WO2021118383A1 - Method for the non-invasive stimulation of neuroplastic processes after stroke - Google Patents

Abstract

The invention relates to the field of medicine, and more particularly to a method for the non-invasive stimulation of neuroplastic processes in patients after stroke. The method includes practicing the execution of cyclical movements targeted at reaching, gripping, transferring and releasing an object. Exoskeleton actuators are controlled by electroencephalogram signals from a brain/computer interface or by electromyography signals. The arm muscles are subjected to functional electrical stimulation (FES) using pulsed signals, wherein said pulsed signals are synchronized with the movements of segments of the exoskeleton. Visual modality feedback is provided in the form of the movement of virtual objects on a computer screen. The result is a broadening of the range of feedback modalities provided in response to a patient's efforts.

Description

METHOD FOR NON-INVASIVE STIMULATION OF NEUROPLASTIC PROCESSES

AFTER STROKE

The invention relates to medicine, namely to methods of rehabilitation of the motor function of the hands of patients who have suffered a stroke.

PRIOR ART

According to the prognostic data of the WHO, the number of strokes in Europe will increase from 1,100,000 cases per year (2000) to more than 1,500,000 per year by 2025. - in connection with an increase in life expectancy and an increase in the incidence of cardiovascular diseases [1]. In the Russian Federation in 2015, 418,602 cases of stroke were registered [74]. At the same time, the most frequent consequences of stroke are movement disorders of varying severity, which are one of the main causes of disability in people of working age. According to some authors, the leading cause of loss of professional skills in 80% of these patients is movement disorders in the arm, especially in the hand [2, 3].

The results of the study by Gert Kwakkel et al. (2003) show that complete restoration of arm function 6 months after stroke was observed in only 11.6% of patients, while patients with initially mild to moderate motor deficits had a more favorable prognosis for good recovery [4].

Recent studies using transcranial magnetic stimulation [35] and diffusion tensor MRI [36, 37] have shown that voluntary extension of the fingers and wrist is significantly associated with the integrity of the corticospinal tract. These motor functions are the most important clinical predictor of recovery in the first days after stroke [38–40].

Gross paresis and plegia are considered by many authors as unfavorable prognostic factors for the motor function of the hand and serve as predictors of a longer recovery period: on the one hand, acting as a marker of severe damage to the corticospinal tract, and on the other, significantly limiting the choice of rehabilitation techniques [5-8] ...

Meanwhile, it is known that the individual variability of dynamics and volume recovery in each patient often does not allow us to confidently judge the prognosis at the early stages of post-stroke rehabilitation clinically, and the insufficient implementation of neurophysiological and imaging methods (somatosensory and motor evoked potentials, transcranial magnetic stimulation, MR tractography) into practice limits their routine use as predictive tools [five].

Thus, before the emergence and introduction into routine practice of techniques with reliable indicators of sensitivity and specificity in predicting functional outcome after stroke, it is necessary to search for new and optimize existing approaches in neurorehabilitation for all categories of patients: those with varying severity of paresis, who are in different rehabilitation periods

Today, there are a large number of technologies and methods for restoring the motor function of the hand after a stroke. A number of innovative technologies are under development. In this work, from the standpoint of evidence-based medicine, the analysis of existing approaches in neurorehabilitation aimed at restoring the motor function of the hand after a stroke is carried out, as well as the possibilities and limitations of the use of innovative technologies, including in relation to severe paresis and plegia, are considered.

In this aspect, the use of exoskeletal technologies, as well as solutions based on the use of neurointerfaces, is one of the most promising: experimental-theoretical and separate practical prerequisites have been formed in the world for the broad translation of such technologies into clinical medicine, but there are practically no medical systems available to the end user on the market. In addition, the world's evidence base on the clinical effectiveness of such technologies is insufficient.

Numerous works have shown that learning to move, in contrast to passive repeated repetition of such a movement, potentiates more stable neurophysiological phenomena in the primary motor cortex, corresponding to neuroplastic processes and leads to a more significant restoration of motor functions [9-17]. Motor techniques aimed at teaching movement are the basis of rehabilitation after a stroke: the main purpose of their application is to potentiate the processes of neuroplasticity in the brain, which is ensured by adequate repetitive and intensive influences beginning in the early stages after the development of a stroke [18,19].

