Novel approach to human walking speed enhancement based on drift estimation

The speed of human walking is a valuable indicator of individuals' health status, for example in sports or medicine. Classic methods such as the camera-based approach have serious limitations: (1) they can be used only in the laboratory setting, and (2) the computational complexity of the data processing is remarkably high. The development of small wearable inertial sensing systems and suitable methods of data processing allow the analysis of human motion to be performed outside the laboratory. Moreover, such solutions can work in the real-time regime. Unfortunately, the inertia-based human walking speed estimation systems applying the strap-down integration approach have an unavoidable drawback. The disadvantage is the estimation inaccuracies caused by the accumulation of errors. This paper presents an approach for attenuating these errors by applying a method for estimating drift. (C) 2018 Elsevier Ltd. All rights reserved.