Review of wireless body sensor networks

  • Authors

    • Sondous Sulaiman Wali university of technology
    • Mohammed Najm Abdullah university of technology
    2020-11-10
    https://doi.org/10.14419/ijet.v9i4.31193
  • Compression Sensing, Healthcare, Sensors, Wireless Body Area Network, WBAN Survey.

  • Wireless body area networks (WBANs) are emerging as important networks that are applicable in various fields. WBAN gives its users access to body sensor data and resources anywhere in the world with the help of the internet. These sensors offer promising applications in areas such as real-time health monitoring, interactive gaming, and consumer electronics. WBAN does not force the patient to stay in the hospital which saves a lot of physical movement. This paper reviews a review of WBANs. We study the following: prior researches, applications and architectures of WBAN, and compression sensing techniques.

     

     

  • References

    1. [1] Shih-Lun Chen, Min-Chun Tuan, Ho-Yin Lee, And Ting- Lan Lin, VLSI “Implementation of a Cost-Efficient Micro Control Unit with an Asymmetric Encryption for Wireless Body Sensor Networksâ€, IEEE. Translations, VOLUME 5, 2017. https://doi.org/10.1109/ACCESS.2017.2679123.

      [2] M. Naeem, U. Pareek, D. C. Lee, A. S. Khwaja, and A. Anpalagan, ‘‘Wireless resource allocation in next- generation healthcare facilities,’’ IEEE Sensors J., vol. 15, no. 3, pp. 1463–1474, Mar. 2015. https://doi.org/10.1109/JSEN.2014.2363571.

      [3] Q. Chen, S. Cheng, H. Gao, J. Li, Z. Cai, ‘‘Energy- efficient algorithm for multicasting in duty-cycled sensor networks,’’ Sensors 15(12), 31224–31243 .2015. https://doi.org/10.3390/s151229860.

      [4] Q. Chen, H. Gao, S. Cheng, Z. Cai, ‘‘Approximate scheduling and constructing algorithms for minimum- energy multicasting in duty-cycled sensor networks,’’ in 2015 International Conference on Identification, Information, and Knowledge in the Internet of Things (IIKI) (IEEE, Piscataway, 2015), pp. 163–168. https://doi.org/10.1109/IIKI.2015.42.

      [5] Forecast for Wearable Devices Worldwide 2016–2018. Available online: http://www.gartner.com/technology/home.jsp (accessed on 26 January 2018).

      [6] Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2016–2021. 2017. Available online: http://www.cisco.com/c/en/us/solutions/collateral/service- provider/visual-networking-indexvni/mobile-white-paper- c11-520862.html (accessed on 26 January 2018).

      [7] Ericsson ConsumerLab: Wearable Technology and the Internet of Things. 2016. Available online: https://www.ericsson.com/thinkingahead/consumerlab/cons umer-insights/wearable-technologyand-the-internet-of- things (accessed on 26 January 2018). H. C. Chuang, C. Y. Shih, C. H. Chou, J. T. Huang, and C.

      [8] J. Wu, ‘‘The development of a blood leakage monitoring system for the applications in hemodialysis therapy,’’ IEEE Sensors J., vol. 15, no. 3, pp. 1515–1522, Mar. 2015. https://doi.org/10.1109/JSEN.2014.2364302.

      [9] Mavinkattimath, S. G., Khanai, R., & Torse, D. A. (2019). A Survey on Secured Wireless Body Sensor Networks. 2019 International Conference on Communication and Signal Processing (ICCSP). https://doi.org/10.1109/ICCSP.2019.8698032.

      [10] W. Lee, H. Kim, M. Hong, Min-Goo Kang, S. R. Jeong, and N. Kim, ‘‘A Survey of the Transmission-Power-Control Schemes in Wireless Body-Sensor Networks, ’’ KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS VOL. 12, NO. 4, Apr. 2018. https://doi.org/10.3837/tiis.2018.04.025.

      [11] Patel, W.D.; Pandya, S.; Koyuncu, B.; Ramani, B.; Bhaskar, S.; Ghayvat, H. NXTGeUH: LoRaWAN based NEXT Generation Ubiquitous Healthcare System for Vital Signs Monitoring & Falls Detection. In Proceedings of the 2018 IEEE Pune, Pune, India, 30 November–2 December 2018; IEEE: Piscataway, NJ, USA, 2019; pp. 1–8. https://doi.org/10.1109/PUNECON.2018.8745431.

      [12] Qu, Y.; Zheng, G.; Ma, H.; Wang, X.; Ji, B.; Wu, H. A survey of routing protocols in WBAN for healthcare applications. Sensors 2019, 19, 1638. [CrossRef] [PubMed]. https://doi.org/10.3390/s19071638.

      [13] Negra, R., Jemili, I., & Belghith, A. (2016). Wireless Body Area Networks: Applications and Technologies. Procedia Computer Science, 83, 1274–1281. https://doi.org/10.1016/j.procs.2016.04.266.

      [14] C. Habib, A. Makhoul, and R.¨el Couturier (2017). On the Problem of Energy Efficient Mechanisms Based on Data Reduction in Wireless Body Sensor Networks. In ENSORCOMM 2017: The Eleventh International Conference on Sensor Technologies and Applications, IARIA, 2017. ISBN: 978-1-61208-580-7.

      [15] Hegde, A., & Prasad, D. (2017). Evaluation of PHY and MAC layer in WBAN using Castalia: Lower layer parameters of WBAN in Castalia. 2017 International Conference on Intelligent Sustainable Systems (ICISS). https://doi.org/10.1109/ISS1.2017.8389438.

      [16] Chen, S.-L., Tuan, M.-C., Lee, H.-Y., & Lin, T.-L., “VLSI Implementation of a Cost-Efficient Micro Control Unit With an Asymmetric Encryption for Wireless Body Sensor Networks,†IEEE Access, vol. 5, pp. 4077–4086. https://doi.org/10.1109/ACCESS.2017.2679123.

      [17] S. Sodagari, S. Member, and B. Bozorgchami, “Technologies and challenges for cognitive radio enabled medical wireless body area networks,†IEEE Access, vol. 6, pp. 29567–29586, 2018. https://doi.org/10.1109/ACCESS.2018.2843259.

      [18] Takabayashi, K., Tanaka, H., Sugimoto, C., Sakakibara, K., & Kohno, R. (2018). Performance evaluation of the quality of service control scheme in multi-hop WBAN based on IEEE 802.15. 6. Sensors, 18(11), 1–20. https://doi.org/10.3390/s18113969.

      [19] Waheed, M., Ahmad, R., Ahmed, W., Drieberg, M., & Alam, M. (2018). Towards Efficient Wireless Body Area Network Using Two-Way Relay Cooperation. Sensors, 18(2), 565. https://doi.org/10.3390/s18020565.

      [20] Bhatia, M., & Kumar, K. (2018). Network selection in cognitive radio enabled Wireless Body Area Networks. Digital Communications and Networks. https://doi.org/10.1016/j.dcan.2018.03.003.

      [21] Khan, R. A., & Pathan, A.-S. K. (2018). The state-of-the-art wireless body area sensor networks: A survey. International Journal of Distributed Sensor Networks, 14(4), 155014771876899. https://doi.org/10.1177/1550147718768994.

      [22] Omuro, Y., Takabayashi, K., & Sakakibara, K. (2018). Detection scheme of a selfish node in WBAN utilizing CSMA/CA based on IEEE 802.15. 6. In the 2018 12th international symposium on medical information and communication technology (ISMICT) (pp.1–4). https://doi.org/10.1109/ISMICT.2018.8573693.

      [23] CicioÄŸlu, M., & Çalhan, A. (2019). SDNâ€based wireless body area network routing algorithm for healthcare architecture. ETRI Journal, 41(4), 452–464. https://doi.org/10.4218/etrij.2018-0630.

      [24] Abidi, B., Jilbab, A., & Mohamed, E. H. (2019). Wireless body area network for health monitoring. Journal of Medical Engineering & Technology, 1–9. https://doi.org/10.1080/03091902.2019.1620354.