Despite the large number of motor techniques used in post-stroke rehabilitation, not all of them have been sufficiently studied for confident recommendations for inclusion in the main rehabilitation protocols, and some approaches, according to recent meta-analyzes, do not have the expected effectiveness from the standpoint of evidence-based medicine [20].

On the other hand, it should be taken into account that in real clinical practice, the isolated use of one technique with the highest evidence without the use of others with limited evidence is unacceptable. Each specific case requires specialists to integrate various approaches or selective elements of approaches based on the patient's needs and depending on the rehabilitation period, the degree of paresis, manifestations of spasticity, premorbid background and other circumstances.

Based on a large number of studies, key elements have been identified that determine the effectiveness of a particular rehabilitation approach in any recovery period:

1. Active training (retraining) of movement, orientation of exercises to achieve a predetermined goal, functional significance of exercises for the patient (taking into account labor and domestic premorbid status), recommendation level A [21]. The implementation of this approach includes exercises that involve indicating a goal or achieving it, training complex complex movements using environmental objects (for example, manipulating cutlery while eating) [9, 22-24]. If necessary, as a preliminary preparation before performing a complex movement, training with simple repetitive movements (repetitive training) is used to practice isolated movements implemented by one muscle or a group of muscles, as well as elements of passive gymnastics and stretching exercises.

2 Regularity, adequate intensity of training, a gradual increase in the complexity and speed of the exercises, taking into account and reinforcing the achieved success, recommendation level A [21]. An important aspect of neurorehabilitation is the optimal dosing of motor loads: in each case, the number and duration of exercises, as well as the number of repetitions of movement within one workout, must be adequately determined. Reinforcement of achieved successes is implemented through feedback of different modality: verbal (by a physical therapist), visual (mirror, monitor screen), kinesthetic (exoskeletal device), etc.

In addition, in the process of training, an important role is played by the initial position of the patient, control and timely adequate limitation of compensatory movements by the trunk during the execution of movements by the proximal parts of the arm, as well as pathological friendly movements of the limbs and their segments, recommendation level B [28, 29].

1.1 Approaches in neurorehabilitation with proven effectiveness.

Based on the theoretical principles outlined in the previous section, various methods of physical rehabilitation have been developed, tested and investigated.

1.1.1 Therapeutic gymnastics. Restricted movement therapy.

According to systematic reviews and meta-analyzes [20], one of the most effective methods in neurorehabilitation is constraint-induced movement therapy (CIMT), which is included in the national guidelines for the management of post-stroke patients in countries such as the United States and England [21, 73]. In fact, this is one of the options for medical gymnastics, which, in addition to training targeted movements, provides for the simultaneous fixation of a healthy hand for up to 90% of the waking time on training days. To fix a healthy hand, use a special mitten, or a bandage (kerchief, sling) or splint, taking into account safety requirements and eliminating the risk of injury during such immobilization. For training purposeful movements, interaction with the everyday environment is proposed: hygiene items (toothbrush, soap, towel), tableware, accessories, clothing items, children's toys, books, magazines act as training equipment [33]. According to the general principles of teaching, the achievement of certain success should increase the complexity of the exercises and the speed of their implementation. The effectiveness of the method has been proven in achieving goals related to increasing strength, range of motion, improving the active function of the arm and quality of life in patients with preserved voluntary extension at the wrist 20 ° and in the fingers 10 ° regardless of the rehabilitation period, recommendation level A [19-21, 34].

The main limitations of the method are: the impossibility of using it with plegia, difficulties with implementation in case of gross paresis, and large labor costs on the part of specialists.

1.1.2 Occupational therapy. This is a complex of rehabilitation measures that provides training in basic skills of self-care (activity of daily living, ADL) and complex skills of self-care (instrumental activities of daily living, IADL). Basic skills include walking, hygiene (brushing teeth, showering, toilet), dressing, and eating. To the second

- cooking, various types of entertainment (for example, board and computer games), hobbies, driving a car, using the phone, computer.

In accordance with certain goals, the patient is trained in conditions as close as possible to a real household or social environment: the early stages involve learning to manipulate dishes, cutlery, technical means (telephone, bed remote control, TV) available for the immobilized in a bed or chair human; at later stages, conditions are created that repeat the setting of the kitchen, bathroom, office, car, and more complex skills are trained.

The effectiveness of this approach has a confidence level of 1 A and, according to the national recommendations of the United States, occupational therapy should begin already in the acute period of stroke, depending on the individual needs and limitations of the patient's functionality [21]. A significant limitation of the technique is the necessary condition for the preservation of voluntary movements, i.e. gross paresis and plegias in the hand translate an effective method into the category of irrelevant.

