition of the user can be monitored, the compensation condition of the upper limbs and the healthy side can be monitored, and the training efficiency is improved. According to the monitoring conditions, guidance and prompt including voice, pictures, vibration and the like can be given in time, so that a user can adjust actions in time, the efficiency is improved, and the falling risk is prevented.
The invention can provide motion image and sound feedback for the user on the screen of the equipment by rich and interesting interactive games and by means of the feedback representation form of the virtual or physical model, and can also provide tactile feedback for the user by vibration of the equipment to help the user to adjust the action. Through multiple feedback, not only provide immersive experience for the user, increased rehabilitation training's interest, strengthen user's motion learning efficiency moreover, promoted recovered effect.
The invention helps the user to perform the sitting and standing training, integrates the training, the evaluation and the monitoring into a whole, provides objective and quantitative evaluation for the user, has no limit on the training time and the training intensity, and reduces the dependence of the rehabilitation training on therapists.
Drawings
Fig. 1 is a flowchart of an implementation of a sitting station training control method based on a brain-computer interface according to this embodiment;
fig. 2 is a functional block diagram of a sitting training control device based on a brain-computer interface according to the present embodiment.
In the figure:1. a data acquisition module; 2. an intent evaluation module; 3. a feedback stimulation module; 4. a training monitoring module; 5. auxiliary deviceA control-assisting module; 6. and recovering the evaluation module.
Detailed Description
The embodiment is a sitting and standing training control method based on a brain-computer interface, which comprises the following specific steps:
s1, acquiring electroencephalogram data and sitting and standing training data when the user performs sitting and standing training by using the sitting and standing training equipment, wherein the sitting and standing training data comprise data of force, displacement, angle, speed, time and the like, and the sitting and standing training data comprise self motion data of the user and pressure data of the user on the sitting and standing training equipment.
The motion data of the user comprises the muscle strength condition of the user for sitting and standing training, the time for finishing sitting and standing actions, the joint angle of the sitting and standing actions, the sitting and standing action speed, the gravity center displacement and the like; the pressure data of the user on the training device at the sitting station comprises the pressure of the user's soles on the device, the pressure of the user on the seat cushion, the pressure of the user on the armrests and the like.
And S2, evaluating and monitoring the active movement intention of the user based on the electroencephalogram data, and monitoring the degree of active participation of the user in training through the active movement intention of the user.
And S3, providing multiple feedback stimuli for the user based on the active movement intention of the user, wherein the multiple feedback stimuli can enhance the training initiative of the user, and the multiple feedback stimuli comprise multiple feedbacks for controlling according to the active movement intention of the user and multiple stimuli for assisting the user to perform the autonomous motor imagery when the active movement intention of the user is weaker.
And S4, monitoring the gravity center shift condition and the upper limb and healthy side compensation condition of the user based on the motion data of the user and the pressure data of the sit-up training equipment.
In the embodiment, the gravity center movement of the user and the compensation condition of the upper limb and the healthy side can be monitored by comparing and analyzing the healthy side force exertion condition and the affected side force exertion condition of the user in the sitting and standing action process and combining the distribution of the sole pressure and the cushion pressure.
And S5, controlling the sitting and standing training equipment to provide the sitting and standing assistance or resistance for the user according to the compensation conditions of the upper limbs and the healthy sides so as to assist the user in finishing the sitting and standing training.
And S6, estimating the recovery condition of the user according to the electroencephalogram data and the sitting training data of the user, wherein the estimation of the recovery condition comprises sitting function estimation, brain function estimation and balance function estimation, the sitting function estimation is based on the motion data in the training of the user, the brain function estimation is based on the change estimation of the electroencephalogram data of the user, and the balance function estimation is based on the gravity center shift condition.
The embodiment also provides a sitting and standing training control device based on the brain-computer interface, which comprises a data acquisition module, an intention evaluation module, a feedback stimulation module, a training monitoring module, an auxiliary control module and a recovery evaluation module.
