Next Article in Journal
Machine Learning Weather Soft-Sensor for Advanced Control of Wastewater Treatment Plants
Next Article in Special Issue
Identification of Aquatic Organisms Using a Magneto-Optical Element
Previous Article in Journal
Fast Dynamic Vehicle Detection in Road Scenarios Based on Pose Estimation with Convex-Hull Model
Previous Article in Special Issue
Output Characteristics and Circuit Modeling of Wiegand Sensor
Open AccessArticle

Development of an Embedded Myokinetic Prosthetic Hand Controller

1
The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
2
Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(14), 3137; https://doi.org/10.3390/s19143137
Received: 29 May 2019 / Revised: 12 July 2019 / Accepted: 15 July 2019 / Published: 17 July 2019
(This article belongs to the Special Issue Integrated Magnetic Sensors)
The quest for an intuitive and physiologically appropriate human machine interface for the control of dexterous prostheses is far from being completed. In the last decade, much effort has been dedicated to explore innovative control strategies based on the electrical signals generated by the muscles during contraction. In contrast, a novel approach, dubbed myokinetic interface, derives the control signals from the localization of multiple magnetic markers (MMs) directly implanted into the residual muscles of the amputee. Building on this idea, here we present an embedded system based on 32 magnetic field sensors and a real time computation platform. We demonstrate that the platform can simultaneously localize in real-time up to five MMs in an anatomically relevant workspace. The system proved highly linear (R2 = 0.99) and precise (1% repeatability), yet exhibiting short computation times (4 ms) and limited cross talk errors (10% the mean stroke of the magnets). Compared to a previous PC implementation, the system exhibited similar precision and accuracy, while being ~75% faster. These results proved for the first time the viability of using an embedded system for magnet localization. They also suggest that, by using an adequate number of sensors, it is possible to increase the number of simultaneously tracked MMs while introducing delays that are not perceivable by the human operator. This could allow to control more degrees of freedom than those controllable with current technologies. View Full-Text
Keywords: hand prosthesis; embedded control system; magnetic sensors; passive magnetic markers; myokinetic controller hand prosthesis; embedded control system; magnetic sensors; passive magnetic markers; myokinetic controller
Show Figures

Figure 1

MDPI and ACS Style

Clemente, F.; Ianniciello, V.; Gherardini, M.; Cipriani, C. Development of an Embedded Myokinetic Prosthetic Hand Controller. Sensors 2019, 19, 3137. https://doi.org/10.3390/s19143137

AMA Style

Clemente F, Ianniciello V, Gherardini M, Cipriani C. Development of an Embedded Myokinetic Prosthetic Hand Controller. Sensors. 2019; 19(14):3137. https://doi.org/10.3390/s19143137

Chicago/Turabian Style

Clemente, Francesco; Ianniciello, Valerio; Gherardini, Marta; Cipriani, Christian. 2019. "Development of an Embedded Myokinetic Prosthetic Hand Controller" Sensors 19, no. 14: 3137. https://doi.org/10.3390/s19143137

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop