Abstract—In IEEE 802.15.4 Wireless Body Area Networks, the existing remote patient monitoring rarely address the joint issues of power consumption, reliability and mobility. Generally, there is a tradeoff between reliability and power consumption since, increasing the reliability may result in increased power consumption. Moreover, when the patient moves from one location to another, it may affect the accuracy of results and leads to increased delay, due to poor channel conditions. To solve the identified problems, in this paper, we propose a Collaborative Remote Patient Monitoring System using IEEE 802.15.4 Wireless Body Area Networks. The proposed architecture consists of clusters of local sensors situated on various parts of the body. Each cluster head communicates with a wireless local gateway (WLG) which lies within the patient’s premises. The WLG in turn communicates with a remote hospital gateway (HG) such that the collected data from WLG is transmitted to the corresponding destination in the HG. The HG applies fuzzy logic decision model based on the input variables patient age, heartbeat, body temperature, percentage of the blood oxygen saturation and blood pressure and determines the criticality condition of patient. By simulation results, we show that the proposed module provides accurate estimation of patient condition.

Index Terms—Wireless body area networks, remote patient monitor, wireless local gateway, fuzzification, sensors, gateway.

Selvaraj Rajalakshmi and Kuthadi Venu Madhav are with Department of CS & IS, Faculty of Science, BIUST, Botswana. Ranjan Abhishek is with Faculty of Computing, Botho University, Lesotho. Yedavalli Venkata Raghava Rao is with Department of Computer Science and Engineering, KLEF, AP, India.

Cite:Selvaraj Rajalakshmi, Kuthadi Venu Madhav, Ranjan Abhishek , Yedavalli Venkata Raghava Rao, "Collaborative Remote Patient Monitoring System Using IEEE 802.15.4 Wireless Body Area Networks," International Journal of Computer and Communication Engineering vol. 8, no. 2, pp. 60-72, 2019.