In the embodiment, the data acquisition module is used for acquiring electroencephalogram data and sitting training data when a user performs sitting training by using sitting training equipment, wherein the sitting training data comprises self-movement data of the user and pressure data of the user on the sitting training equipment; the intention evaluation module is used for evaluating and monitoring the active movement intention of the user based on the electroencephalogram data; the feedback stimulation module is used for providing multiple feedback stimulations capable of enhancing the training initiative of the user for the user based on the active movement intention of the user; the training monitoring module is used for monitoring the gravity center offset condition and the upper limb and healthy side compensation condition of the user based on the motion data of the user and the pressure data of the sit-up training equipment; the auxiliary control module is used for controlling the sitting and standing training equipment to provide assistance or resistance for assisting the user in finishing sitting and standing training according to the compensation conditions of the upper limbs and the healthy sides; the recovery evaluation module is used for evaluating the recovery condition of the user according to the electroencephalogram data and the sitting training data of the user, and the evaluation of the recovery condition comprises sitting function evaluation, brain function evaluation and balance function evaluation, wherein the sitting function evaluation is evaluated according to the motion data in the training of the user, the brain function evaluation is evaluated according to the change of the electroencephalogram data of the user, and the balance function evaluation is evaluated according to the gravity center shift condition.
The present embodiment also provides a storage medium having a computer program stored thereon, the computer program being executable by a processor, and the computer program being executed to implement the steps of the sitting training control method based on brain-computer interface of the present embodiment.
The embodiment also provides a sitting and standing training system based on the brain-computer interface, which comprises electroencephalogram acquisition equipment, sitting and standing training equipment, feedback stimulation equipment and data analysis equipment.
The brain electrical collecting device in this example is used for obtaining brain electrical information data of a user, and comprises at least one set of brain electrical collecting device which can be non-invasive, semi-invasive or invasive. The collecting electrode can be a dry electrode, a semi-dry electrode, a wet electrode, a disk electrode or the like. The acquisition channels are typically 8-lead, but may also be 4-lead, 16-lead, 64-lead, etc. The electroencephalogram signal processor is used for extracting and classifying the characteristics of the acquired electroencephalogram signals. The electroencephalogram signal feature extraction method comprises the steps of spectrum analysis, autoregressive analysis, common space mode, source reconstruction and the like. The classification algorithm of the brain electrical signals comprises linear discriminant analysis, support vector machine analysis, artificial neural network, fuzzy system and the like.
The sitting and standing training device is used for assisting a user to complete sitting and standing training and collecting sitting and standing training data in the sitting and standing training process of the user, and can also provide partial feedback (tactile feedback and the like). The sitting and standing training equipment in the embodiment is provided with a seat for a user to sit and capable of collecting data of sole pressure, seat cushion pressure and armrest pressure of the user in the sitting and standing training process, and the seat is provided with various sensors, such as a pressure sensor, a grip sensor, a displacement sensor, an optical motion capture system and the like, and is used for acquiring motion data of the user in the training process.
The feedback stimulation device in this embodiment is capable of providing multiple feedback, including one or more feedback modalities, to the user during training. The feedback means may be visual, tactile, auditory, gustatory, olfactory, etc. Further, the visual feedback may include virtual feedback such as mirror image feedback, virtual reality, animation simulation, etc., and may also include physical feedback such as a peripheral model, e.g., a racing game, a soccer robot, etc. Further, haptic feedback includes position control and haptic guidance, which can enhance the environment to generate somatosensory stimuli inducing neuroplasticity. Further, the auditory feedback may include targeted alert tones and underdeveloped encouragement, etc. to reduce the perceived and perceived workload. The multi-mode stimulation and the multi-mode feedback can enhance the exercise learning and are more beneficial to the rehabilitation.
In the embodiment, the muscle strength of the user in the process of finishing the sitting and standing exercise can be monitored, so that the muscle strength of the user in the process of finishing the sitting and standing exercise can be obtained. According to the muscle strength data, the system can evaluate the recovery condition of the user, and can also directly feed back the muscle strength condition to the user by means of a visual feedback device of the feedback stimulation equipment through animation simulation modeling.