      [25] Alkhayyat, A., Thabit, A. A., Al-Mayali, F. A., & Abbasi, Q. H. (2019). WBSN in IoT Health-Based Application: Toward Delay and Energy Consumption Minimization. Journal of Sensors, 2019, 1–14. https://doi.org/10.1155/2019/2508452.

      [26] R, L., & P, V. (2020). Wireless Body Area Network (WBAN)-Based Telemedicine for Emergency Care. Sensors, 20(7), 2153. https://doi.org/10.3390/s20072153.

      [27] Shahbazi, Z., & Byun, Y.-C. (2020). Towards a Secure Thermal-Energy Aware Routing Protocol in Wireless Body Area Network Based on Blockchain Technology. Sensors, 20(12), 3604. https://doi.org/10.3390/s20123604.

      [28] Akbar, M. S., Yu, H., & Cang, S. (2016). Delay, Reliability, and Throughput Based QoS Profile: A MAC Layer Performance Optimization Mechanism for Biomedical Applications in Wireless Body Area Sensor Networks. Journal of Sensors, 2016, 1–17. https://doi.org/10.1155/2016/7170943.

      [29] Pitbull, S., Zhang, H., Wu, W., & Zhang, Y.-T. (2016). A comparative study of fuzzy vault-based security methods for wireless body sensor networks. 2016 10th International Conference on Sensing Technology (ICST). https://doi.org/10.1109/ICSensT.2016.7796226.

      [30] Kalaiselvi, K., & Cerli, A. A. (2017). A pragmatic implementation of energy efficiency in the wireless body area network using CASTALIA. 2017 International Conference on Inventive Computing and Informatics (ICICI). https://doi.org/10.1109/ICICI.2017.8365291.

      [31] AIT ZAOUIAT, C.E. & LATIF, A. (2017). Performances Comparison of IEEE 802.15.6 and IEEE 802.15.4. IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 8, No. 11, 2017 https://doi.org/10.14569/IJACSA.2017.081156.

      [32] Albahri, A. S., Zaidan, A. A., Albahri, O. S., Zaidan, B. B., & Alsalem, M. A. (2018). Real-Time Fault-Tolerant mHealth System: Comprehensive Review of Healthcare Services, Opens Issues, Challenges, and Methodological Aspects. Journal of Medical Systems, 42(8). https://doi.org/10.1007/s10916-018-0983-9.

      [33] Agarwal, N., Biswas, S., Saif, S.& Saha, R. (2019). Evaluation of WBAN with and Without Temporal Model using Castalia. TECH VISTAS. VOL. 1, NO. 2, FEB. 2019.

      [34] Gupta, R., & Biswas, S. (2019). Priority-based IEEE 802.15.4 MAC by varying GTS to satisfy heterogeneous traffic in healthcare applications. Wireless Networks. https://doi.org/10.1007/s11276-019-02149-6.

      [35] Vidhyotma & Singh, J., (2020). WBSN based safe lifestyle: a case study of the heart rate monitoring system. International Journal of Electrical and Computer Engineering (IJECE) Vol. 10, No. 3, June 2020, pp. 2296~2304 ISSN: 2088-8708, https://doi.org/10.11591/ijece.v10i3.pp2296-2304.

      [36] Altamimi, A. S. H., Al-Dulaimi, O. R. K., Mahawish, A. A., Hashim, M. M. & Mustafa Sabah Taha, M. S. (2020). Power minimization of WBSN using an adaptive routing protocol. Indonesian Journal of Electrical Engineering and Computer Science Vol. 19, No. 2, August 2020, pp. 837~846 ISSN: 2502-4752, https://doi.org/10.11591/ijeecs.v19.i2.pp837-846.

      [37] Benmansour, T., Ahmed, T., Moussaoui, S., & Doukha, Z. (2020). Performance analyses of the IEEE 802.15.6 wireless body area network with heterogeneous traffic. Journal of Network and Computer Applications, 102651. https://doi.org/10.1016/j.jnca.2020.102651.

      [38] Hasan, K., Ahmed, K., Biswas, K., Saiful Islam, M., & Sianaki, O. A. (2020). Software-defined application-specific traffic management for wireless body area networks. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2020.01.052.

