A lightweight EEG-controlled hand exoskeleton for assisting activities of daily living in patients with hand impairments

Abstract

This paper presents the design and implementation of a lightweight, portable hand exoskeleton controlled via electroencephalography (EEG) signals to support individuals with hand impairments in performing activities of daily living (ADLs). The device is fabricated using 3D-printed PLA material and actuated by a linear motor under Arduino Uno control. With two degrees of freedom (DoFs) per finger, the prototype achieves a total of eight DoFs across four fingers. EEG signals – specifically eye-blink detection – serve as intuitive control inputs, enabling users to initiate flexion and extension movements. In this study, EEG signals are used as event-based commands rather than continuous control inputs for system dynamics. A closed-loop position regulation mechanism using potentiometer feedback ensures stable and safe actuator displacement during operation. Experimental validation demonstrates effective assistance in hand opening and closing, with a maximum grasping force of 11.88 N and a range of motion of 67°. Compared to existing designs, the proposed exoskeleton achieves reduced weight (298 g including controller and battery) while ensuring safety, comfort, and functional grasping capability. These findings suggest that the integration of EEG-based control with feedback, combined with a cost-effective 3D-printed rigid structure, provides a promising approach for enhancing autonomy and independence in patients with impaired hand function. The presented results represent a preliminary proof-of-concept validation conducted on a single healthy subject.