We recently introduced the concept of a new human-machine interface (the myokinetic control interface) to control hand prostheses. The interface tracks muscle contractions via permanent magnets implanted in the muscles and magnetic field sensors hosted in the prosthetic socket. Previously we showed the feasibility of localizing several magnets in non-realistic workspaces. Here, aided by a 3D CAD model of the forearm, we computed the localization accuracy simulated for three different below-elbow amputation levels, following general guidelines identified in early work. To this aim we first identified the number of magnets that could fit and be tracked in a proximal (T1), middle (T2) and distal (T3) representative amputation, starting from 18, 20 and 23 eligible muscles, respectively. Then we ran a localization algorithm to estimate the poses of the magnets based on the sensor readings. A sensor selection strategy (from an initial grid of 840 sensors) was also implemented to optimize the computational cost of the localization process. Results showed that the localizer was able to accurately track up to 11 (T1), 13 (T2) and 19 (T3) magnetic markers (MMs) with an array of 154, 205 and 260 sensors, respectively. Localization errors lower than 7% the trajectory travelled by the magnets during muscle contraction were always achieved. This work not only answers the question: "how many magnets could be implanted in a forearm and successfully tracked with a the myokinetic control approach?", but also provides interesting insights for a wide range of bioengineering applications exploiting magnetic tracking.
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http://dx.doi.org/10.1109/TNSRE.2020.3024960 | DOI Listing |
Sci Robot
September 2024
BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
The loss of a hand disrupts the sophisticated neural pathways between the brain and the hand, severely affecting the level of independence of the patient and the ability to carry out daily work and social activities. Recent years have witnessed a rapid evolution of surgical techniques and technologies aimed at restoring dexterous motor functions akin to those of the human hand through bionic solutions, mainly relying on probing of electrical signals from the residual nerves and muscles. Here, we report the clinical implementation of an interface aimed at achieving this goal by exploiting muscle deformation, sensed through passive magnetic implants: the myokinetic interface.
View Article and Find Full Text PDFIEEE Trans Biomed Eng
March 2024
Objective: The search for a physiologically appropriate interface for the control of dexterous hand prostheses is an ongoing challenge in bioengineering. In this context, we proposed an interface, named myokinetic control interface, based on the localization of magnets implanted in the residual limb muscles, to monitor their contractions and send appropriate commands to the artificial hand. As part of such concept, this interface requires a transcutaneous magnet localizer that can be integrated in a self-contained limb prosthesis, a feature yet to be realized within the current state of the art.
View Article and Find Full Text PDFObjective: We recently proposed a new concept of human-machine interface to control hand prostheses which we dubbed the myokinetic control interface. Such interface detects muscle displacement during contraction by localizing permanent magnets implanted in the residual muscles. So far, we evaluated the feasibility of implanting one magnet per muscle and monitoring its displacement relative to its initial position.
View Article and Find Full Text PDFJ Neural Eng
April 2022
The BioRobotics Institute, Scuola Superiore Sant'Anna, 56121 Pisa, Italy.
. Proprioception is the sense of one's position, orientation, and movement in space, and it is of fundamental importance for motor control. When proprioception is impaired or absent, motor execution becomes error-prone, leading to poorly coordinated movements.
View Article and Find Full Text PDFIEEE Trans Biomed Circuits Syst
April 2022
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