Feasibility of a Sensor-Based Gait Event Detection Algorithm for Triggering Functional Electrical Stimulation during Robot-Assisted Gait Training

摘要: Technologies such as robot-assisted gait trainers or functional electrical stimulation can improve the rehabilitation process of people affected with disorders due to stroke other neurological defects. By combining both technologies, potential disadvantages each technology could be compensated and simultaneously, therapy effects improved. Thus, an algorithm was designed that aims detect cycle a trainer. Based on movement data recorded inertial measurement units, events detected. These further used trigger stimulation. This novel setup offers possibility equipping broad range The aim this paper in particular test feasibility system using units for event detection during training. 39-year-old healthy male adult executed total six training sessions two (Lokomat Lyra). measured from sensors were analyzed by custom-made algorithm. An overall rate 98.1% ± 5.2% Lokomat 94.1% 6.8% Lyra achieved. mean type-1 error 0.3% 1.2% 1.9% 4.3% Lyra. As result, provides promising results research technique enhance adding process.