1.1.3 Strength training.

To increase muscle strength, resistance exercises are used, provided by a motor rehabilitation specialist or with the help of weights. In addition to building muscle strength itself, strength training techniques are used to reduce manifestations of spasticity and restore physiological synergies [88, 89]. When strength training is important, the correct selection of the trained muscle groups and alertness to the development or increase of spasticity. The main effect should be on muscle antagonists of spastic muscles, i.e. in a typical post-stroke position of the hand - on the abductor shoulder muscles, forearm extensors and arch supports, hand and finger extensors [49, 50]. The effectiveness of strength training has been shown in relation to an increase in the strength of the trained muscle groups (but not an improvement in self-care skills) in patients with the possibility of voluntary movement in the acute, subacute, chronic periods, including those with a high level of spasticity, when they are included in the complexes of targeted training, level of evidence A [21].

1.1.4 Mental training.

The method of mental training is based on a mental representation of a certain movement, its planning. Numerous studies have shown that movement representation is accompanied by changes in neurophysiological characteristics similar to those in the background of voluntary movements, and therefore it is generally accepted that movement representation stimulates the same plastic processes in the “target” motor zones of the brain as training for real movements [75] ... Learning to represent movement leads to a significant increase in the excitability of the motor cortex, which is manifested in an increase in evoked motor responses from target muscles during movement representation. In addition, after such training, the cortical representation of this function becomes more localized, which reflects the development of a new skill and the automatism of its implementation [76-78]. This phenomenon is a scientific rationale for the application of the approach in teaching motor skills of both healthy people, athletes, and in neurorehabilitation to restore the motor function of the hand after a stroke, including with severe paresis and plegia.

In a systematic review of the rehabilitation of patients with post-stroke arm paresis, which included data from 5 RCTs, 5 systematic reviews and meta-analyzes, the method of mental training with the paradigm of movement representation was assigned level A evidence, provided it is used as an adjuvant method for standard motor rehabilitation of central arm paresis (exercise therapy , occupational therapy, etc.), starting from the early recovery period at any degree of paresis [20, 21]. Some functionally significant movement for the patient is proposed as a movement, represented during training, for example, grabbing a glass of water, using cutlery, brushing teeth, while the intensity of the exercise is from 1 hour per week for 6 weeks [79-80] ...

The advantage of the motion representation technique is the possibility of using it both in a hospital, during therapeutic exercises, and at outpatient and home stages. A relative limitation is the patient's cognitive and speech functions: reliable contact with specialists is important for correct understanding and implementation of instructions. 1.1.5 Brain-computer interface.

Expanding the capabilities of the method of mental training due to the implementation of feedback is the use of interface-brain-computer (BCI) technology, based on the recognition of sensorimotor rhythms of the electroencephalogram (EEG) [81-86]. With the development of BCI technology, it became possible to objectify the process of representing motion in the mode

"Online", which implements the presentation of feedback of any modalities (depending on the device connected to the BCI), allows you to control the intensity of procedures, and most importantly

- opens up serious prospects for patients with severe paresis and plegia, because the method is based on direct active teaching of the patient. Such expectations of scientists are confirmed by numerous studies in recent years [90-96]. Most studies on BCI technology use the response of synchronization / desynchronization of EEG patterns, which occurs during mental movement, as a control signal for a device connected to a computer to present feedback to a patient [87]. These data are prerequisites for the use of BCIs in patients with severe post-stroke paresis or plegia, including those with extensive damage to the primary motor and somatosensory cortex, and, in addition, they justify the use of the hand exoskeleton in a cohort of such patients as kinesthetic feedback. Afferentation from the paretic hand, created by the movement of the exoskeleton, provides additional activation of the motor areas of the cerebral cortex through thalamocortical connections and contributes to an increase in the effectiveness of the approach. This hypothesis is confirmed: data from a multicenter controlled study conducted at the Scientific Center of Neurology and published in 2016 show the clinical effectiveness of an approach involving the use of a hand exoskeleton in the BCI circuit [86]. Also, in a comparative study, Ono T. et al., It was shown that for the presentation of feedback, it is preferable to use a hand exoskeleton providing kinesthetic afferentation, as opposed to one visual feedback presented from a computer screen [85].

