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Wearable Wireless Body Area Nodes for Remote Physiological Signal Monitoring System

DOI: 10.4236/jbise.2019.122011, PP. 151-182

Keywords: WPMS, WBAN, Textile Electrode, Sensor Node, Physiological Signals, ZigBee

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Abstract:

Wearable remote health monitoring systems have gained significant prominence in the recent years due to their growth in technological advances. One form of the Wearable Physiological Monitoring System (WPMS) is the Wearable Body Area Networks (WBAN) used to monitor the health status of the wearer for long durations. The paper discusses a prototype WBAN based wearable physiological monitoring system to monitor physiological parameters such as Electrocardiogram (ECG) and Electroencephalogram (EEG) acquired using a textile electrode, Photoplethysmogram (PPG), Galvanic Skin Response (GSR), Blood Pressure derived from analysis of Pulse Transmit Time (PTT) and body temperature. The WBAN consists of three sensor nodes that are placed strategically to acquire the physiological signals and the sensor nodes communicate to a chest/wrist worn sink node also known as wearable data acquisition hardware. The sink node receives physiological data from the sensor nodes and is transmitted to a remote monitoring station. The remote monitoring station receives the raw data and it is processed to remove noises, such as power line interference, baseline wander and tremor in the signals and the information is extracted and displayed. The WBANs are designed using the ZigBee wireless communication modules to transmit and receive the data. At the remote monitoring station the physiological parameters such as heart rate, pulse rate, systolic, diastolic blood pressure, GSR and body temperature are continuously monitored from the wearer. The data acquired from the wearable monitoring system is statically validated using a qualified medical device on 34 subjects.

