Year: 2021
Type: conference-paper
Abstract: In previous work, we developed an exoskeleton (HandSOME II) that allows movement at 15 hand degrees of freedom (DOF) and is intended for take-home use. An activity tracking device was developed in order to track index finger movement with a pair of magnetometers and magnet. The goal was to detect grip attempts by the individual. Machine learning was utilized to estimate angles for metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints at the index finger. Testing was performed with healthy control and individuals with stroke.Clinical Relevance- This device and method of data collection during daily activities might be useful for stroke rehabilitation and compliance with home-based therapy programs.
Institution: Catholic University of America
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4200433522
