Ubiquitous Health Monitoring: Integration of Wearable Sensors, Novel Sensing Techniques, and Body Sensor Networks

Abstract

Abstract. Emergence of the Internet and widespread use of mobile computing have brought traditional eHealth beyond the boundary of the clinical setting, evolving to mHealth which is patient-centered and ubiquitous. Faced with the world's rapidly ageing population and its burden on the healthcare system, one of the intense areas of development in mHealth is continuous patient monitoring. It requires careful integration of wearable sensors and wireless body sensor networks. Unlike traditional ambulatory monitors, sensors for mHealth may appear in various forms, such as watches, jewelry, eyewear, and even smart garments. Recent work have focused on design for wearability, alternative sensing techniques, and mHealth-specific network topologies.

Data Mining and Fusion Techniques for WSNs as a Source of the Big Data

“…This class is used when independent sources are fused their data to produce a new piece of data. This type of data fusion is suitable for the applications of the Body Sensor Networks (BSNs) which are currently enabling a number of humancentric applications specially e-Health and sports monitoring 30 . An example about the cooperative data fusion is the C-SPINE 31 which is a framework allowing data fusion from a number of Collaborative BSNs (CBSNs).…”

Sensor Networks and Data Management in Healthcare: Emerging Technologies and New Challenges

“…The key issue with these systems is the interoperability of these independent information systems [31]. The rapid development of sensor networks and IoT have created new challenges for merging traditional biomedical information systems with massive data streamscreating challenges for real-time decisions making [32,33].…”

Embedded multimodal interfaces in robotics: applications, future trends, and societal implications

“…Context refers to the state of interaction in the broader sense (e.g., space, task, human state, environmental state, system state, etc.). The required interfaces are often not stand-alone systems, as a mouse or a keyboard are, but they are part of the robotic system that make use of input from internal and external sensor systems as well as sensors that are worn by the interacting human [Hung et al 2015] designed to capture physiological measures from the body and neurophysiological measures from the brain. For example, today, exoskeletons are commonly equipped with gravity compensation [Lewis et al 2003].…”