Thus, the use of mental training using BCIs based on the recognition of sensorimotor EEG rhythms is recommended for patients in the early and late recovery periods with paresis of any severity, the level of persuasiveness of recommendation B (level reliability of evidence - 2b) [81-86].

1.1.6 Low-frequency neuromuscular electrical stimulation (NMES).

The method of electrical stimulation is used to potentiate muscle contraction in passive or active modes, applying electrodes to the area of the motor point of the muscle and supplying an electric current with certain characteristics. The passive mode involves the contraction of a muscle / muscle group without the implementation of purposeful movement, in contrast to functional electrical stimulation (FES), the purpose of which is to bring muscles into a contracted state during a motor act to increase its effectiveness, for example, during targeted exercises. The start of the FES, depending on the specific device and settings, is performed by pressing the trigger button by a specialist or patient, or it is triggered by a signal that is set as a trigger. This signal can be recorded electromyographic activity of the patient's limb muscles, signals from acceleration / angular velocity sensors of an exoskeleton device, or signals from a BCI classifier [97-100]. According to the clinical recommendations of the Union of Rehabilitologists of Russia for the restoration of motor functions of the hand after a stroke, NMES of the flexors and extensors of the wrist and fingers is proposed as an adjuvant method for use in patients with a stroke duration of up to 6 months. Strength of recommendation B, reliability of evidence - 2a.

Summarizing the above data, it should be emphasized that methods with active motor paradigms based on learning to move are most effective for paresis in the hand of only mild, moderate or severe severity, i.e. in cases where the patient's own movements are preserved by 75-25% of normal and we are talking about the desire to increase strength, range of motion, improve dexterity, fine motor skills. In the case of severe paresis (a sharp limitation of voluntary movement - 10% of normal), it is possible to use neuromyostimulation triggered by a myographic signal (limited evidence base according to the method), robotic therapy (limited evidence base according to the method) and the use of mental training. Plegia narrows the range of proven methods to one thing - mental training with movement representation. Robotic therapy for plegia in the classical view will only be formally applied in an assistive mode, thereby transforming into passive mechanotherapy, because active patient participation (learning to move) during plegia is impossible if a BCI is not used for this. Thus, compliance with all the principles of effective neurorehabilitation at this stage of technology development is possible only for patients with mild to severe paresis, while gross paresis and plegia of the hand sharply limit the possibilities of using active rehabilitation programs.

Summing up, it is important to note that the modification of existing or the development of new approaches (devices) in post-stroke rehabilitation should be carried out with the obligatory consideration of the factors identified in this section that determine both the effectiveness and limitations of the techniques.

The effectiveness of methods using an exoskeleton for the hand.

A wide range of robotic and mechanotherapy devices is currently used for complex hardware-based hand rehabilitation. However, according to the data of systematic reviews and meta-analyzes, there has not yet been an unambiguous statement about the effectiveness of apparatus rehabilitation for the hand, which results in the absence of a generally recognized and effective strategy for its use.

Earlier studies have shown that the use of robots for training the arm as a whole in stroke patients significantly improves the performance of the test movement (motor performance), but at the same time does not improve the functional capabilities of the arm when performing daily self-service functions (that is, there is no motor learning). - motor learning), which, apparently, is due to the fact that most of the existing robots for the arm can be programmed to perform only a simple stereotyped movement (pronation / supination, flexion / extension, mainly in the shoulder and elbow, very rarely - in brushes) [102, 103].

A 2016 meta-analysis showed that there are no advantages of using robotic devices compared to classical methods [20], which, however, may be due to the high variability of the protocols for carrying out the works included in the study.

Analysis of publications devoted to the study of rehabilitation robotic systems designed to train movements in the proximal parts of the arm (shoulder and elbow joints) in patients with mild to severe paresis (except for plegia) shows the effectiveness of their use in any rehabilitation period, provided they are added to the basic methods. physical rehabilitation in order to increase muscle strength and reduce paresis. Strength of recommendation A (level of evidence - 1a) [9, 103].

Robotic systems for restoring the function of the distal parts of the hand (hand and fingers) have become widespread and introduced into rehabilitation relatively recently, most often in routine practice such robotic systems as

“Manovo Power” and “Amadeo”, however, due to the short observation period, there is a lack of clinical studies to confirm their effectiveness, and the level of recommendations can be attributed to category C [9, 20]. 1.2 Robotic and mechanotherapy devices.

