Presentation description

This project aims to improve and innovate upon the efficiency of stroke therapy processes for both occupational therapists and patients. Stroke is a leading cause of long-term disability, and is most commonly associated with upper limb hemiparesis, causing significant impairments to the hands ability to perceive touch and/or its motor function on side of the body. Currently, rehabilitation processes for stroke patients focus primarily on tasks involving gross motor function (e.g., grasping and moving objects), while neglecting tasks which require fine motor control and tactile sensory feedback (e.g., moving fragile objects without crushing or dropping them). We developed, the Electronic Grip Gauge (EGG), a sensor-embedded cube-shaped device, which detects applied force and make's a break sound if squeezed above a programmable break threshold. Participants transfer the EGG over a short barrier, while regulating grip force to avoid breakage. In this study, we tested a new adaptive break threshold algorithm, which detects the force at which the user is gripping the EGG during transfers and adjusts the break threshold in order to sufficiently challenge them. This adaptive break threshold algorithm provides three difficulty levels, which may be used along various stages of one's therapy process. It functions by storing all previous maximum grip forces measured during a patient's session and sets the breaking threshold within a proportion of the average. This algorithm aims for a 50-50 split between successful transfers and broken transfers. By adapting the EGG device's break threshold for each user, therapy exercises become more individualized, allowing patients to potentially achieve more efficient gains in sensorimotor function.