Modelling and simulations of a central pattern generator controlled, antagonistically actuated limb joint

Wearable assistive devices (WAD) assist rehabilitation and recuperation. However, WADs´ development is impeded by traditional actuators and current control paradigms´ lack of compliance and adaptability, in contrast to the mammalian central nervous system. A limb´s joint´s compliance is a function of muscles´ level of activation and passive viscoelastic properties. Increased equal and unequal co-activation of a limb joint´s muscles leads to an increasingly stable joint. Unequal limb joint muscle activation leads to an angular displacement. Muscles´ activation is controlled by alpha motor neurons, which are innervated by the spinal-cord´s autonomous neural networks, i.e. central pattern generators. Given a continuous excitatory supraspinal input, a two-level, mutually inhibiting, CPG network can control an antagonistically actuated limb joint´s muscles´ level of activation, thus the joint´s compliance, and joint oscillation frequency.