[Abstract] Low-cost haptic glove for grasp precision improvement in Virtual Reality-Based Post-Stroke Hand Rehabilitation

Abstract:Stroke in Algeria is one of the most important causes of severe physical disability. Upper limb paralysis is also most common in stroke patients, which severely affecting their daily life. Therefore, it is important to help stroke patients to improve the quality of their life. In this article, we have proposed a novel system based on virtual reality for fine motor rehabilitation. Because the sense of touch is essential to the patient’s daily activities, we have integrated haptic feedback into our system (vibrating glove), this is to help the patient to perform rehabilitation exercises. The proposed vibrating glove is equipped with five small and flat vibrating motor discs (one on each finger); these motors are controlled by ESP8266 board. This system has been tested on two patients with stroke. The preliminary results show that the system can help patients recover fine motor skills.

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[Abstract] Robotic Hand Exoskeleton With Tactile Force Feedback For Post-Stroke Spasticity Rehabilitation

Abstract

Spasticity is a common complication that occurs in post-stroke patients that refers to stiff muscles. Post-Stroke patients with spasticity can cause a lack of ability to grasp object. Repetition of specific-task practice, such as grasping and lifting a cup, can help the recovery of spasticity. After various physiotherapy techniques to treat spasticity on the hand, it is necessary to evaluate the strength of the patient’s hands during grasping. Rehabilitation technology, including exoskeleton, are being developed to enhance hand function in patients with spasticity. Although there are many task-spesific practice method with exoskeleton, to get a measurement of force during grasp interactions is still challenging. The purpose of this study is to develop a hand exoskeleton with feedback from tactile sensor to measure contact force distribution at patient’s rmgertips during grasp movement, then external power from the exoskeleton helps subjects maintain grip strength. The external power is determined based on the measured contact force distribution value using the tactile sensor and it is value compared with the threshold obtained based on experiment. The normal hand grip threshold measurement obtained for lifting a cup was 2.254 N. During rehabilitation, subjects were hold and lift a cup 10 times. It was found the timing of fatigue during experiments on subjects 1, 2, 4 and 5 respectively occurred in the 9th, 10th, 8th and 9th tests. Furthermore, exoskeleton can maintain the strength of the grasp around the threshold by giving external power stimulus if the contact force measurement were detected below the threshold. As a result, in the whole test before fatigue appeared, the total average value of the grasp was above the threshold.

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