References

[1]  Raskovic, D., Martin, T. and Jovanov, E. (2004) Medical Monitoring Applications for Wearable Computing. The Computer Journal, 47, 495-504.
https://doi.org/10.1093/comjnl/47.4.495
[2]  Martin, T., Jovanov, E. and Raskovic, D. (2000) Issues in Wearable Computing for Medical Monitoring Applications: A Case Study of a Wearable ECG Monitoring Device. Proceedings. of the 4th International Symposium on Wearable Computers, Atlanta, GA, 16-17 October 2000, 43-49.
https://doi.org/10.1109/ISWC.2000.888463
[3]  Kim, Y., Lee, S.S. and Lee, S.K. (2015) Coexistence of Zig Bee-Based WBAN and WiFi for Health Telemonitoring Systems. IEEE Journal of Biomedical and Health Informatics, 20, 222-230.
https://doi.org/10.1109/JBHI.2014.2387867
[4]  Egbogah, E.E. and Fapojuwo, A.O. (2013) Achieving Energ Efficient Transmission in Wireless Body Area Networks for the Physiological Monitoring of Military Soldiers. 2013 IEEE Military Communications Conference (MILCOM 2013), San Diego, CA, 18-20 November 2013.
https://doi.org/10.1109/MILCOM.2013.233
[5]  Moulik, S., Misra, S. and Chakraborty, C. (2015) CAPCoS: Context-Aware PAN Coordinator Selection for Health Monitoring of Soldiers in Battlefield. 2015 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Kolkata, India, 15-18 December 2015.
https://doi.org/10.1109/ANTS.2015.7413650
[6]  Mundt, C.W., Montgomery, K.N., Udoh, U.E., Barker, V.N., Thonier, G.C., Tellier, A.M., et al. (2005) A Multi Parameter Wearable Physiologic Monitoring System for Space and Terrestrial Applications. IEEE Transactions on Information Technology in Biomedicine, 9, 382-391.
https://doi.org/10.1109/TITB.2005.854509
[7]  Aqueveque, P., Gutierrez, C., Saavedra, F., Pino, E.J., Morales, A.S. and Wiechmann, E. (2017) Monitoring Physiological Variables of Mining Workers at High Altitude. IEEE Transactions on Industry Applications, 53.
[8]  Hazarika, P. (2016) Implementation of Smart Safety Helmet for Coal Mine Workers. 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), Delhi, India, 4-6 July 2016.
https://doi.org/10.1109/ICPEICES.2016.7853311
[9]  Maity, T., Das, P.S. and Mukherjee, M. (2012) A Wireless Surveillance and Safety System for Mine Workers Based on Zigbee. 2012 1st International Conference on Recent Advances in Information Technology (RAIT), Dhanbad, India, 15-17 March 2012.
https://doi.org/10.1109/RAIT.2012.6194496
[10]  Potirakis, S., Mitilineos, S., Chatzistamatis, P., Vassiliadis, S., Primentas, A., Kogias, D., Michailidis, E.T., Rangoussi, M., Bahadır, S.K., Atalay, O., Kalaoglu, F. and Saglam, Y. (2016) Physiological Parameters Monitoring of Fire-Fighters by Means of a Wearable Wireless Sensor System. 2016 IOP Science Conference Series: Material Science Engineering 108012011, March 2016.
[11]  Coca, A., Roberge, R.J., Williams, W.J., Landsittel, D.P., Powell, J.B. and Palmiero, A. (2009) Physiological Monitoring in Firefighter Ensembles: Wearable Plethysmographic Sensor Vest versus Standard Equipment. Journal of Occupational and Environmental Hygiene, 7, 109-114.
https://doi.org/10.1080/15459620903455722
[12]  Bu, Y., Wu, W., Zeng, X.Y., Koehl, L. and Tartare, G. (2015) A Wearable Intelligent System for Real Time Monitoring Fire Fighter’s Physiological State and Predicting Dangers. 2015 IEEE 16th International Conference on Communication Technology (ICCT), China, 8-20 October 2015.
[13]  Hiware, A. and Tet, A.D. Sudden Infant Death Monitoring Using Smart Wearable System. International Journal of Science, Engineering and Technology Research (IJSETR), 6.
[14]  Fernandes, D., Ferreira, A.G., Branco, S., Abrishambaf, R., Carvalho, H., Mendes, J., Cabral, J. and Rocha, A. (2016) Energy Saving Mechanism for a Smart Wearable System: Monitoring Infants during the Sleep. 2016 IEEE International Conference on Industrial Technology (ICIT), Taipei, 14-17 March 2016.
https://doi.org/10.1109/ICIT.2016.7475062
[15]  Oliver, N. and Flores-Mangas, F. (2007) HealthGear: Automatic Sleep Apnea Detection and Monitoring with a Mobile Phone. Journal of Communications, 2, 1-9.
[16]  Sannino, G., De Falco, I. and De Pietro, G. (2014) Monitoring Obstructive Sleep Apnea by Means of a Real Time Mobile System Based on the Automatic Extraction of Sets of Rules through Differential Evolution. Journal of Biomedical Informatics, 49, 84-100.
https://doi.org/10.1016/j.jbi.2014.02.015
[17]  Paradiso, R., Loriga, G. and Taccini, N. (2005) A Wearable Health Care System Based on Knitted Integrated Sensors. IEEE Transactions on Information Technology in Biomedicine, 9, 337-344.
https://doi.org/10.1109/TITB.2005.854512
[18]  Pandian, P.S., Mohanavelu, K., Safeer, K.P., Kotresh, T.M., Shakunthala, D.T., Gopal, P. and Padaki, V.C. (2008) Smart Vest: Wearable Multi-Parameter Remote Physiological Monitoring System. Medical Engineering & Physics, 466-477.
