Stroke Rehabilitation Glove

Project Engineer

● Phase 1 — Proof of Concept

  • Reverse Engineering
  • Embedded Systems
  • PCB Design
  • Microcontroller
Stroke Rehabilitation Glove
Overview

In Australia, nearly 50,000 people are affected by stroke each year, with many experiencing partial or complete loss of hand mobility. This project aims to improve the accessibility and affordability of stroke rehabilitation gloves — devices designed to reduce spasticity and support the rebuilding of neural pathways responsible for hand control.

Inspired by the commercially available Syrebo rehabilitation glove, we are developing a custom controller and rehabilitation program tailored for flexible, software-driven therapy. The project is currently in Phase 1, focused on proof-of-concept development — validating that a custom-built controller can fully replicate and extend the capabilities of the original hardware.


Technical Approach
  • Reverse engineering of the commercially available Syrebo rehabilitation glove controller
  • Mechanical modification of the glove to improve finger dexterity and range of motion
  • Design and development of a custom replacement controller
  • Integration with a microcontroller to enable programmable and adaptive rehabilitation routines

My Contributions
  • Disassembled and analysed the original Syrebo controller hardware to understand signal characteristics and control logic
  • Used laboratory equipment including oscilloscopes and multimeters to characterise actuator drive signals and support reverse engineering
  • Designed and built a custom controller, enabling full software control of the glove via a microcontroller

Gallery

Photos of the hardware build and early proof-of-concept demonstrations. Click any image to view full size.


Next Steps — Phase 2

In Phase 2, we will implement individual finger actuation to give stroke patients finer motor control over their dexterity. The pneumatic system will be upgraded with minimal power draw. We will accomplish mirror therapy and intention detection, enabling the glove to perform more unique gestures beyond what is currently available on the market.