Incremental similarity metric to evaluate complexity of human gait: A distributed Wireless Sensor Network approach

The analysis of the complexity of biological systems - a proved parameter indicative of the proper functioning of the human body - traditionally involves highly complex algorithms. In this work we use a well-known measure of similarity, the Normalized Compression Distance (NCD), to compute the variation of complexity of the human gait. We define the incremental NCD (iNCD) and analyze the duration of the gait cycle time series. To validate iNCD as a metric for this type of analysis, we perform experiments using a four-nodes Wireless Sensor Network (WSN), with one trained volunteer running on a treadmill during one hour, at a comfortable velocity. We show that the joint use of a WSN with iNCD analysis is a useful tool for detecting human gait anomalies at controlled computational load.