Effects of Sensor Resolution and Localization Rate on the Performance of a Myokinetic Control Interface

Abstract

Magnetic tracking systems have been widely investigated in biomedical engineering due to the transparency of the human body to static magnetic fields. We recently proposed a novel human-machine interface for prosthetic application, namely the myokinetic interface. This controls multi-articulated prostheses by tracking magnets implanted in the residual muscles of individuals with amputation. Previous studies in this area focused solely on the choice and tuning of the localization algorithm. Here, we addressed the role of the intrinsic properties of the sensors, by analysing their effects on the tracking accuracy and on the computation time of the localization algorithm, through experimentally-verified computer simulations. We observed that the tracking accuracy is primarily affected by the localization rate, which is directly related to the sampling frequency of the sensors, and less significantly affected by the sensor resolution. The computation time, instead, proved positively correlated to the number of MMs, and negatively correlated with the localization rate. Our results may contribute to the development of novel human-machine interfaces for prosthetic limbs and could be extended to a broad range of applications involving magnetic tracking.

Exact and Computationally Robust Solutions for Cylindrical Magnets Systems with Programmable Magnetization

“…As for the latter, they could be used, for example, for accurately detecting magnets relatively close to sensors in robotic prostheses, thus possibly extending ref. [ 25 ]. Moreover, exactly knowing the gradient is profitable for both computations and system design/control.…”

“…[ 11 ] As a matter of fact, permanent magnets, and specifically cylindrical magnets in most cases, were used to actuate micro/millirobots and magnetoresponsive agents in air and (biological) fluids/tissues [ 12 , 13 , 14 , 15 , 16 ] (by also enabling complementary localization [ 17 , 18 ] ), catheters, [ 19 ] endoscopes, [ 20 ] capsules/pills, [ 21 , 22 ] building blocks for stable assemblies [ 23 ] and flexible pumps prospectively functional to soft robotic hearts. [ 24 ] Moreover, magnetic localization of cylindrical magnets was investigated, for example, for controlling robotic prostheses [ 25 ] and in wearable sensing systems for rehabilitation. [ 26 ] Furthermore, (rigid) permanent magnets with simple geometries, such as cylinders and cuboids, were used as external actuation sources for a variety of (deformable) soft magnetoresponsive systems, such as soft magnetic robots [ 27 , 28 ] and active substrates for mechanobiology investigations, [ 29 ] by also enabling shape‐memory and stiffness modulation in composite elastomers.…”

To What Extent Implanting Single vs Pairs of Magnets Per Muscle Affect the Localization Accuracy of the Myokinetic Control Interface? Evidence From a Simulated Environment

“…So far, we proofed this concept by investigating the case of a single magnet per muscle for several conditions, in both ideal and anatomical workspaces, in simulated and experimental scenarios [7], [8], [9], [10], [11]. For example, we investigated the effects of geometrical configuration, localization rate and sensor resolution on the tracking accuracy [11], [9] and defined a strategy for optimizing the spatial sensor design [8]. Moreover, we simulated the implant of multiple magnets in a workspace resembling the human forearm and assessed the localization accuracy and the To what extent implanting single vs pairs of magnets per muscle affect the localization accuracy of the myokinetic control interface?…”

“…Generally speaking, muscle contraction could be monitored by implanting and localizing one or more magnets per muscle. So far, we proofed this concept by investigating the case of a single magnet per muscle for several conditions, in both ideal and anatomical workspaces, in simulated and experimental scenarios [7], [8], [9], [10], [11]. For example, we investigated the effects of geometrical configuration, localization rate and sensor resolution on the tracking accuracy [11], [9] and defined a strategy for optimizing the spatial sensor design [8].…”

Transcutaneous Magnet Localizer for a Self-Contained Myokinetic Prosthetic Hand

“…The computation time of the LMA is not predictable a-priori, since the number of iterations needed to converge to a solution depends on the unknown configuration of the magnets in space [25], [28]. Thus, the computation time was measured through the CU internal clock for all the eight configurations, and for both individual and simultaneous movement conditions.…”