The human hand is a manipulator, the main tasks of which are reaching, grasping and manipulating the target. There are six types of gripping: hook, interdigital, planar, plucked, cylindrical, ball. Robotic and mechanotherapy devices created and developed for post-stroke neurorehabilitation are intended mainly for the restoration of reach (training of the proximal regions) and grasping (training of various types of grip).

There is currently no single classification that takes into account all the characteristics of the created devices.

Depending on the severity of movement disorders, the use of apparatus rehabilitation pursues different goals (see Table 1).

Table 1 - Application of apparatus hand rehabilitation depending on the severity of paresis.

* by Medical research council (MRC).

Rehabilitation devices can be roughly divided into two main categories: robotic and mechanotherapy. Robotic devices are devices equipped with motors to provide the necessary movement or assistance, having anthropomorphism (similarity to a living organism or its part), as well as having interactivity, i.e. the ability to change the stereotype of their work depending on environmental conditions, based on the indicators of built-in sensors. Mechanotherapy simulators are simulators that have motors to provide programmed movement, they can also be equipped with sensors to implement biofeedback.

Provision of purposeful motor learning requires from the applied robotic and mechanotherapeutic devices the maximum correspondence to the anatomical and biomechanical features of the hand, in this connection, the devices of the exoskeletal structure are the most preferable for the complex rehabilitation of hand movements. It has been shown that exoskeletal robotic systems, due to the greater number of degrees of freedom, have an impact on the restoration of skills in everyday activity and complex movements, which is the main goal of rehabilitation [17].

Equally important is an adequate way to control the device, which should involve the use of familiar modes of action for a person, for example, turning on the drives by a signal from acceleration sensors (with mild to severe paresis), a myographic signal (with gross paresis), a control signal from the brain interface - computer (with plegia). Forcible movement of arm segments regardless of the patient's intention often brings discomfort and, obviously, reduces the effectiveness of rehabilitation.

Differing in the principles of device control and the implementation of the exercises / movements performed, robotic and mechanotherapy complexes provide the following capabilities:

• training of passive movement: the simulator moves the patient's hand, the patient's own movements are absent (passive mechanotherapy);

• training of active movement: the patient performs exercises with an exoskeleton fixed on the arm, manipulating virtual (game) objects on the monitor screen, the simulator does not assist;

• training of active movement: the simulator assists in case of an attempt to move with its insufficient volume or irrational trajectory;

• training of active movement with resistance: the simulator forces you to overcome force during the exercise.

The main advantages of robotic therapy as part of modern rehabilitation devices are highlighted:

• the problem of active training of patients with severe paresis is solved due to unloading the weight of the paretic arm and the robot's own drives, with gross paresis - due to the use of electromyogram as a trigger, with plegia - when using BCI;

• afferentation from the paretic limb is provided during prolonged, purposeful and intense training using the simulator;

• an adequate feedback of various modalities (visual, kinesthetic, auditory, electrostimulation) is realized in response to the movements of the exoskeleton;

• possible early start, carrying out rehabilitation in a real environment, or as close as possible to a real one; • intensification of rehabilitation measures is provided by an increase in the intensity of training (the number of repetitions of movement), the accuracy of repeated movements;

• ensuring the rehabilitation process with high motivation and involvement in active movement training, subject to the completeness and attractiveness of technical and software solutions, the use of a virtual environment, game scenarios with an assessment of the success of tasks;

• the physical load on the personnel is facilitated, the productivity of the work of kinesiotherapists is increased;

• rehabilitation protocols are unified, while the probability of errors and inaccuracies in the training process is reduced.

The main limitations of robotic devices available on the market are:

• high price;

• limited effectiveness in gross paresis and plegia, comparable to passive mechanotherapy and remedial gymnastics, because there is no active participation of the patient, which means - his education. An exception in this case is the use of hand rehabilitation devices controlled by EMG and BCI;

• The majority of robotic devices already studied or continuing to be studied in clinical trials and used in rehabilitation centers are designed to improve movements in the proximal parts of the hand, while for the hand such devices are used significantly less, due to the complexity of the function and restoration of motor skills of the human hand.

1.3 Analysis of robotic devices on the market and in research.

The search and analysis of the characteristics of devices proposed for consideration in publications was carried out on the basis of a detailed review by Maciejasz and colleagues, which included 129 devices [111].

The current analysis included the most clinically successful devices on the market with a grip training design and active drives. In addition, the analysis of these devices was carried out in relation to the effectiveness of their use in patients in post-stroke rehabilitation, shown by studies of different quality.

