WO2021118383A1 - Procédé de stimulation non invasive de processus neuroplastiques après un avc - Google Patents

Procédé de stimulation non invasive de processus neuroplastiques après un avc Download PDF

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Publication number
WO2021118383A1
WO2021118383A1 PCT/RU2019/000916 RU2019000916W WO2021118383A1 WO 2021118383 A1 WO2021118383 A1 WO 2021118383A1 RU 2019000916 W RU2019000916 W RU 2019000916W WO 2021118383 A1 WO2021118383 A1 WO 2021118383A1
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WIPO (PCT)
Prior art keywords
stroke
training
exoskeleton
hand
movement
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PCT/RU2019/000916
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English (en)
Russian (ru)
Inventor
Роман Харисович ЛЮКМАНОВ
Антон Сергеевич КЛОЧКОВ
Анастасия Евгеньевна ХИЖНИКОВА
Наталья Александровна СУПОНЕВА
Михаил Александрович ПИРАДОВ
Original Assignee
Федеральное государственное бюджетное научное учреждение "НАУЧНЫЙ ЦЕНТР НЕВРОЛОГИИ"
Общество, С Ограниченной Ответственностью "Нейроботикс"
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Application filed by Федеральное государственное бюджетное научное учреждение "НАУЧНЫЙ ЦЕНТР НЕВРОЛОГИИ", Общество, С Ограниченной Ответственностью "Нейроботикс" filed Critical Федеральное государственное бюджетное научное учреждение "НАУЧНЫЙ ЦЕНТР НЕВРОЛОГИИ"
Priority to PCT/RU2019/000916 priority Critical patent/WO2021118383A1/fr
Publication of WO2021118383A1 publication Critical patent/WO2021118383A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
    • A61H1/02—Stretching or bending or torsioning apparatus for exercising
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation

Definitions

  • the invention relates to medicine, namely to methods of rehabilitation of the motor function of the hands of patients who have suffered a stroke.
  • 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.
  • CIMT constraint-induced movement therapy
  • 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.
  • 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.
  • 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 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.
  • 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.
  • BCI interface-brain-computer
  • EEG electroencephalogram
  • 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].
  • NMES Low-frequency neuromuscular electrical stimulation
  • 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.
  • FES functional electrical stimulation
  • 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].
  • 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.
  • 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.
  • active patient participation learning to move
  • plegia is impossible if a BCI is not used for this.
  • 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.
  • Robotic systems for restoring the function of the distal parts of the hand have become widespread and introduced into rehabilitation relatively recently, most often in routine practice such robotic systems as
  • the human hand is a manipulator, the main tasks of which are reaching, grasping and manipulating the target.
  • 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).
  • 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.
  • 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.
  • robotic and mechanotherapy complexes provide the following capabilities:
  • 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.
  • Robotic arm Amadeo (2011, tyromotion.com).
  • 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.
  • 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).
  • a manipulator such as a mouse
  • 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.
  • EEG electroencephalography
  • BCI brain-computer interface
  • EMG electromyography
  • the cyclic movements include a ball, cylindrical, and pinch grip with subsequent release.
  • cyclical movements are performed over real objects.
  • cyclic movements are performed over objects modeled in a virtual environment.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the segments of the exoskeleton 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.
  • a change in the objects of the virtual environment with which the patient interacts is displayed on the computer monitor.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Butefisch CM Davis BC, Wise SP, et al. Mechanisms of use-dependent plasticity in the human motor cortex. Proc Natl Acad Sci USA 2000; 97: 3661-3665;
  • Winstein C Wing AM, Whitall J. Motor control and learning principles for rehabilitation of upper limb movements after brain injury. In: Boiler F, Grafman J, Robertson IH, editors.

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  • Health & Medical Sciences (AREA)
  • Veterinary Medicine (AREA)
  • Public Health (AREA)
  • General Health & Medical Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Rehabilitation Therapy (AREA)
  • Physical Education & Sports Medicine (AREA)
  • Pain & Pain Management (AREA)
  • Epidemiology (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Rehabilitation Tools (AREA)

Abstract

L'invention se rapporte au domaine de la médecine, notamment à des procédés de stimulation non invasive de processus neuroplastiques chez des patients après un AVC. Ce procédé comprend un entraînement afin d'effectuer des mouvements cycliques pour atteindre, saisir, déplacer et relâcher un objet. Des actionneurs d'exosquelette sont commandés par des signaux d'une interface électro-encéphalographique (cerveau-ordinateur) ou des signaux d'électromyographie. On effectue une électro-stimulation fonctionnelle (ESF) des muscles de la main avec des signaux par impulsions en synchronisant les signaux par impulsions avec les segments en mouvement de l'exosquelette. On présente une liaison retour de modalité visuelle en déplaçant des objets virtuels sur un écran d'ordinateur. Il est ainsi possible d'élargir l'éventail des modalités présentées de liaison retour en réponse aux efforts du patient.
PCT/RU2019/000916 2019-12-09 2019-12-09 Procédé de stimulation non invasive de processus neuroplastiques après un avc WO2021118383A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113576831A (zh) * 2021-07-27 2021-11-02 南京麦澜德医疗科技股份有限公司 一种辅助手功能作业训练康复系统及操作方法

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090221928A1 (en) * 2004-08-25 2009-09-03 Motorika Limited Motor training with brain plasticity
US20130261514A1 (en) * 2012-03-30 2013-10-03 The Hong Kong Polytechnic University Wearable power assistive device for hand rehabilitation
US20140277582A1 (en) * 2013-03-15 2014-09-18 Neurolutions, Inc. Brain-controlled body movement assistance devices and methods

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090221928A1 (en) * 2004-08-25 2009-09-03 Motorika Limited Motor training with brain plasticity
US20130261514A1 (en) * 2012-03-30 2013-10-03 The Hong Kong Polytechnic University Wearable power assistive device for hand rehabilitation
US20140277582A1 (en) * 2013-03-15 2014-09-18 Neurolutions, Inc. Brain-controlled body movement assistance devices and methods

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113576831A (zh) * 2021-07-27 2021-11-02 南京麦澜德医疗科技股份有限公司 一种辅助手功能作业训练康复系统及操作方法

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