Abstract
Wireless sensor networks (WSN) comprises of many locally distributed sensor nodes in human body which monitor physical data such as body temperature, pressure, and heart rate. The use of sensor nodes for medical health has greatly attracted the attention of researchers recently because sensor nodes can be used to monitor patient’s health condition or assist physicians in critical situations. This can greatly improve the existing patient care in health service. In this paper, Simulink model of health monitor using WSN has been designed. Parameters such as systolic blood pressure, heart rate, and body temperature have used to build the model and show the performance characteristics of various channels, i.e., AWGN, Rayleigh fading. The result shows that body temperature has the best performance in AWGN channel and heart rate has the best performance in Rayleigh fading channel.
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References
M. Afsaneh, S.M. Ali, S.M. Paymon, S.M. Reza, Application of wireless sensor networks in healthcare system, in Proceedings of 120th ASEE Annual Conference and Exposition (2013), pp. 1–12
A. Carlos, M. Paulo, Wireless sensor networks for biomedical application, in Proceedings 3rd Portuguese Meeting in Bioengineering (2013), pp. 1–4
C. Subhajit, D. Srijan, C. Soumyadeep, B. Sayan, S. Suparna, S.G. Kali, D. Niket, Internet of things and body area network-an integrated future, in Proceedings 8th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (2012), pp. 396–400
S.M. Riazul Islam, D. Kwak, M. Hossain, K. Kyung, Md. Humaun Kabir, The internet of things for health care: a comprehensive survey. IEEE Access J. 3, 678–708 (2015)
B. Bahareh, S. Shabnam, Spectrally efficient telemedicine and in-hospital patient data transfer, in Proceedings of the International Symposium on Medical Measurements and Applications (2017)
I. Al Mamoon, A.K.M. Muzahidul Islam, S. Baharun, K. Shozo, A. Ahmed, Architecture and communication protocols for cognitive radio network enabled hospital, in Proceedings of International Symposium on Medical Information and Communication Technology (2015), pp. 170–174
M. Brice, H. Nicolas, F. Franck, Model-based software engineering to tame the IoT jungle. IEEE Softw. 34(1), 30–36 (2017)
Y.Y. Lo, Y.C. Pei, L.T. Yi, L.H. Jiun, Cloud-based fine gained health information access control framework for lightweight IoT devices with dynamic auditing and attribute revocation. Trans. Cloud Comput. 6(2), 532–544 (2018)
K. Manh, S. Saguna, M. Karan, A. Christer, IReHMo: an efficient IoT-based remote health monitoring system for smart regions, in Proceedings of the International Conference on E-health Networking, Application & Services (2015), pp. 563–568
A.T. Majid, A.N. Waleed, J.M. Zahra, A.A. Ali, Robot assistant in management of diabetes in children based on the internet of things. IEEE Internet Things J. 4(2), 437–445 (2017)
F. Farshad, F. Bahar, I. Mohamed, C. Krishnendu, From EDA to IoT e-health: promises, challenges, and solutions. IEEE Trans. Comput. Des. Integr. Circ. Syst. (2018)
S. Ajmal, D. Soufience, Z. Zonghua, N.A. Farid, Toward energy efficient and trustworthy ehealth monitoring system. China Commun. 12(1), 46–65 (2015)
B. Igor, D. Alessandro, L. Fabio, S. Andrea, Enabling IoT for in-home rehabilitation: accelerometer signals classification methods for activity and movement recognition. IEEE Internet Things J. 4(1), 135–145 (2017)
P. Phond, H. Ekram, N. Dusit, C. Serio, A cognitive radio system for e-health applications in a hospital environment. IEEE Wirel. Commun. 17(1), 20–28 (2010)
M. Jose, B. Camara, Trends in wireless communication towards 5 g networks—the influence of e-health and IoT applications, in Proceedings of the International Multidisciplinary Conference on Computer and Energy Science (2016), pp. 1–7
O. Dramane, T.Q. Minh, K. Francine, A.C. Mohamed, K. Hicham, Mitigating the hospital area communication’s interference using cognitive radio networks, in Proceedings of the International Conference on e-Health Networking, Applications and Services (2013), pp. 324–328
S. Qiang, L. Jing, Y. Hui, M. Zhichao, L. Ming, S. Zhichun, Adaptive cognitive enhanced platform for WBAN, in Proceedings of the International Conference on communications in China: Wireless Networking and Applications (2013), pp. 739–744
D.O. Chukwuemeka, Health monitoring using wireless sensor: a MATLAB approach. Bachelor of Engineering Thesis, Helsinki Metropolia University (2016)
D. Elham, W. Xianbin, A prototype body area network using IEEE 802.15.4. University of Western Ontario (2010)
P.I. Valery, Spread Spectrum and CDMA: Principles and Applications (Wiley Ltd, England, 2005)
Circadian Rhythm Laboratory, http://www.circadian.org/vital.html
MATLAB Documentation, https://www.mathworks.com/help/com/ref/walsh.html
F. RodrĂguez HenrĂquez, N. Cruz CortĂ©s, J.M. Rocha-PĂ©rez, F. Amaro SĂ¡nchez, Generation of gold sequences with applications to spread spectrum systems (2016)
Gold Sequence Generator, https://www.mathworks.com/help/comm/ref/gold.html
R.S. Saifur, H. Masanori, Outage and energy-efficiency analysis of cognitive radio networks: a stochastic approach to transmit antenna selection. Perv. Mob. Comput. Elsevier 42, 444–469 (2017)
R.S. Saifur, H. Masanori, Uplink modelling of cognitive radio network using stochastic geometry. Perform. Eval. Elsevier 117, 1–15 (2017)
Asynchronous CDMA—File Exchange—MATLAB Central, https://www.mathworks.com
CDMA.mdl-File exchange-MATLAB Central, https://www.mathworks.com
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Fazlul Haque Jesan, M., Monwar Jahan Chowdhury, M., Sabuj, S.R. (2020). Simulink Model of Wireless Sensor Network in Biomedical Application. In: Saini, H.S., Singh, R.K., Tariq Beg, M., Sahambi, J.S. (eds) Innovations in Electronics and Communication Engineering. Lecture Notes in Networks and Systems, vol 107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3172-9_3
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