OBJECTIVE: 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 (MMs- i.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 450 ms, demonstrating position/orientation accuracies in the range of 1 mm/5°. The comparison with the experimental recordings demonstrated a median difference with the simulations in the order of 0.45 mm. 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.
OBJECTIVE: 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 (MMs- i.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 450 ms, demonstrating position/orientation accuracies in the range of 1 mm/5°. The comparison with the experimental recordings demonstrated a median difference with the simulations in the order of 0.45 mm. 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.