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Updated: Mar 27, 2026
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A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
Published on: November 6, 2015
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A bio-inspired force control for cyclic manipulation of prosthetic hands
Summary
This study introduces a bio-inspired control system for prosthetic hands, enabling them to learn complex manipulation tasks. The novel approach demonstrates successful application in both simulation and on a real prosthetic hand.
Area of Science:
- Biomedical Engineering
- Robotics
- Neuroscience
Background:
- The human hand's dexterity is a benchmark for prosthetic development.
- Controlling polyarticulated prosthetic hands to mimic natural manipulation is a significant research challenge.
Purpose of the Study:
- To propose a bio-inspired learning architecture for prosthetic hands.
- To enable prosthetic hands to learn cyclic manipulation capabilities using parallel force/position control.
Main Methods:
- Developed a bio-inspired learning architecture.
- Implemented parallel force/position control.
- Trained and tested the control system in simulation and on the IH2 commercial biomechatronic hand.
Main Results:
- The proposed architecture demonstrated the ability to learn cyclic manipulation.
- Parallel force/position control was successfully tested in simulation.
- Preliminary tests on the IH2 hand showed promising results.
Conclusions:
- The bio-inspired neural control is applicable to real biomechatronic hands.
- This approach advances the capabilities of prosthetic hand control.
- The system shows potential for replicating natural hand manipulation.