      [39] A. Asif, I. A. Sumra. (2017). Applications of Wireless Body Area Network (WBAN): A Survey. ESTIRJ, ENGINEERING SCIENCE, AND TECHNOLOGY INTERNATIONAL RESEARCH JOURNAL, VOL1, NO.1, APR, 2017.

      [40] Kim, Y. K., Wang, H., & Mahmud, M. S. (2016). Wearable body sensor network for health care applications. Smart Textiles and Their Applications, 161–184. https://doi.org/10.1016/B978-0-08-100574-3.00009-6.

      [41] Cao, Y., Zhang, G., Liu, F., You, I., Zheng, G., Samuel, O. W., & Chen, S. (2018). Muscle Activity-Driven Green- Oriented Random Number Generation Mechanism to Secure WBSN Wearable Device Communications. Wireless Communications and Mobile Computing, 2018, 1–11. https://doi.org/10.1155/2018/3403456.

      [42] A. Sangwan and P. P. Bhattacharya (2015). Wireless Body Sensor Networks: A Review. International Journal of Hybrid Information Technology Vol.8, No.9 (2015), pp.105-120. https://doi.org/10.14257/ijhit.2015.8.9.12.

      [43] Gupta, S., & Kaur, P. (2015). WBAN Health Monitoring System Using TEEN Protocol: Threshold Sensitive Energy Efficient Network Protocol. IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 2 Issue 10, October 2015. ISSN 2348 – 7968.

      [44] Singh, A., & Dandapat, S. (2016). Exploiting multi-scale signal information in joint compressed sensing recovery of multi-channel ECG signals. Biomedical Signal Processing and Control, 29, 53–66. https://doi.org/10.1016/j.bspc.2016.05.008.

      [45] M. Yamin, A.A.A. Sen, Improving privacy and security of user data in location-based services, International Journal of Ambient Computing and Intelligence (IJACI) 9 (1) (2018) 19–42. https://doi.org/10.4018/IJACI.2018010102.

      [46] M. Khosravy, N. Gupta, N. Marina, I.K. Sethi, M.R. Asharif, Morphological filters: an inspiration from natural geometrical erosion and dilation, in Nature-Inspired Computing and Optimization, Springer, Cham, 2017, pp. 349–379. https://doi.org/10.1007/978-3-319-50920-4_14.

      [47] S. Hemalatha, S.M. Anouncia, Unsupervised segmentation of remote sensing images using FD based texture analysis model and ISODATA, International Journal of Ambient Computing and Intelligence (IJACI) 8 (3) (2017) 58–75. https://doi.org/10.4018/IJACI.2017070104.

      [48] A.A. Picorone, T.R. de Oliveira, R. Sampaio-Neto, M. Khosravy, M.V. Ribeiro, Channel characterization of low voltage electric power distribution networks for PLC applications based on measurement campaign, International Journal of Electrical Power & Energy Systems 116 (105) (2020) 554. https://doi.org/10.1016/j.ijepes.2019.105554.

      [49] E. Santos, M. Khosravy, M.A. Lima, A.S. Cerqueira, C.A. Duque, A. Yona, High accuracy power quality evaluation under a colored noisy condition by filter bank ESPRIT, Electronics 8 (11) (2019) 1259. https://doi.org/10.3390/electronics8111259.

      [50] E. Santos, M. Khosravy, M.A. Lima, A.S. Cerqueira, C.A. Duque, Esprit associated with filter bank for power-line harmonics, sub-harmonics and inter-harmonics parameters estimation, International Journal of Electrical Power & Energy Systems 118 (105) (2020) 731. https://doi.org/10.1016/j.ijepes.2019.105731.

      [51] K. Melo, M. Khosravy, C. Duque, N. Dey, Chirp code deterministic compressive sensing: analysis on power signal, in 4th International Conference on Information Technology and Intelligent Transportation Systems (ITITS 2019), IOS Press, 2020, pp. 125–134. https://doi.org/10.1016/B978-0-12-821247-9.00012-3.

