Related Experiment Video
Updated: Jul 17, 2026
06:58
A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
Published on: November 6, 2015
9.5K
A quantitative comparison between the mHand Adapt passive adjustable hand prosthesis and its predecessor, the Delft
Spyros L L Krinis1,2, Alix Chadwell1, Laurence Kenney1
1Centre for Health Sciences Research, University of Salford, Salford, United Kingdom.
Plos One
|March 21, 2024
Summary
The mHand prosthesis offers improved functionality and task completion compared to the Delft Self-Grasping Hand (SGH), requiring less use of the user's other hand. Some learning challenges exist, but overall performance is enhanced.
Area of Science:
- Prosthetics and Orthotics
- Rehabilitation Engineering
- Human-Computer Interaction
Background:
- The Delft Self-Grasping Hand (SGH) is a passive adjustable prosthesis requiring contralateral hand use for grasp adjustment.
- The mHand Adapt, a commercialized version, features a modified release mechanism and hand shape.
- This study is the first to quantitatively compare the SGH and mHand Adapt.
Purpose of the Study:
- To compare the functionality and contralateral hand involvement of the mHand Adapt against the SGH.
- To assess the performance of two passive adjustable hand prostheses using quantitative scoring.
Main Methods:
- 10 participants performed the Southampton Hand Assessment Procedure (SHAP) using the mHand.
- Functionality and contralateral hand interaction were recorded.
- Data was compared to previous SGH trial data.
Main Results:
- The mHand demonstrated higher functionality scores and reduced contralateral hand interaction time, particularly during release.
- A broader range of tasks were completable with the mHand compared to the SGH.
- Geometric changes improved manipulation of smaller objects.
Conclusions:
- The mHand offers enhanced functionality and task versatility with reduced contralateral hand dependency.
- Design modifications improve object manipulation and release efficiency.
- Potential trade-offs include a steeper learning curve for users.