The feedback stimulation device in this embodiment can also provide visual or auditory stimulation to the user to assist the patient in performing the voluntary motor imagery, the visual stimulation includes presenting the patient with motion images of himself or others, the auditory stimulation can be a description related to limb movement, and the presentation can be in the form of a lecture, a story, music, and the like. Furthermore, the motion image can be presented by playing the image of human motion by using a computer display device; may be simulating the movement of a user's limb by means of a computer display device and sensors; or may be a presentation of the movement of a limb using virtual reality techniques, etc. The motor intention of the user disclosed in the present embodiment may also be that the user significantly activates the brain motor center based on the mirror neuron system through a motion observation or the like. The brain electrical signals generated in this case may be motor visual evoked potentials, including transient motor visual evoked potentials and steady state motor visual evoked potentials. Further, the visual stimulus includes a visual module that presents a frequency flash. The visual modules include different shapes, brightness, colors, positions, orientations, etc. The electroencephalogram signal in this case may also be an event-related potential generated by the patient under external stimulation. Further, the visual or auditory stimuli include a sequence of visual/auditory modules presented at a large probability with a small probability of being presented. The visual stimulus module includes different shapes, brightness, colors, positions, directions, etc. The auditory stimulation module can be in the forms of frequency, loudness, tone quality, duration and the like of sound, vowels, syllables, words, question sentences, statement sentences and the like, and the presentation mode can be speech, stories, music and the like.
The data analysis device in this example is electrically connected with the electroencephalogram acquisition device, the sitting-station training device and the feedback stimulation device, and has a memory and a processor, wherein the memory stores a computer program which can be executed by the processor, and the computer program realizes the steps of the sitting-station training control method based on the brain-computer interface in this embodiment when executed.
In this embodiment, the data analysis device and the feedback stimulation device may be integrated into a computer device with a display screen, and the computer device may be a desktop computer, a notebook computer, a tablet computer, a smart phone, or the like.
In the embodiment, the electroencephalogram data of the user in the training process are analyzed, so that the movement intention of the user can be evaluated and monitored in real time. The user motor intention in the example can be generated by directly exciting the cerebral motor cortex through motor imagery, or can be generated by assisting the patient to perform autonomous motor imagery through visual or auditory stimulation provided by a feedback stimulation device.
In this embodiment, the user needs to wear the electroencephalogram acquisition device, master the use method of the system, and select a proper rehabilitation scheme on the device according to the actual rehabilitation stage of the user. The system carries out evaluation, monitoring and feedback according to the electroencephalogram signal characteristics and the training condition of the user. The system monitors the degree of active participation of the user in training by calculating the active movement intention of the user; through a plurality of virtual reality interactive games, the initiative of the training of the patient is enhanced; the gravity center monitoring and compensation monitoring are carried out by analyzing the force exertion condition of the user in the sitting and standing action process, and the prompting is carried out when the user carries out gravity center transfer training through the tactile feedback prompt on the equipment; providing multiple sensory feedback such as vision, hearing, touch and the like for a user through a display screen and equipment; and evaluating the brain function change and the change of the sitting and standing conversion capability of the user after training by analyzing the acquired electroencephalogram data and motion data.
Claims (10)
1. A sitting-standing training control method based on a brain-computer interface is characterized by comprising the following steps:
acquiring electroencephalogram data and sitting training data when a user performs sitting training by using sitting training equipment, wherein the sitting training data comprises self motion data of the user and pressure data of the user on the sitting training equipment;
evaluating and monitoring the active motor intention of the user based on the electroencephalogram data;
providing a user with multiple feedback stimuli that can enhance the user's training initiative based on the user's active motor intent;
monitoring the gravity center shift condition and the upper limb and healthy side compensation condition of the user based on the self motion data of the user and the pressure data of the sit-up training equipment;
controlling the sitting and standing training equipment according to the compensation conditions of the upper limbs and the healthy sides to provide assistance or resistance for assisting the user to finish sitting and standing training;
estimating the recovery condition of the user according to the electroencephalogram data and the sitting training data of the user, wherein the estimation of the recovery condition comprises sitting function estimation, brain function estimation and balance function estimation, the sitting function estimation is estimated according to the motion data in the training of the user, the brain function estimation is estimated according to the change of the electroencephalogram data of the user, and the balance function is estimated according to the gravity center shift condition.
