Model-free adaptive control-based electrical stimulation modulation system for upper limb bi-joint function

Functional Electrical Stimulation (FES) is a rehabilitation technique that helps restore or improve motor function by activating muscles through the distribution of electrical signals to nerves or muscles. However, because of the nonlinear and time-varying characteristics of muscle feedback to external electrical stimulation, achieving highly accurate real-time control is difficult. To precisely control the angles of the elbow joint and wrist joints of the upper limb simultaneously, this study adopted a model-free adaptive control (MFAC) algorithm to design the controller and improve the single-joint algorithm to achieve multi-joint control. A model-free adaptive control (RPPD-MFAC) algorithm with an improved pseudo-partial derivative estimation formula was adopted. The FES system designed based on this algorithm can track the trajectory of the reference joint angle. The algorithm effectively reduces the impact of the initial value of the pseudo-partial derivatives (PPD, a key parameter in the dynamic linearization of the MFAC algorithm) on the control performance such as the convergence rate and tracking accuracy. The system has successfully completed functional tests on both healthy individuals and hemiplegic patients, which is of great significance for the recovery and reconstruction of upper limb motor function.