Modelling muscle spindle dynamics for a proprioceptive prosthesis

Muscle spindles are found throughout our skeletal muscle tissue and continuously provide us with a sense of our limbs' position and motion (proprioception). This paper advances a model for generating artificial muscle spindle signals for a prosthetic limb, with the aim of one day providing amputees with a sense of feeling in their artificial limb. By utilising the Opensim biomechanical modelling package the relationship between a joint's angle and the length of surrounding muscles is estimated for a prosthetic limb. This is then applied to the established Mileusnic model to determine the associated muscle spindle firing pattern. This complete system model is then reduced to allow for a computationally efficient hardware implementation. This reduction is achieved with minimal impact on accuracy by selecting key mono-articular muscles and fitting equations to relate joint angle to muscle length. Parameter values fitting the Mileusnic model to human spindles are then proposed and validated against previously published human neural recordings. Finally, a model for fusimotor signals is also proposed based on data previously recorded from reduced animal experiments.