Non-Intrusive Healthcare System in Global Machine-to-Machine Networks

Abstract

A global machine-to-machine (M2M) healthcare system is proposed to monitor patient's health conditions using wearable physiological sensors. This system has the potential of providing excellent accessibility to international as well as intercity healthcare services using the concept of IPv6 over low-power wireless personal area networks (6LoWPANs) in a hierarchical network structure. Non-intrusive low-power embedded wearable sensors are designed to dynamically measure health parameters and are connected to the M2M node for wireless transmission through the internet or external IP-enabled networks via the M2M gateway. Practical tests are conducted using the M2M gateway with the IEEE 802.15.4 and the 6LoWPAN protocol in the internal and external networks environments. In addition, the physical health state is estimated by the heart rate variability analysis in the time and frequency domains to gauge the activity of the autonomic nervous system and consequently provide a stress level to the server. Our approaches for the global M2M healthcare system are managed to process the large amount of physiological signals with the network evaluation and to obtain the stress index and autonomic balance diagram of patient's health conditions.