A Robot-Assisted Neuro-Rehabilitation System for Post-Stroke Patients’ Motor Skill Evaluation with ALEx Exoskeleton

Introduction: Telerehabilitation (TR) is defined as a model of home service for motor and cognitive rehabilitation, ensuring continuity of care over time. TR can replace the traditional face-to-face approach as an alternative method of delivering conventional rehabilitation and applies to situations where the patient is unable to reach rehabilitation facilities or for low-income countries where outcomes are particularly poor. For this reason, in this study, we sought to demonstrate the feasibility and utility of a well-known TR intervention on post-stroke patients living in one of the poorest indebted regions of Italy, where the delivery of rehabilitation services is inconsistent and not uniform.Materials and Methods: Nineteen patients (13 male/6 female; mean age: 61.1 ± 8.3 years) with a diagnosis of first-ever ischemic (n = 14) or hemorrhagic stroke (n = 5), who had been admitted to the intensive rehabilitation unit (IRU) of the Institute S. Anna (Crotone, Italy), were consecutively enrolled to participate in this study. After the discharge, they continued the motor treatment remotely by means of a home-rehabilitation system. The entire TR intervention was performed (online and offline) using the Virtual Reality Rehabilitation System (VRRS) (Khymeia, Italy). All patients received intensive TR five times a week for 12 consecutive weeks (60 sessions, each session lasting about 1h).Results: We found a significant motor recovery after TR protocol as measured by the Barthel Index (BI); Fugl-Meyer motor score (FM) and Motricity Index (MI) of the hemiplegic upper limbs.Conclusions: This was the first demonstration that a well-defined virtual reality TR tool promotes motor and functional recovery in post-stroke patients living in a low-income Italian region, such as Calabria, characterized by a paucity of specialist rehabilitation services.

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Design and Analysis of Cloud Upper Limb Rehabilitation System Based on Motion Tracking for Post-Stroke Patients

Applied Sciences ◽

10.3390/app9081620 ◽

2019 ◽

Vol 9 (8) ◽

pp. 1620 ◽

Cited By ~ 6

Author(s):

Bai ◽

Song ◽

Keyword(s):

Upper Limb ◽

Motion Tracking ◽

Stroke Patients ◽

Mean Velocity ◽

Upper Limb Rehabilitation ◽

Rehabilitation Training ◽

Post Stroke ◽

Reachable Workspace ◽

Rehabilitation System ◽

Limb Rehabilitation

In order to improve the convenience and practicability of home rehabilitation training for post-stroke patients, this paper presents a cloud-based upper limb rehabilitation system based on motion tracking. A 3-dimensional reachable workspace virtual game (3D-RWVG) was developed to achieve meaningful home rehabilitation training. Five movements were selected as the criteria for rehabilitation assessment. Analysis was undertaken of the upper limb performance parameters: relative surface area (RSA), mean velocity (MV), logarithm of dimensionless jerk (LJ) and logarithm of curvature (LC). A two-headed convolutional neural network (TCNN) model was established for the assessment. The experiment was carried out in the hospital. The results show that the RSA, MV, LC and LJ could reflect the upper limb motor function intuitively from the graphs. The accuracy of the TCNN models is 92.6%, 80%, 89.5%, 85.1% and 87.5%, respectively. A therapist could check patient training and assessment information through the cloud database and make a diagnosis. The system can realize home rehabilitation training and assessment without the supervision of a therapist, and has the potential to become an effective home rehabilitation system.

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Evaluating the post-stroke patients progress using an Augmented Reality Rehabilitation system

2009 IEEE International Workshop on Medical Measurements and Applications ◽

10.1109/memea.2009.5167961 ◽

2009 ◽

Cited By ~ 8

Author(s):

Atif Alamri ◽

Jongeun Cha ◽

Mohamad Eid ◽

Abdulmotaleb El Saddik

Keyword(s):

Augmented Reality ◽

Stroke Patients ◽

Post Stroke ◽

Rehabilitation System

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Motor Skill Evaluation During Robot-Assisted Surgery

Volume 5A: 41st Mechanisms and Robotics Conference ◽

10.1115/detc2017-67607 ◽

2017 ◽

Cited By ~ 2

Author(s):

Somayeh B. Shafiei ◽

Lora Cavuoto ◽

Khurshid A. Guru

Keyword(s):

Motor Skills ◽

Power Law ◽

Motor Skill ◽

Dynamic Change ◽

Robot Assisted ◽

End Effector ◽

Remote Manipulation ◽

Home Based ◽

Skill Evaluation ◽

Robot Assisted Surgery

Remote manipulation during robot-assisted surgery requires proficiency in perception, cognition, and motor skills. We aim to understand human motor control in remote manipulation of robotic surgical instrument and attempt to measure motor skills. Three features, smoothness, normalized jerk score, and two-thirds power law coefficient, estimating the motor skills of surgeons were analyzed. These features were calculated through segments, extracted from continuous end-effector trajectories during suturing, knot-tying, and needle-passing surgical tasks, performed by 8 right-handed subjects on bench-top models using da vinci surgical kit control system. Each subject repeated each task five times. Totally 1567 segments were extracted, 413, 437, and 717 segments performed by experts, intermediates, and novice subjects, respectively. Dynamic change of kinematic properties was analyzed to evaluate the relationship between considered features and motor skill level. Results show smoothness is significantly correlated with normalized jerk score and both features are significant measures of expertise levels. Also, results show the power law is violated by many end-effector trajectories and there is no relationship between obeying two-thirds power law, smoothness and jerk. We conclude trajectory is improved from non-smooth and jerky in novices to smooth in expert surgeons. This property may be used for motor skill evaluation. It is unlikely that obeying two-thirds power law be a valid property of all end-effector trajectories. However, power law coefficient may be a discriminant feature for levels of expertise. The results are also applicable in a home-based monitoring platform, to monitor motor functioning improvement of stroke patients during rehabilitation process.

