[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
research-article

An Energy Efficient Health Monitoring Approach with Wireless Body Area Networks

Published: 07 April 2022 Publication History

Abstract

Wireless Body Area Networks (WBANs) comprise a network of sensors subcutaneously implanted or placed near the body surface and facilitate continuous monitoring of health parameters of a patient. Research endeavours involving WBAN are directed towards effective transmission of detected parameters to a Local Processing Unit (LPU, usually a mobile device) and analysis of the parameters at the LPU or a back-end cloud. An important concern in WBAN is the lightweight nature of WBAN nodes and the need to conserve their energy. This is especially true for subcutaneously implanted nodes that cannot be recharged or regularly replaced. Work in energy conservation is mostly aimed at optimising the routing of signals to minimise energy expended. In this article, a simple yet innovative approach to energy conservation and detection of alarming health status is proposed. Energy conservation is ensured through a two-tier approach wherein the first tier eliminates “uninteresting” health parameter readings at the site of a sensing node and prevents these from being transmitted across the WBAN to the LPU. The second tier of assessment includes a proposed anomaly detection model at the LPU that is capable of identifying anomalies from streaming health parameter readings and indicates an adverse medical condition. In addition to being able to handle streaming data, the model works within the resource-constrained environments of an LPU and eliminates the need of transmitting the data to a back-end cloud, ensuring further energy savings. The anomaly detection capability of the model is validated using data available from the critical care units of hospitals and is shown to be superior to other anomaly detection techniques.

References

[1]
Goldberger, Ary L., Luis AN Amaral, Leon Glass, Jeffrey M. Hausdorff, Plamen Ch Ivanov, Roger G. Mark, Joseph E. Mietus, George B. Moody, Chung-Kang Peng, and H. Eugene Stanley. 2000. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101, 23 (2000), e215–e220.
[2]
Jamshid Abouei, J. David Brown, Konstantinos N. Plataniotis, and Subbarayan Pasupathy. 2011. Energy efficiency and reliability in wireless biomedical implant systems. IEEE Transactions on Information Technology in Biomedicine 15, 3 (2011), 456–466.
[3]
Temilola Aderibigbe and Hongmei Chi. 2017. A quick outlier detection in wireless body area networks. In Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact. 1–3.
[4]
Sriyanjana Adhikary, Sankhayan Choudhury, and Samiran Chattopadhyay. 2016. A new routing protocol for WBAN to enhance energy consumption and network lifetime. In Proceedings of the 17th International Conference on Distributed Computing and Networking. 1–6.
[5]
Hande Alemdar and Cem Ersoy. 2010. Wireless sensor networks for healthcare: A survey. Computer networks 54, 15 (2010), 2688–2710.
[6]
Aftab Ali and Farrukh Aslam Khan. 2013. Energy-efficient cluster-based security mechanism for intra-WBAN and inter-WBAN communications for healthcare applications. EURASIP Journal on Wireless Communications and Networking, 1 (2013), 216.
[7]
Prasanna Ballal and F. Lewis. 2007. Introduction to Crossbow Mica2 Sensors. Course Note, University of Texas at Arlington.
[8]
Torsha Banerjee, Bin Xie, and Dharma P. Agrawal. 2008. Fault tolerant multiple event detection in a wireless sensor network. Journal of Parallel and Distributed Computing 68, 9 (2008), 1222–1234.
[9]
Deena M. Barakah and Muhammad Ammad-uddin. 2012. A survey of challenges and applications of wireless body area network (WBAN) and role of a virtual doctor server in existing architecture. In Proceedings of the 2012 3rd International Conference on Intelligent Systems Modelling and Simulation. IEEE, 214–219.
[10]
Leo Breiman. 2001. Random forests. Machine learning 45, 1 (2001), 5–32.
[11]
Maria Gabriela Calle Torres. 2006. Energy Consumption in Wireless Sensor Networks Using GSP. Ph.D. Dissertation. University of Pittsburgh.
[12]
Xu Cheng, Ji Xu, Jian Pei, and Jiangchuan Liu. 2010. Hierarchical distributed data classification in wireless sensor networks. Computer Communications 33, 12 (2010), 1404–1413.
[13]
Jennifer Gonik Chester and James L. Rudolph. 2011. Vital signs in older patients: Age-related changes. Journal of the American Medical Directors Association 12, 5 (2011), 337–343.
[14]
Joyce Chiang and Rabab K. Ward. 2014. Energy-efficient data reduction techniques for wireless seizure detection systems. Sensors 14, 2 (2014), 2036–2051.
[15]
Zachary V. Edmonds, William R. Mower, Luis M. Lovato, and Rosaelva Lomeli. 2002. The reliability of vital sign measurements. Annals of Emergency Medicine 39, 3 (2002), 233–237.
[16]
Hilmi E. Egilmez and Antonio Ortega. 2014. Spectral anomaly detection using graph-based filtering for wireless sensor networks. In Proceedings of the 2014 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 1085–1089.
[17]
Shahin Farshchi, Paul H. Nuyujukian, Aleksey Pesterev, Istvan Mody, and Jack W. Judy. 2006. A TinyOS-enabled MICA2-BasedWireless neural interface. IEEE Transactions on Biomedical Engineering 53, 7 (2006), 1416–1424.
[18]
Tia Gao, Tammara Massey, Leo Selavo, David Crawford, Bor-rong Chen, Konrad Lorincz, Victor Shnayder, Logan Hauenstein, Foad Dabiri, James Jeng, Arjun Chanmugam, David White, Majid Sarrafzadeh, and Matt Welsh. 2007. The advanced health and disaster aid network: A light-weight wireless medical system for triage. IEEE Transactions on Biomedical Circuits and Systems 1, 3 (2007), 203–216.
[19]
N. Genes, D. Chandra, S. Ellis, and K. Baumlin. 2013. Validating emergency department vital signs using a data quality engine for data warehouse. The Open Medical Informatics Journal 7, 1 (2013), 34.
[20]
Mohammad Ghamari, Balazs Janko, R Simon Sherratt, William Harwin, Robert Piechockic, and Cinna Soltanpur. 2016. A survey on wireless body area networks for ehealthcare systems in residential environments. Sensors 16, 6 (2016), 831.
[21]
Sudipto Guha, Nina Mishra, Gourav Roy, and Okke Schrijvers. 2016. Robust random cut forest based anomaly detection on streams. In Proceedings of the International Conference on Machine Learning. 2712–2721.
[22]
James A. Hanley and Barbara J. McNeil. 1982. The meaning and use of the area under a receiver operating characteristic curve. Radiology 143, 1 (1982), 29–36.
[23]
Shah Ahsanul Haque, Mustafizur Rahman, and Syed Mahfuzul Aziz. 2015. Sensor anomaly detection in wireless sensor networks for healthcare. Sensors 15, 4 (2015), 8764–8786.
[24]
De-Thu Huynh and Min Chen. 2016. An energy efficiency solution for WBAN in healthcare monitoring system. In Proceedings of the 2016 3rd International Conference on Systems and Informatics. IEEE, 685–690.
[25]
Prarthi Jain, Seemandhar Jain, Osmar R. Zaïane, and Abhishek Srivastava. 2021. Anomaly detection in resource constrained environments with streaming data. IEEE Transactions on Emerging Topics in Computational Intelligence.
[26]
Shanshan Jiang, Yanchuan Cao, Sameer Iyengar, Philip Kuryloski, Roozbeh Jafari, Yuan Xue, Ruzena Bajcsy, and Stephen B. Wicker. 2008. CareNet: An integrated wireless sensor networking environment for remote healthcare. In Proceedings of the ICST 3rd International Conference on Body Area Networks. 9.
[27]
Emil Jovanov, Aleksandar Milenkovic, Chris Otto, Piet De Groen, Bruce Johnson, Steve Warren, and Gueseppe Taibi. 2006. A WBAN system for ambulatory monitoring of physical activity and health status: Applications and challenges. In Proceedings of the 2005 27th Annual Conference on IEEE Engineering in Medicine and Biology. IEEE, 3810–3813.
[28]
Emil Jovanov, Aleksandar Milenkovic, Chris Otto, and Piet C. De Groen. 2005. A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. Journal of Neuro Engineering and Rehabilitation 2, 1 (2005), 6.
[29]
James Kang and Sasan Adibi. 2015. A review of security protocols in mHealth wireless body area networks. In Proceedings of the International Conference on Future Network Systems and Security. Springer, 61–83.
[30]
Ho Chee Keong and Mehmet R. Yuce. 2011. UWB-WBAN sensor node design. In Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2176–2179.
[31]
Jamil Yusuf Khan, Mehmet R. Yuce, Garrick Bulger, and Benjamin Harding. 2012. Wireless body area network (WBAN) design techniques and performance evaluation. Journal of Medical Systems 36, 3 (2012), 1441–1457.
