From Micro to Nano: The Evolution of Wireless Sensor-Based Health Care.

Over the past decade, embedded systems and microelectromechanical systems have evolved in a radical way, redefining our standard of living and enhancing the quality of life. Health care, among various other fields, has benefited vastly from this technological development. The concept of using sensors for health care purposes originated in the late 1980s when sensors were developed to measure certain physiological parameters associated with the human body. In traditional sensor nodes, the signal sources are mostly different environmental phenomena (such as temperature, vibration, and luminosity) or man-made events (such as intrusion and mobile target tracking), whereas in case of the physiological sensors, the signal source is living human tissue. These sensor nodes, as their primary sensing element, have a diaphragm that converts pressure into displacement. This displacement, in turn, is subsequently transformed into an electrical signal. The concept of wireless physiological sensor nodes, however, gained popularity in the mid-2000s, with the sensed data from the nodes transmitted to the hub via a wireless medium. The network formed by this heterogeneous set of wireless body sensor nodes is termed a wireless body-area network (WBAN). Each WBAN is essentially a composition of multiple wireless body sensor nodes and a single hub. The hub is primarily responsible for acquisition of the raw sensed data from all the component sensor nodes and first-level aggregation of the data before transmitting the aggregated data for further analysis to a remote data acquisition center. Here, we outline the evolution of WBANs in the context of modern health care and its convergence with nanotechnology.

Priority-based time-slot allocation in wireless body area networks during medical emergency situations: an evolutionary game-theoretic perspective.

In critical medical emergency situations, wireless body area network (WBAN) equipped health monitoring systems treat data packets with critical information regarding patients' health in the same way as data packets bearing regular healthcare information. This snag results in a higher average waiting time for the local data processing units (LDPUs) transmitting data packets of higher importance. In this paper, we formulate an algorithm for Priority-based Allocation of Time Slots (PATS) that considers a fitness parameter characterizing the criticality of health data that a packet carries, energy consumption rate for a transmitting LDPU, and other crucial LDPU properties. Based on this fitness parameter, we design the constant model hawk-dove game that ensures prioritizing the LDPUs based on crucial properties. In comparison with the existing works on priority-based wireless transmission, we measure and take into consideration the urgency, seriousness, and criticality associated with an LDPU and, thus, allocate transmission time slots proportionately. We show that the number of transmitting LDPUs in medical emergency situations can be reduced by 25.97%, in comparison with the existing time-division-based techniques.