      [52] N. Gupta, M. Khosravy, N. Patel, T. Senjyu, A bi-level evolutionary optimization for coordinated transmission expansion planning, IEEE Access 6 (2018) 48455–48477. https://doi.org/10.1109/ACCESS.2018.2867954.

      [53] N. Gupta, M. Khosravy, K. Saurav, I.K. Sethi, N. Marina, Value assessment method for expansion planning of generators and transmission networks: a non-iterative approach, Electrical Engineering 100 (3) (2018) 1405–1420. https://doi.org/10.1007/s00202-017-0590-7.

      [54] G.V. Kale, V.H. Patil, A study of vision-based human motion recognition and analysis, International Journal of Ambient Computing and Intelligence (IJACI) 7 (2) (2016) 75–92. https://doi.org/10.4018/IJACI.2016070104.

      [55] N. Dey, A.S. Ashour, A.S. Ashour, A. Singh, Digital analysis of microscopic images in medicine, Journal of Advanced Microscopy Research 10 (1) (2015) 1–13. https://doi.org/10.1166/jamr.2015.1229.

      [56] B. Alenljung, J. Lindblom, R. Andreasson, T. Ziemke, User experience in social human-robot interaction, in Rapid Automation: Concepts, Methodologies, Tools, and Applications, IGI Global, 2019, pp. 1468–1490. https://doi.org/10.4018/978-1-5225-8060-7.ch069.

      [57] N. Dey, A.S. Ashour, F. Shi, S.J. Fong, R.S. Sherratt, Developing residential wireless sensor networks for ECG healthcare monitoring, IEEE Transactions on Consumer Electronics 63 (4) (2017) 442–449. https://doi.org/10.1109/TCE.2017.015063.

      [58] A.S. Ashour, S. Samanta, N. Dey, N. Kausar, W.B. Abdessalemkaraa, A.E. Hassanien, Computed tomography image enhancement using cuckoo search: a log transform- based approach, Journal of Signal and Information Processing 6 (03) (2015) 244. https://doi.org/10.4236/jsip.2015.63023.

      [59] M. Khosravy, N. Gupta, N. Marina, I. Sethi, M. Asharif, Brain action inspired morphological image enhancement, in Nature-Inspired Computing and Optimization, Springer, Cham, 2017, pp. 381–407. https://doi.org/10.1007/978-3-319-50920-4_15.

      [60] M. Khosravy, N. Gupta, N. Marina, I. Sethi, M. Asharifa, Perceptual adaptation of image based on Chevreul–Mach bands visual phenomenon, IEEE Signal Processing Letters 24 (5) (2017) 594–598. https://doi.org/10.1109/LSP.2017.2679608.

      [61] P. Sosnin, Precedent-oriented approach to conceptually experimental activity in designing the software-intensive systems, International Journal of Ambient Computing and Intelligence (IJACI) 7 (1) (2016) 69–93. https://doi.org/10.4018/IJACI.2016010104.

      [62] S. Gupta, M. Khosravy, N. Gupta, H. Darbari, N. Patel, Hydraulic system onboard monitoring and fault diagnostic in the agricultural machine, Brazilian Archives of Biology and Technology 62 (2019). https://doi.org/10.1590/1678-4324-2019180363.

      [63] S. Gupta, M. Khosravy, N. Gupta, H. Darbari, In-field failure assessment of tractor hydraulic system operation via a pseudo spectrum of acoustic measurements, Turkish Journal of Electrical Engineering & Computer Sciences 27 (4) (2019) 2718–2729. https://doi.org/10.3906/elk-1807-165.

      [64] N. Kausar, S. Palaniappan, B.B. Samir, A. Abdullah, N. Dey, Systematic analysis of applied data mining based optimization algorithms in clinical attribute extraction and classification for diagnosis of cardiac patients, in Applications of Intelligent Optimization in Biology and Medicine, Springer, 2016, pp. 217–231. https://doi.org/10.1007/978-3-319-21212-8_9.

  • Downloads

  • How to Cite

    Sulaiman Wali, S., & Najm Abdullah, M. (2020). Review of wireless body sensor networks. International Journal of Engineering & Technology, 9(4), 863-870. https://doi.org/10.14419/ijet.v9i4.31193