[32]
Kyung Sup Kwak, Sana Ullah, and Niamat Ullah. 2010. An overview of IEEE 802.15. 6 standard. In Proceedings of the 2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies. IEEE, 1–6.
[33]
Christopher Leys, Christophe Lei, Olivier Klein, Philippe Bernard, and Laurent Licata. 2013. Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median. Journal of Experimental Social Psychology 49, 4 (2013), 764–766.
[34]
Yantao Li, Xin Qi, Matthew Keally, Zhen Ren, Gang Zhou, Di Xiao, and Shaojiang Deng. 2012. Communication energy modeling and optimization through joint packet size analysis of BSN and WiFi networks. IEEE Transactions on Parallel and Distributed Systems 24, 9 (2012), 1741–1751.
[35]
Fang Liu, Xiuzhen Cheng, and Dechang Chen. 2007. Insider attacker detection in wireless sensor networks. In Proceedings of the 26th IEEE International Conference on Computer Communications. IEEE, 1937–1945.
[36]
Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou. 2008. Isolation forest. In Proceedings of the 2008 8th IEEE International Conference on Data Mining. IEEE, 413–422.
[37]
Craig Lockwood, Tiffany Conroy-Hiller, and Tamara Page. 2004. Vital signs. JBI Reports 2, 6 (2004), 207–230.
[38]
Angshul Majumdar and Rabab K. Ward. 2015. Energy efficient EEG sensing and transmission for wireless body area networks: A blind compressed sensing approach. Biomedical Signal Processing and Control 20 (2015), 1–9.
[39]
David J. Malan, Thaddeus Fulford-Jones, Matt Welsh, and Steve Moulton. 2004. Codeblue: An ad hoc sensor network infrastructure for emergency medical care. In Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks.
[40]
Jason W. P. Ng, Benny P. L. Lo, Oliver Wells, Morris Sloman, Nick Peters, Ara Darzi, Chris Toumazou, and Guang-Zhong Yang. 2004. Ubiquitous monitoring environment for wearable and implantable sensors. In Proceedings of the International Conference on Ubiquitous Computing.
[41]
Joseph Polastre, Jason Hill, and David Culler. 2004. Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems. 95–107.
[42]
Xin Qi, Gang Zhou, Yantao Li, and Ge Peng. 2012. Radiosense: Exploiting wireless communication patterns for body sensor network activity recognition. In Proceedings of the 2012 IEEE 33rd Real-Time Systems Symposium. IEEE, 95–104.
[43]
Sutharshan Rajasegarar, Christopher Leckie, and Marimuthu Palaniswami. 2008. Anomaly detection in wireless sensor networks. IEEE Wireless Communications 15, 4 (2008), 34–40.
[44]
Moumita Roy, Chandreyee Chowdhury, and Nauman Aslam. 2017. Designing an energy efficient WBAN routing protocol. In Proceedings of the 2017 9th International Conference on Communication Systems and Networks. IEEE, 298–305.
[45]
Marwa Salayma, Ahmed Al-Dubai, Imed Romdhani, and Youssef Nasser. 2017. Wireless body area network (WBAN) a survey on reliability, fault tolerance, and technologies coexistence. ACM Computing Surveys 50, 1 (2017), 1–38.
[46]
Osman Salem, Alexey Guerassimov, Ahmed Mehaoua, Anthony Marcus, and Borko Furht. 2013. Sensor fault and patient anomaly detection and classification in medical wireless sensor networks. In Proceedings of the 2013 IEEE International Conference on Communications. IEEE, 4373–4378.
[47]
Osman Salem, Alexey Guerassimov, Ahmed Mehaoua, Anthony Marcus, and Borko Furht. 2014. Anomaly detection in medical wireless sensor networks using SVM and linear regression models. International Journal of E-Health and Medical Communications 5, 1 (2014), 20–45.
[48]
Hichem Sedjelmaci, Sidi Mohammed Senouci, and Mohamad Al-Bahri. 2016. A lightweight anomaly detection technique for low-resource IoT devices: A game-theoretic methodology. In Proceedings of the 2016 IEEE International Conference on Communications (ICC). IEEE, 1–6.
[49]
Omar Smail, Adda Kerrar, Youssef Zetili, and Bernard Cousin. 2016. ESR: Energy aware and stable routing protocol for WBAN networks. In Proceedings of the 2016 International Wireless Communications and Mobile Computing Conference. IEEE, 452–457.
[50]
G. S. Smrithy, Ramadoss Balakrishnan, and Nikita Sivakumar. 2019. Anomaly detection using dynamic sliding window in wireless body area networks. In Proceedings of the Data Science and Big Data Analytics. Springer, 99–108.
[51]
David M. Studdert, Michelle M. Mello, Jeffrey P. Burns, Ann Louise Puopolo, Benjamin Z. Galper, Robert D. Truog, and Troyen A. Brennan. 2003. Conflict in the care of patients with prolonged stay in the ICU: Types, sources, and predictors. Intensive Care Medicine 29, 9 (2003), 1489–1497.
[52]
Arijit Ukil, Soma Bandyoapdhyay, Chetanya Puri, and Arpan Pal. 2016. IoT healthcare analytics: The importance of anomaly detection. In Proceedings of the 2016 IEEE 30th International Conference on Advanced Information Networking and Applications. IEEE, 994–997.
[53]
Sana Ullah, Henry Higgins, Bin Shen, and Kyung Sup Kwak. 2010. On the implant communication and MAC protocols for WBAN. International Journal of Communication Systems 23, 8 (2010), 982–999.
[54]
Zahid Ullah, Imran Ahmed, Fakhri Alam Khan, Muhammad Asif, Muhammad Nawaz, Tamleek Ali, Muhammad Khalid, and Fahim Niaz. 2019. Energy-efficient harvested-aware clustering and cooperative routing protocol for WBAN. IEEE Access 7 (2019), 100036–100050.
[55]
Anthony D. Wood, John A. Stankovic, Gilles Virone, Leo Selavo, Zhimin He, Qiuhua Cao, Thao Doan, Yafeng Wu, Lei Fang, and Radu Stoleru. 2008. Context-aware wireless sensor networks for assisted living and residential monitoring. IEEE Network 22, 4 (2008), 26–33.
[56]
Miao Xie, Song Han, Biming Tian, and Sazia Parvin. 2011. Anomaly detection in wireless sensor networks: A survey. Journal of Network and Computer Applications 34, 4 (2011), 1302–1325.
[57]
Miao Xie, Jiankun Hu, and Song Guo. 2014. Segment-based anomaly detection with approximated sample covariance matrix in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems 26, 2 (2014), 574–583.
[58]
Chenfu Yi, Lili Wang, and Ye Li. 2015. Energy efficient transmission approach for WBAN based on threshold distance. IEEE Sensors Journal 15, 9 (2015), 5133–5141.
[59]
Tuba Yilmaz, Robert Foster, and Yang Hao. 2010. Detecting vital signs with wearable wireless sensors. Sensors 10, 12 (2010), 10837–10862.
[60]
Yang Zhang, Nirvana Meratnia, and Paul Havinga. 2010. Outlier detection techniques for wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials 12, 2 (2010), 159–170.
[61]
Mingbo Zhao, Zhaoyang Tian, and Tommy W. S. Chow. 2019. Fault diagnosis on wireless sensor network using the neighborhood kernel density estimation. Neural Computing and Applications 31, 8 (2019), 4019–4030.