The analysis excluded devices that were not available commercially. versions and have not been shown to be effective according to publications on studies that included patients with post-stroke paresis in the arm.

Robotic arm Amadeo (2011, tyromotion.com).

It consists of 5 carriages with active drives for all fingers of the hand, to which the patient's fingers are attached using magnetic clips. During training, the patient's forearm is fixed in the cradle, thereby unloading the weight of the hand (see Fig. 1).

Opportunities: active, passive, assisting training for ball gripping, finger extension, fine motor skills. Training by electromyographic signal is possible. Proprioceptive sensitivity training. Training in a virtual environment with game scenarios.

Limitations: plegia excludes the active participation of the patient. Lack of anthropomorphism (non-exoskeleton construction). Lack of training for a complex movement of the whole arm. Impossibility to manipulate real objects.

A 2012 study of 7 stroke patients showed the effectiveness of Amadeo. According to the results of clinical and instrumental (using Amadeo testing programs) assessment, all patients showed improvement in everyday skills, as well as in the volume of active movements in all fingers of the hand.

The limitations of the study were the absence of a control group, a small sample size, and the acute period of stroke in which all patients participated in the study, i.e. most likely, the improvement was observed against the background of spontaneous recovery of motor functions.

A more recent, already controlled 2013 study involving 17 patients in the subacute period of stroke also showed the effectiveness of Amadeo in improving test movements (according to the Fugl-Meyer scale) when compared with a control group in which occupational therapy was carried out. However, robotic therapy had no effect on the skills of everyday activity.

In another 2014 randomized controlled trial involving 20 patients, the effectiveness of Amadeo was shown comparable to that of therapeutic exercises, the authors recommended the extension of the simulator to widespread clinical practice. GloReha exoskeleton (2013.gloreha.com).

It is a soft exoskeleton glove of the hand with flexion-extension drives for each finger. Additionally, the manufacturers have proposed a system for unloading the weight for the hand (see Fig. 2).

Opportunities: passive, active, assistive training of spherical and cylindrical grip, extension of the fingers of the hand, training of complex interdigital grips. Use of feedback on signals from sensors on the exoskeleton, assessment of movement and dynamics of rehabilitation. Training in a virtual and real environment. Open palmar surface, which allows you to maintain tactile contact with the object during household exercises.

Limitations: gross paresis and plegia exclude the active participation of the patient.

A series of controlled studies have shown the effectiveness of the device in the complex rehabilitation of post-stroke patients in terms of increasing the range of motion, strength of cylindrical and pinched grips, improving coordination of movements and functional independence, preventing contractures, reducing pain and spasticity in muscles, and stimulating proprioception [104-106].

Hand of hope (2010, http://www.rehab-robotics.com).

Rigid exoskeleton of the hand, controlled by an electromyographic signal from electrodes placed on the skin in the projection area of the flexor and extensor muscles of the fingers (see Fig. 3).

Opportunities: passive, active, assistive training of cylindrical gripping, extension of the fingers of the hand, training of complex interdigital grips using an electromyographic signal.

It is possible to assess the movement and the effectiveness of rehabilitation. Trainings are conducted in a virtual and real environment. Open palmar surface, which allows you to maintain tactile contact with the object during household exercises.

Unloading the weight of the hand is carried out with the help of a cradle, on which the exoskeleton is fixed and which simultaneously serves as a manipulator (such as a mouse) for objects of the virtual environment, and in addition, it allows you to train not only the hand and fingers, but also elements of complex movement (reach, abduction).

Limitations: gross paresis significantly limits the capabilities of the method, the impossibility of active training during plegia The effectiveness of such training in patients with post-stroke paresis in the arm of moderate severity has been shown. There was a significant (p = 0.017) improvement in hand function in the robotic therapy group (n = 9, the median on the Wolf motor function test scale was 8.89 ± 8.67 in the hand function section; -30.38 ± 23.74 in the speed section instructions) compared with the control group (n = 10, therapeutic gymnastics, the median on the Wolf motor function test scale was 2.40 ± 4.12 in the function section; -4.22 ± 21.01 in the section of instruction execution speed) [107-110].

Application for plegia, gross paresis is not shown (they were exclusion criteria in the research of a group of developers) Based on the above data, a list of necessary attributes of the device under development has been formed (see Table 2).

Table 2 - List of technical requirements for the device being developed

"Neurostimulator".

