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Related Experiment Video

Updated: Jan 22, 2026

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

Development of an Embedded Myokinetic Prosthetic Hand Controller.

Francesco Clemente^1,2, Valerio Ianniciello^1,2, Marta Gherardini^1,2

¹The Biorobotics Institute, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.

Sensors (Basel, Switzerland)

|July 20, 2019

Summary

A novel myokinetic interface uses magnetic markers (MMs) implanted in residual muscles for intuitive prosthetic control. This embedded system offers real-time, precise localization, advancing dexterous prosthesis interface technology.

Keywords:

embedded control system hand prosthesis magnetic sensors myokinetic controller passive magnetic markers

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Last Updated: Jan 22, 2026

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Published on: May 20, 2020

Area of Science:

Biomedical Engineering
Human-Machine Interface Design
Prosthetics and Orthotics

Background:

Current prosthetic control relies heavily on muscle electrical signals, facing limitations in intuitiveness and physiological appropriateness.
Developing advanced human-machine interfaces for dexterous prostheses remains a significant challenge.
Novel control strategies are needed to enhance prosthetic functionality and user experience.

Purpose of the Study:

To introduce and validate a novel embedded system for a myokinetic interface.
To demonstrate real-time localization of multiple magnetic markers (MMs) for prosthetic control.
To assess the system's performance in terms of speed, precision, and accuracy.

Main Methods:

Development of an embedded system featuring 32 magnetic field sensors and a real-time computation platform.
Real-time localization of up to five magnetic markers (MMs) within an anatomically relevant workspace.
Performance evaluation including linearity, repeatability, computation time, and cross-talk error analysis.

Main Results:

The embedded system achieved simultaneous, real-time localization of five MMs with high linearity (R² = 0.99) and precision (1% repeatability).
The system demonstrated short computation times (4 ms) and limited cross-talk errors (10%).
The embedded system was approximately 75% faster than previous PC-based implementations, with comparable accuracy and precision.

Conclusions:

This study validates the feasibility of using an embedded system for magnetic marker localization in prosthetic control.
The myokinetic interface shows potential for controlling more degrees of freedom than current technologies.
Further development with more sensors could increase tracked MMs without perceivable delays, enhancing prosthetic dexterity.