[Abstract + References] Enhancing Stroke Recovery: A Sensor-Enabled Interactive Rehabilitation Glove for Improved Motor Skills and Progress Monitoring

Abstract:

A stroke survivor’s initial symptoms are restricted mobility, specifically hand mobility. The incorporation of remote interactive rehabilitation gloves with a game-based platform can be introduced to enhance rehabilitation quality and patient experience. The developed system is composed of sensors, machine learning, and a personalized feedback system to enhance diagnosis accuracy and promote motor recovery in individuals with hand injuries, stroke, or neurological conditions. The glove was tested and evaluated using recovery-focused exercises by participants categorized into two groups: healthy individuals and patients. The results illustrate patients’ finger dexterity and agility during various stages of the game and generate medical reports to monitor areas of improvement and target subjected areas requiring intervention by medical experts to ensure patients’ recovery progress.

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[Abstract] Motivating wearable device for plegic hand rehabilitation – Conference Publication

Abstract

We present an inexpensive, passive device supporting patient’s hand rehabilitation while their hand is in a plegic state. The device’s standalone capabilities allow patients to train their hand while in bed. A simple gamification scheme using flexion sensors and an accelerometer as input provides a way to remind patients to exercise and motivate them. WiFi connectivity to a cloud-based therapist interface allows monitoring of patient activity. The resulting device can support the hospital and house rehabilitation.

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[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] Volitional EMG Controlled Wearable FES System for Lower Limb Rehabilitation

Abstract

Muscle rehabilitation by functional electrical stimulation (FES) is one of the effective treatments for the patients with neuromuscular diseases. The conventional FES applications, however, have limitations that utilize predetermined or repetitive stimulation patterns with the help of experts such as physical therapists. Therefore, we propose a wearable FES system in which the stimulus intensity is dynamically controlled by the motion intention of user in this paper. The proposed FES system utilizes electromyography (EMG) and inertial measurement unit (IMU) sensors for estimating the motion intention regardless of electrical stimulation, and is designed for the lower limb rehabilitation. The overall system configurations including hardware and software are presented in this paper, and the system performance was tested by lower limb exercises, e.g., squat, heel lift, and gait.

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