Self-paced treadmill controller algorithm based on position and speed of centre of mass

Background Self-paced treadmills are increasingly used in clinical and research settings. Using self-paced (SP) treadmills, researchers can simulate overground walking while participants can walk with different but comfortable gait speeds in a controlled environment. Several algorithms have been designed for self-paced treadmills based on data from force plates, motion capture, and even marker-less systems such as 3D depth cameras. Methods We present a non-linear controller that implements a self-paced algorithm integrated with treadmills. This algorithm uses the subject’s centre-of-mass (CoM) position and velocity, relative to the front and back end of the treadmill as inputs. The controller continuously adjusts the treadmill’s belt speed via belt acceleration. The algorithm attempts to prevent the subject reaching the front and back of treadmill via minimal treadmill acceleration. Findings This method has been safely used in previous studies with over 410 subjects in various populations. We simulated the use of the SP algorithm with three different sensitivities (0.2, 1 and 2). The belt speed predicted by algorithm simulation in matched well with the belt speeds of experiments in (Gait Realtime Analysis Interactive Lab (GRAIL) system. Interpretation This algorithm is integrated with a VR environment in which the subject can be immersed and even be mechanically perturbed. Additionally, this algorithm can be implemented in other treadmills where CoM position is known. We encourage researchers to use and build upon our well-established SP algorithm toward a more standardized SP algorithm in different gait scenarios across various instrumented treadmills with different populations.