Estimation of speed and incline of walking using neural network

A portable datalogger is designed to record body accelerations during human walking. The recorded signals are parametrised and the pattern of walking at each gait cycle is found. These patterns are presented to two neural networks which estimate the incline and the speed of walking. Subjects performed a treadmill walking followed by a self paced walking on an outdoor test circuit involving roads of various inclines. The results show a good estimation of the incline and the speed for all of the subjects. To the best of our knowledge these results constitute the first speed and incline estimation of level and grade walking in free-living conditions