Fog Computing for Personal Health: Case Study for Sleep Apnea Detection

Abstract

The recent trends in healthcare as e-health and electronic hospital health services pushed healthcare systems to a patient-centric concept, collecting a large amount of data in Electronic or Personal Health Records, providing evidence-based medicine and data analysis. This concept, together with the pervasive health care environments, can generate recommendations and suggestions for preventive intervention, depending on some measured parameters of the patient at home. This can improve the healthcare service from home, based on the health conditions, disease history, and data gained from vital sign sensors according to the Internet of Things Smart living concept. From the technical point of view, a remote monitoring system can provide remote consultation as a part of Assistive technology trends. We used cloud and fog computing for experiment with noninvasive sensors that can follow humans’ sleeping activities towards detecting sleep apnea, to demonstrate the fog-based data processing. With this case study, we have shown the applicability of fog computing and ability trough preprocessing to accomplish computational and bandwidth savings, protecting sensitive data privacy.