https://orcid.org/0000-0001-8369-3495
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Abstract
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.
Acknowledgement
The authors sincerely thank Dr Arunansu Talukdar, Professor, Medical College and Hospital, Kolkata for his cooperation in performance testing of the BSNs in the hospital ward. The authors also thank the SAP DRS-II program (2015–2020) from University Grants Commission (UGC) at Department of Applied Physics, University of Calcutta for the technical support.
Additional information
Funding
Notes on contributors
Soumyak Chandra
Soumyak Chandra is currently a junior research fellow (JRF) attached to the project funded by Department of Higher Education, Science & Technology and Biotechnology (DHESTB), Govt. of West Bengal at Department of Applied Physics, University of Calcutta. He obtained BTech in electronics and communication engineering in 2013. He has one Indian copyright to his credit. His research interests are intelligent systems, networking and medical instrumentation. Corresponding author. Email: [email protected]
Rajarshi Gupta
Rajarshi Gupta is currently an associate professor at Electrical Engineering Section, Dept of Applied Physics at University of Calcutta, India. His research interests include cardiovascular signal measurements and intelligent health monitoring. He has 49 publications in national and international peer-reviewed journals and conferences, one Indian copyright, two book chapters and one book. Currently, he is guiding three PhD students and one scholar has been awarded PhD. Email: [email protected]
Saurav Ghosh
Saurav Ghosh is currently an assistant professor at A K Choudhury School of Information Technology, University of Calcutta, India. His research interests are mobile crowd sensing, sensor networks and machine learning. He has a number of publications in reputed international journals and conferences. He is currently guiding two PhD scholars and one scholar has been awarded PhD. Email: [email protected]
Sanjoy Mondal
Sanjoy Mondal is currently a Rajiv Gandhi senior research fellow at A K Choudhury School of Information Technology, University of Calcutta, India. He has completed MCA and MTech in information technology, and currently pursuing PhD in the area of smart sensing. He has a number of international conference publications to his credit. Email: [email protected]
