Functional electrical stimulation (FES) applies low-
current high-voltage electrical pulses to muscles to induce a
torque-generating contraction. While FES is widely used for
movement rehabilitation, it is challenging to control the muscle
response for goal-oriented actions, due to the many physical
and neural sources of variation in the signal-to-muscle response
pathway. This paper aims to describe sources of variation that
have not previously been discussed for learning FES control,
and proposes how a neuromuscular simulation might leverage
this knowledge through domain randomisation to help develop
adaptive real-world controllers.
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Functional electrical stimulation (FES) applies low-
current high-voltage electrical pulses to muscles to induce a
torque-generating contraction. While FES is widely used for
movement rehabilitation, it is challenging to control the muscle
response for goal-oriented actions, due to the many physical
and neural sources of variation in the signal-to-muscle response
pathway. This paper aims to describe sources of variation that
have not previously been discussed for learning FES control,
an...
»