Design & Evaluation Of A Sensor Minimal Gait Phase And Situation Detection Algorithm Of Human Walking

This paper presents the design and evaluation of gait detection algorithm based on one IMU placed on the shank. The algorithm is based on adaptive thresholds by artificial neural network and fuzzy logic to identify gait phase and situation for real-time applications like micro-processed prosthesis. Offline evaluation with fifteen able-bodied subjects and two transtibial amputees shows high detection rates of 98 % for distinguishing stance from swing phase as well as 93.6 % between straight and turning gait situation with global parameters.