ReGlove: A Soft Pneumatic Glove for Activities of Daily Living Assistance via Wrist-Mounted Vision

TL;DR

ReGlove is an affordable, vision-guided assistive glove that uses a wrist-mounted camera and edge computing to enable reliable grasping and ADL assistance for individuals with upper-limb impairments.

Contribution

The paper introduces ReGlove, a low-cost, vision-based assistive glove that integrates real-time computer vision and edge computing for improved grasping assistance.

Findings

96.73% grasp classification accuracy

82.71% success on object manipulation benchmarks

Reliable performance across 27 ADL tasks

Abstract

This paper presents ReGlove, a system that converts low-cost commercial pneumatic rehabilitation gloves into vision-guided assistive orthoses. Chronic upper-limb impairment affects millions worldwide, yet existing assistive technologies remain prohibitively expensive or rely on unreliable biological signals. Our platform integrates a wrist-mounted camera with an edge-computing inference engine (Raspberry Pi 5) to enable context-aware grasping without requiring reliable muscle signals. By adapting real-time YOLO-based computer vision models, the system achieves 96.73% grasp classification accuracy with sub-40.00 millisecond end-to-end latency. Physical validation using standardized benchmarks shows 82.71% success on YCB object manipulation and reliable performance across 27 Activities of Daily Living (ADL) tasks. With a total cost under $250 and exclusively commercial components, ReGlove provides a technical foundation for accessible, vision-based upper-limb assistance that could benefit populations excluded from traditional EMG-controlled devices.