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PNEUMATIC PLANAR REHABILITATION ROBOT FOR POST-STROKE PATIENTS

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237214500252 ◽

2014 ◽

Vol 26 (02) ◽

pp. 1450025 ◽

Cited By ~ 8

Author(s):

Franciso J. Badesa ◽

Ana Llinares ◽

Ricardo Morales ◽

Nicolas Garcia-Aracil ◽

Jose M. Sabater ◽

...

Keyword(s):

Cerebrovascular Accident ◽

Rehabilitation Robot ◽

Design Development ◽

Stroke Patients ◽

Robot Assisted ◽

Upper Limb Rehabilitation ◽

Post Stroke ◽

Planar Robot ◽

Limb Rehabilitation ◽

And Control

Cerebrovascular accident or stroke in aging population is the primary cause of disability and the second leading cause of death in many countries, including Spain. Arm impairment is common and the recovery is partly dependent on the intensity and frequency of rehabilitation intervention. However, physical therapy resources are often limited, so methods of supplementing traditional physiotherapy, such as robot assisted therapy, are essential. This paper describes design, development and control aspects of a planar robot driven by pneumatic swivel modules for upper-limb rehabilitation of post-stroke patients. Moreover, first experimental results with one post-stroke patient are presented to show the benefits of using the proposed system.

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METHODS AND MEANS OF PROVIDING REHABILITATION PROCEDURES THROUGH A BIOTECHNICAL SYSTEM WITH BIOLOGICAL FEEDBACK AND A FUZZY CONTROL MODULE

СИСТЕМНЫЙ АНАЛИЗ И УПРАВЛЕНИЕ В БИОМЕДИЦИНСКИХ СИСТЕМАХ ◽

10.36622/vstu.2021.20.3.010 ◽

2021 ◽

pp. 71-83

Author(s):

Андрей Андреевич Трифонов ◽

Елена Валерьевна Петрунина ◽

Александр Алексеевич Кузьмин ◽

Зейнаб Усама Протасова ◽

Людмила Петровна Лазурина

Keyword(s):

Virtual Reality ◽

Fuzzy Control ◽

Control Group ◽

Robotic Device ◽

Biological Feedback ◽

Stroke Patients ◽

Control Module ◽

Post Stroke ◽

Rehabilitation System ◽

Biotechnical System

В статье описана реабилитационная биотехническая система с виртуальной реальностью, позволяющая модулю нечеткого управления осуществлять биологическую обратную связь путем сопоставления стимулирующих сигналов виртуальной реальности, электроэнцефалографических сигналов и электромиосигналов. Предложена рекурсивная математическая модель планирования процедур реабилитации с использованием биологической обратной связи, основанная на понятии функций «обучения» и «забывания», позволяющая планировать сеансы тренинга и прогнозировать их результаты. Разработано аппаратное, алгоритмическое и программное обеспечение биотехничекой системы реабилитации постинсультных больных с модулем нечеткого управления экзоскелетом, позволяющее адаптировать программу реабилитации постинсультных больных с функциональным состоянием конкретного пациента. Сформирована экспериментальная группа для оценки эффективности БТС-тренинга постинсультных больных с паретичными нижними конечностями. Контрольная группа формировалась виртуально на основе статистического анализа ретроспективных стратифицированных результатов реабилитации постинсультных больных посредством биотехнической системы с робототехническим устройством без использования модуля нечеткого управления. Исследование показало, что можно изменить показатели клинического исхода у пациентов с подострым и хроническим течением инсульта после 12 сеансов БТС-тренинга. Биотехничесая система с нечетким управлением робототехническим устройством позволяет осуществлять индивидуальную стратегию реабилитации постинсультных больных (включая целенаправленную тренировку ходьбы) The article describes a biotechnical rehabilitation system with virtual reality, which allows the fuzzy control module to carry out biological feedback by comparing stimulating signals of virtual reality, electroencephalographic signals and electromyosignals. A recursive mathematical model for planning rehabilitation procedures using biofeedback is proposed, based on the concept of “learning” and “forgetting” functions, which allows planning training sessions and predicting their results. The hardware, algorithmic and software support of the biotechnical rehabilitation system for post-stroke patients with a fuzzy exoskeleton control module has been developed, which allows to adapt the rehabilitation program for post-stroke patients with the functional state of a particular patient. An experimental group was formed to assess the effectiveness of BPS training in post-stroke patients with paretic lower extremities. The control group was formed virtually on the basis of statistical analysis of retrospective stratified results of rehabilitation of post-stroke patients using a biotechnical system with a robotic device without using a fuzzy control module. The study showed that it is possible to change the indicators of clinical outcome in patients with subacute and chronic stroke after 12 sessions of BPS training. A biotechnical system with fuzzy control of a robotic device allows an individual strategy for the rehabilitation of post-stroke patients (including targeted walking training)

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