Feasibility of Tracking Multiple Implanted Magnets With a Myokinetic Control Interface: Simulation and Experimental Evidence Based on the Point Dipole Model

Abstract

The quest for an intuitive and physiologically appropriate human-machine interface for the control of dexterous prostheses is far from being completed. To control a hand prosthesis, a possible approach could consist in using information related to the displacement of forearm muscles of an amputee during contraction. We recently proposed that muscle displacement could be monitored by implanting passive magnetic markers (MMsi.e. permanent magnets) in them. We dubbed this the myokinetic interface. However, besides the system feasibility, how much its accuracy, precision and computation time are affected by the number and distribution of both the MMs and the sensors used to record the MF was not quantified. Methods: Here we investigated, through simulations validated with a physical system, the performance of a system capable to track position and orientation of up to 9 MMs using information from up to 112 sensors in a volume resembling the dimensions of the human forearm. Results: The system was able to track up to 7 MMs in 450ms, demonstrating position/orientation accuracies in the range of 1mm/5°. The comparison with the experimental recordings demonstrated a median difference with the simulations in the order of 0.45mm. Conclusion: We were able to formulate general guidelines for the implementation of magnetic tracking systems. Significance: Our results pave the way towards the development of new human-machine interfaces for the control of artificial limbs, but they are also interesting for the whole range of biomedical engineering applications exploiting magnetic tracking.

Control Methods for Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship with Proprioceptive Feedback

“…In the following works [ 150 , 151 ], researchers assessed the accuracy of the position tracking of multiple magnetic markers with a set of magnetic field sensors. It was found that increasing number of magnets (and decreasing available space between them) causes localization errors and false predictions to occur more often.…”

The Myokinetic Control Interface: How Many Magnets Can be Implanted in an Amputated Forearm? Evidence From a Simulated Environment

“…Then, a sensor selection strategy (described in the next section) was implemented, aiming at reducing the computational complexity of the localization problem, while still ensuring adequate accuracy. Likewise, the algorithm approximated the MMs as point-like dipoles for solving the localization problem, akin to several previous works [12], [14]. The localization error, both in terms of position and orientation, was assessed relatively to the starting position as:…”

“…A few exceptions to single marker systems are the trackers developed by Yang et al [12], Taylor at al. [13] and Tarantino et al [14] that considered the pose of three (15 unknowns), four (20 unknowns) or seven (35 unknowns) markers.…”

“…In particular, in [14] we investigated the viability and the The myokinetic control interface: how many magnets can be implanted in an amputated forearm? Evidence from a simulated environment performance of a multi-magnet tracking system in a workspace/volume resembling the bulk dimensions of the human forearm, using magnets small enough for being implanted.…”

“…As the performance of a magnetic tracking system strongly depends on its spatial features (i.e. the distance among MMs and between MMs and sensors [14], [15]), it is yet unknown how many magnets could fit in a residual forearm and be successfully tracked to restore independent control over multiple DoFs in a hand prosthesis. Thus, using a 3D CAD anatomical model of the forearm, we simulated the implant of n magnets in n available independent muscles.…”