Cited By

View all
  • (2024)A Survey on Data-Driven Approaches for Reliability, Robustness, and Energy Efficiency in Wireless Body Area NetworksSensors10.3390/s2420653124:20(6531)Online publication date: 10-Oct-2024
  • (2024)Energy efficient and reliable data transmission in WBAN using multivariate gradient divergence African buffalo optimizationInternational Journal of Communication Systems10.1002/dac.599938:4Online publication date: 29-Sep-2024
  • (2023)A Networked System Dependability Validation Framework Using Physical and Virtual NodesIEEE Access10.1109/ACCESS.2023.333068811(127242-127254)Online publication date: 2023

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Computing for Healthcare
ACM Transactions on Computing for Healthcare  Volume 3, Issue 3
July 2022
251 pages
EISSN:2637-8051
DOI:10.1145/3514183
Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 April 2022
Accepted: 01 November 2021
Revised: 01 September 2021
Received: 01 June 2020
Published in HEALTH Volume 3, Issue 3

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Fault detection
  2. isolation forest
  3. sliding window
  4. body area networks

Qualifiers

  • Research-article
  • Refereed

Funding Sources

  • Ministry of Electronics & Information Technology (MeitY)
  • National Research Foundation (NSF)
  • Science and Engineering Research Board

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)87
  • Downloads (Last 6 weeks)12
Reflects downloads up to 01 Mar 2025

Other Metrics

Citations

Cited By

View all
  • (2024)A Survey on Data-Driven Approaches for Reliability, Robustness, and Energy Efficiency in Wireless Body Area NetworksSensors10.3390/s2420653124:20(6531)Online publication date: 10-Oct-2024
  • (2024)Energy efficient and reliable data transmission in WBAN using multivariate gradient divergence African buffalo optimizationInternational Journal of Communication Systems10.1002/dac.599938:4Online publication date: 29-Sep-2024
  • (2023)A Networked System Dependability Validation Framework Using Physical and Virtual NodesIEEE Access10.1109/ACCESS.2023.333068811(127242-127254)Online publication date: 2023

View Options

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Full Text

View this article in Full Text.

Full Text

HTML Format

View this article in HTML Format.

HTML Format

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media