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Updated: Jun 26, 2026
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A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
Published on: November 6, 2015
Towards control of dexterous hand manipulations using a silicon Pattern Generator
Alexander Russell1, Francesco Tenore, Girish Singhal
1Department of Electrical and Computer Engineering at the Johns Hopkins University, Baltimore, MD 21218, USA. arussell@jhu.edu
Summary
This study presents a low-power Pattern Generator (PG) for prosthetic hand control. The system uses neural spike patterns to enable dexterous manipulation in virtual prosthetic arms.
Area of Science:
- Biomedical Engineering
- Neuroprosthetics
- Robotics
Background:
- Developing intuitive and low-power control systems for upper-limb prostheses is crucial for restoring hand function.
- Existing control systems often face challenges with power consumption and dexterity for complex manipulation tasks.
Purpose of the Study:
- To demonstrate the efficacy of an in silico Pattern Generator (PG) as a low-power control system for rhythmic hand movements.
- To implement and test a PG system for controlling a virtual prosthetic arm, focusing on dexterous manipulation.
Main Methods:
- Neural spike patterns encoding cylindrical object rotation were implemented on a custom Very Large Scale Integration (VLSI) chip.
- The Pattern Generator (PG) control system was tested using decoded control signals to actuate a virtual prosthetic arm's fingers.
Main Results:
- The in silico Pattern Generator successfully controlled rhythmic hand movements in a virtual prosthetic arm.
- The system demonstrated the ability to decode neural signals for dexterous manipulation tasks.
Conclusions:
- The Pattern Generator offers a compact and efficient framework for prototyping and controlling dexterous hand manipulation in upper-limb prosthetics.
- This low-power control system represents a significant advancement in prosthetic technology, enhancing functional capabilities.