As a result of the scientific and technical work, a rehabilitation complex was created, which has the attributes listed in the above table (see Fig. 4) and a method for the rehabilitation of patients using this complex has been developed.

The technical result achieved by the patentable solution is to expand the possibilities of rehabilitation assistance and to include patients with gross paresis and plegia in movement training, qualitatively changing the training paradigm from passive to active, while the possibility of synchronizing training using an exoskeleton with functional electrical stimulation allows not only expanding the spectrum provided modalities of feedback in response to patient efforts, but also potentiates movement hands making it more efficient.

The claimed technical result is achieved by implementing a method of non-invasive stimulation of neuroplastic processes in patients after a stroke, including the stages at which the patient's paretic hand is fixed in the exoskeleton by means of fasteners, training is performed with the performance of cyclic movements aimed at reaching, gripping, transferring and releasing the object, in this case, the drives of the exoskeleton are controlled by the residual movement of the patient's paretic hand and / or signals of electroencephalography (EEG) of the brain-computer interface (BCI) and / or signals of electromyography (EMG), functional electrical stimulation of the arm muscles is carried out by impulse (FES) signals with synchronization of impulse signals with movements of exoskeleton segments, provide feedback of the visual modality by moving virtual objects on the computer screen, kinesthetic modality by stimulating superficial and deep sensitivity by moving the fingers of the exoskeleton fetus and FES of muscles during each movement.

In a particular case of the invention, the cyclic movements include a ball, cylindrical, and pinch grip with subsequent release.

In the particular case of the invention, cyclical movements are performed over real objects.

In a particular case of the invention, cyclic movements are performed over objects modeled in a virtual environment.

In a particular case of the invention, during training, flexion / extension of 2-5 fingers and / or - flexion / extension of 1 finger and / or abduction / adduction of 1 finger by means of an exoskeleton with a maximum applied force on one finger from the side of the exoskeleton 30 N.

The patient's finger drive has an exoskeletal design, fundamentally corresponds to the implementation of such rehabilitation tasks as providing kinesthetic feedback and training movements aimed at gripping and releasing an object and allows training in a domestic environment, allowing the patient's hand to contact and manipulate objects. in the usual way. Another important, promising distinctive solution is the inclusion of a robotic devices with several control options: not only in the passive mode, but also by the myographic signal, as well as by the signal from the brain-computer interface.

DESCRIPTION OF DRAWINGS

FIG. 1 to FIG. 3 illustrates designs of exoskeletons used in the prior art.

FIG. 4 is a general view of the patient's hand exoskeleton used in the patented method.

FIG. 5 is a block diagram of the basic operation of the rehabilitation complex.

The method of non-invasive stimulation of neuroplastic processes in patients after a stroke is carried out using a rehabilitation complex, which includes a personal computer with software for synchronous data transmission, extraction of EEG and EMG indicators and signal classification to determine the control command, an encephalographic analog-to-digital converter, an electroencephalographic cap for EEG registration , FES module and EMG module with two registration channels, as well as a hand exoskeleton, controlled by electric motors and equipped with a hand weight unloading system.

Depending on the severity of movement disorders in the arm and the patient's condition, the motor rehabilitation specialist chooses a method for receiving signals about the activity of the patient's cerebral cortex associated with the motor system. EEG, or EMG, or residual movement of the paretic hand, or a combination of signals can act as such a signal. When using EEG signals with the help of a cap with electrodes and an encephalograph, the EEG is recorded, processed by the BCI classifier and transmitted as a control signal to the exoskeleton of the hand. In the case of using EMG, a myogram is used as a signal, recorded using skin electrodes connected via two channels to the myograph, and after processing using software, it is transmitted as a control signal to the exoskeleton of the hand. When the residual movement of the paretic hand is used by a system of sensors provided for by the design of the exoskeleton and the system for unloading the weight of the hand, such movement is recorded and, after processing with the help of software, is used as a control signal for the electric motors of the exoskeleton of the hand.