2. The brain-computer interface based sitting station training control method according to claim 1, wherein: the motion data of the user comprises the muscle strength condition of the user for sitting and standing training, the time for finishing sitting and standing actions, the joint angle of the sitting and standing actions, the sitting and standing action speed and the gravity center displacement.
3. The brain-computer interface based sitting station training control method according to claim 1 or 2, wherein: the pressure data of the user on the training device at the sitting station comprises the pressure of the soles of the user on the device, the pressure of the user on the seat cushion and the pressure of the user on the armrests.
4. The brain-computer interface based sitting station training control method according to claim 1, wherein: the multiple feedback stimulation comprises multiple feedback controlled according to the active motor intention of the user and/or multiple stimulation for assisting the user to perform the autonomous motor imagery when the active motor intention is weaker.
5. The utility model provides a sit and stand training controlling means based on brain machine interface which characterized in that:
the data acquisition module is used for acquiring electroencephalogram data and sitting training data when a user performs sitting training by using the sitting training equipment, and the sitting training data comprises self motion data of the user and pressure data of the user on the sitting training equipment;
the intention evaluation module is used for evaluating and monitoring the active movement intention of the user based on the electroencephalogram data;
the feedback stimulation module is used for providing multiple feedback stimulations capable of enhancing the training initiative of the user for the user based on the active movement intention of the user;
the training monitoring module is used for monitoring the gravity center offset condition and the upper limb and healthy side compensation condition of the user based on the self motion data of the user and the pressure data of the sit-up training equipment;
the auxiliary control module is used for controlling the sitting and standing training equipment to provide assistance or resistance for assisting the user in finishing sitting and standing training according to the compensation conditions of the upper limbs and the healthy sides;
the recovery evaluation module is used for evaluating the recovery condition of the user according to the electroencephalogram data and the sitting training data of the user, the evaluation of the recovery condition comprises sitting function evaluation, brain function evaluation and balance function evaluation, wherein the sitting function evaluation is evaluated according to the motion data in the training of the user, the brain function evaluation is evaluated according to the change of the electroencephalogram data of the user, and the balance function is evaluated according to the gravity center shift condition.
6. The brain-computer interface based sitting station training control device of claim 5, wherein: the motion data of the user comprises the muscle strength condition of the user for sitting and standing training, the time for finishing sitting and standing actions, the joint angle of the sitting and standing actions, the sitting and standing action speed and the gravity center displacement.
7. A brain-computer interface based sitting station training control device according to claim 5 or 6, wherein: the pressure data of the user on the training device at the sitting station comprises the pressure of the soles of the user on the device, the pressure of the user on the seat cushion and the pressure of the user on the armrests.
8. The brain-computer interface based sitting station training control device of claim 5, wherein: the multiple feedback stimulation comprises multiple feedback controlled according to the active motor intention of the user and/or multiple stimulation for assisting the user to perform the autonomous motor imagery when the active motor intention is weaker.
9. A storage medium having stored thereon a computer program executable by a processor, the computer program comprising: the computer program is executed to realize the steps of the brain-computer interface based sitting and standing training control method of any one of claims 1 to 4.
10. A sit-stand training system based on a brain-computer interface, comprising:
the electroencephalogram acquisition equipment is used for acquiring electroencephalogram data of a user;
the sitting and standing training equipment is used for assisting a user to finish sitting and standing training and collecting sitting and standing training data in the sitting and standing training process of the user;
a feedback stimulation device for providing multiple feedback stimuli to a user;
the data analysis equipment is electrically connected with the electroencephalogram acquisition equipment, the sitting-standing training equipment and the feedback stimulation equipment, and is provided with a memory and a processor, a computer program capable of being executed by the processor is stored in the memory, and when the computer program is executed, the steps of the sitting-standing training control method based on the brain-computer interface of any one of claims 1 to 4 are realized.
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