Feature Detection and Extraction Techniques for Sensor Data

Remote human well‐being observing incorporates sensors, actuators, and propelled correspondence innovations and provides opportunities for the patient to remain at their home rather than in costly medical service facilities. This chapter discusses the electronic health record and the various sensors used in healthcare systems. The use of sensor data and its parameters is elaborated. The chapter discusses the various feature extraction techniques provides case studies for better understanding feature extraction through sensor data. It proposes a sensor‐based system for health monitoring through activity recognition using deep recurrent neural network, which is a promising deep learning algorithm that is completely based on sequential information. The proposed approach shows superior performance on all the datasets. The chapter provides pseudocode for the proposed approach.