The exoskeleton is a system of polymer structures used to fix the patient's arm segments, unload its weight to facilitate implementation movements in conditions of paresis and setting in motion of the fingers of the hand using electric motors. The length and degrees of freedom of the exoskeleton segments are adjusted depending on the anthropometric characteristics of the patient. After receiving the control signal from the software, depending on the scenario of interaction between the signal recorders and the exoskeleton selected by the specialist in motor rehabilitation, the segments of the exoskeleton are set in motion with the patient's arm fixed. Sensors are built into the exoskeleton system, which at each time unit during training determine the relative position of the exoskeleton segments and transmit this information to the software. Magnetic encoders are used as sensors, which determine the angle of rotation of the link. Simultaneously with the movements of the exoskeleton, a change in the objects of the virtual environment with which the patient interacts, following the instructions of a specialist in motor rehabilitation, is displayed on the computer monitor. During the execution of the instructions, the motor functions of the hand are trained with the movement of the fingers with the exoskeleton in conditions of interaction with objects of the virtual and real environment, such training is accompanied by functional electrical stimulation of the muscles to potentiate the movement performed using electrical stimulation electrodes installed above the target muscles connected to the FES module. Depending on the success of the instruction, the patient receives feedback of various modalities: visual feedback using the virtual environment, game scenarios; kinesthetic feedback by stimulating superficial and deep sensitivity by moving the fingers of the hand with the exoskeleton of the hand; electrostimulation feedback using functional electrical muscle stimulation.

The rehabilitation procedure with the implementation of the invention is carried out using the following algorithm:

1. Preparatory stage.

A. Installation of a cap with EEG electrodes, calibration of the classifier using two differentiated mental states of the patient. As the first, the patient receives the instruction "Imagine the movement in the hand", as the second - "Relax, not think about the movement in the hand."

B. Connection and installation of FES electrodes, installation of electrodes of the EMG module, calibration of the FES, EMG module. B. Fixation of the patient's hand in the cradle of the weight unloading system, calibration of the initial position and range of motion of the hand in the exoskeleton.

2. Training stage.

A. Passive training using cyclic movement of the exoskeleton.

B Conducting training using BCI: the patient receives instructions on how to visualize movement in the hand, the BCI system registers EEG activity, the exoskeleton sets the fingers in motion, and FES occurs synchronously with the movements of the exoskeleton.

B. Conducting training using the EMG module: the patient is instructed to try to make a movement in the hand, the system registers EMG activity in the target muscles, the exoskeleton moves the fingers of the hand, FES occurs synchronously with the movements of the exoskeleton.

D. Carrying out training using the residual movement of the paretic hand: the patient is instructed to move in the hand, the system registers the movement in the system of unloading the weight of the hand, the exoskeleton sets the fingers in motion, and FES occurs synchronously with the movements of the exoskeleton.

During all episodes of the training stage, the patient's sensory systems interact - visual, proprioceptive, tactile with objects of the virtual and real environment, which provides feedback and reinforces the learning of movement aimed at reaching, gripping, transferring and releasing cylindrical or spherical objects.

3. Post-training stage.

A. Disconnection and removal of equipment.

It is important to emphasize that the retraining of the skills of daily activity using the "Neurostimulator" occurs depending on the individual needs and capabilities of each patient using one rehabilitation complex.

In addition to the necessary utilitarian attributes, the developed device has elements of technical design and ergonomics, a friendly software interface, which together contribute to the successful interaction of the device, the patient and the specialist in motor rehabilitation.

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Claims

CLAIM

1. A method of non-invasive stimulation of neuroplastic processes in patients after a stroke, including the stages at which the patient's paretic arm is fixed in the exoskeleton by means of fasteners, training is performed with the performance of cyclic movements aimed at reaching, gripping, transferring and releasing the object, while the drives of the exoskeleton are controlled by means of residual movement of the patient's paretic hand and / or signals of electroencephalography (EEG) of the brain-computer interface (BCI) and / or signals of electromyography (EMG), functional electrical stimulation of the arm muscles is carried out with impulse (FES) signals with synchronization of impulse signals with the movements of exoskeleton segments , present a feedback of the visual modality by moving virtual objects on the computer screen, kinesthetic modality by stimulating superficial and deep sensitivity by moving the fingers of the hand with the exoskeleton and the FES of the muscles during each movement.

2. A method according to claim 1, characterized in that the cyclic movements include a ball, cylindrical, and pinch grip followed by release.

3. The method according to claim 2, characterized in that cyclical movements are performed over real objects.

4. The method according to claim 2, characterized in that cyclic movements are performed over objects modeled in a virtual environment.

5. The method according to claim 1, characterized in that during training, flexion / extension of 2-5 fingers and / or - flexion / extension of 1 finger and / or abduction / adduction of 1 finger with a maximum applied force on one finger from the side exoskeleton 30 N.

SUBSTITUTE SHEET (RULE 26)