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Wireless human health monitoring using different techniques has been a popular research area in the last few decades. In this paper, we describe the development of a biomedical sensor node (BSN) for short-range monitoring of static cardiovascular patients using a supervisory computer. In particular, the present research focuses on developing (a) an intelligent hybrid routing algorithm which takes care of intermediate node(s) failure condition; (b) improved packet delivery ratio with the reliability and efficient use of BSN’s battery power. A data compression algorithm in the BSNs further enhanced the communication channel efficiency. With 15 BSNs hardware implemented and tested over a floor area of 93 m2 to collect electrocardiogram and finger pulse signals, we achieved average packet reception accuracy over 98.45% taken cumulatively over 200 trails, along with a latency of 1.58 s per data packet with three faulty BSNs and maximum number of allowable transmission attempts in each hop. A simulation study with the first-order radio model, using 100 BSNs under nine faulty nodes and worst-case scenario, yielded a node power consumption of 3.49 mW per packet and a latency of 22 s per data packet. The performance results are superior to those of similar published works on wireless biomedical health monitoring using wireless sensor networks. The developed system can provide a low-cost solution for patient monitoring at indoor hospital wards in developing nations like India.
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Chandra et al. (2019) studied this question.
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