Physical Activity Classification Using a Smart Textile

Abstract

The aim of this study is to develop a human activities classification system based on a wearable intelligent textile and machine learning techniques. Using the Relief-F feature selection algorithm, we identified a set of relevant features collected by the smart textile. Then, the retained features have fed a classifier in order to recognize the underlying activity. Since the Hexoskin intelligent textile allows the physiological data collection, the classification systems are promising for practical applications which will make it possible to study the patient's state of health or to detect physiological abnormalities in real time depending on the physical activity exerted.