Intelligent Systems for Rehabilitation Engineering
by Roshani Raut, Pranav Pathak, Sandeep Kautish, Pradeep N.
4Smart Sensors for Activity Recognition
Rehab A. Rayan1*, Imran Zafar2, Aamna Rafique3 and Christos Tsagkaris4
1Department of Epidemiology, High Institute of Public Health, Alexandria University, Alexandria, Egypt
2Department of Bioinformatics and Computational Biology, Virtual University of Pakistan, Punjab, Pakistan
3Department of Biochemistry, Agriculture University Faisalabad, Punjab, Pakistan
4Faculty of Medicine, University of Crete, Heraklion, Greece
Abstract
Nowadays, health informatics is enhancing the efficiency of healthcare via improved collecting, storing, and retrieving of vital health-related data. Smart sensors arose because of the rapidly growing information and communication technologies and wireless communications. Today, both smartphones and wearable biosensors are highly used for self-monitoring of health and well-being. Smart sensors could enable healthcare providers to monitor digitally and routinely the elderly’s activities. Smart health has emerged from integrating smart wearable sensors in healthcare, while the growth in machine learning (ML) technologies enabled recognizing human activity. This chapter describes applications and limitations of a smart healthcare framework that could model and record, digitally and precisely, body movements and vital signs during daily-living human activities through ML techniques applying smartphones and wearables.
Keywords: Smart health, activity recognition, health monitoring, machine learning, biosensors