https://doi.org/10.1016/j.medengphy.2007.05.014
[19]  Zheng, Y., Leung, B., Sy, S., Zhang, Y. and Poon, C.C. (2012) A Clip-Free Eyeglasses-Based Wearable Monitoring Device for Measuring Photoplethysmograhic Signals. Conference Proceedings in IEEE Engineering Medicine and Biology Society, San Diego, 28 August-1 September 2012, 5022-5025.
[20]  Anliker, U., Ward, J.A., Lukowicz, P., Tröster, G., Dolveck, F., Baer, M., Keita, F., Schenker, E.B., Catarsi, F., Coluccini, L., Belardinelli, A., Shklarski, D., Alon, M., Hirt, E., Schmid, R. and Vuskovic, M. (2004) AMON: A Wearable Multiparameter Medical Monitoring and Alert System. IEEE Transactions on Information in Biomedicine, 8, 415-427.
https://doi.org/10.1109/TITB.2004.837888
[21]  Malhi, K., Chandra, S., Schnepper, J., Haefke, M. and Ewald, H. (2012) A Zigbee Based Wearable Physiological Parameters Monitoring System. IEEE Sensors Journal, 12, 423-430.
https://doi.org/10.1109/JSEN.2010.2091719
[22]  Mundt, C.W., Montgomery, K.N., Udoh, U.E., Barker, V.N., Thonier, G.C., Tellier, A.M., Ricks, R.D., Darling, R.B., Cagle, Y.D., Cabrol, N.A., Ruoss, S.J., Swain, J.L., Hines, J.W. and Kovacs, G.T.A. (2005) A Multiparameter Wearable Physiologic Monitoring System for Space and Terrestrial Applications. IEEE Transactions on Information Technology in Biomedicine, 9, 382-391.
https://doi.org/10.1109/TITB.2005.854509
[23]  Halin, N., Junnila, M., Loula, P. and Aarnio, P. (2005) The LifeShirt System for Wireless Patient Monitoring in the Operating Room. Journal of Telemedicine and Telecare, 11, 41-43.
https://doi.org/10.1258/135763305775124623
[24]  Coyle, S., Lau, K.-T., Moyna, N., O’Gorman, D., Diamond, D., Di Francesco, F., Costanzo, D., Salvo, P., Trivella, M.G., De Rossi, D.E., Taccini, N., Paradiso, R., Porchet, J.-A., Ridolfi, A., Luprano, J., Chuzel, C., Lanier, T., Revol-Cavalier, F., Schoumacker, S., Mourier, V., Chartier, I., Convert, R., De-Moncuit, H. and Bini, C. (2010) BIOTEX—Biosensing Textiles for Personalised Healthcare Management. IEEE Transactions on Information Technology in Biomedicine, 14, 364-370.
https://doi.org/10.1109/TITB.2009.2038484
[25]  Jovanov, E., Milenkovic, A., Otto, C. and de Groen, P.C. (2005) A Wireless Body Area Network of Intelligent Motion Sensors for Computer Assisted Physical Rehabilitation. Journal of Neuro Engineering and Rehabilitation, 2, 6.
[26]  Al Rasyid, M.U.H., Lee, B.-H. and Sudarsono, A. (2015) Wireless Body Area Network for Monitoring Body Temperature, Heart Beat and Oxygen in Blood. International Seminar on Intelligent Technology and Its Applications, Surabaya, 20-21 May 2015, 95-98.
[27]  Abidoye, A.P., Azeez, N.A., Adesina, A.O., Agbele, K.K. and Nyongesa, H.O. (2011) Using Wearable Sensors for Remote Healthcare Monitoring System. Journal of Sensor Technology, 1, 22-28.
https://doi.org/10.4236/jst.2011.12004
[28]  Thwe, H.M. and Tun, H.M. (2015) Patient Health Monitoring Using Wireless Body Area Network. International Journal of Scientific & Technology Research, 4, 364-368.
[29]  Kachuee, M., Kiani, M.M., Mohammadzade, H. and Shabany, M. (2017) Cuffless Blood Pressure Estimation Algorithms for Continuous Health-Care Monitoring. IEEE Transactions on Biomedical Engineering, 64, 859-869.
https://doi.org/10.1109/TBME.2016.2580904
[30]  Tang, Z., Tamura, T., Sekine, M., Huang, M., Chen, W., Yoshida, M., Sakatani, K., Kobayashi, H. and Kanaya, S. (2017) A Chair for Cufless Real-Time Estimation of Systolic Blood Pressure Based on Pulse Arrival Time. IEEE Journal of Biomedical and Health Informatics, 21, 1194-1205.
https://doi.org/10.1109/JBHI.2016.2614962
[31]  Mbachu, C.B. and Offor, K.J. (2013) Reduction of Power Line Noise in ECG Signal Using FIR Digital Filter Implemented with Hamming Window. International Journal of Science, Environment and Technology, 2, 1380-1387.
[32]  Arya, R. and Jaiswal, S. (2015) Design of Low Pass FIR Filters Using Kaiser Window Function with Variable Beta(β). International Journal of Multi-Disciplinary and Current Research, 3, 220-224.
[33]  Bland, J.M. and Altman, D.G. (2010) Statistical Methods for Assessing Agreement between Two Methods of Clinical Measurement. International Journal of Nursing studies, 47, 931-936.
https://doi.org/10.1016/j.ijnurstu.2009.10.001
[34]  Griffiths, P. and Murrells, T. (2010) Reliability Assessment and Approaches to Determining Agreement between Measurements: Classic Paper. International Journal of Nursing Studies, 47, 937-938.
https://doi.org/10.1016/j.ijnurstu.2010.03.004
[35]  Oweis, R.J., Basim, O. and Al-Tabbaa, B.O. (2014) QRS Detection and Heart Rate Variability Analysis: A Survey. Biomedical Science and Engineering, 2, 13-34.
[36]  Milagro, F.J. (2016) Poincare Plot Analysis and Graphical User Interface Development for the Study of Heart Rate Variability in Asthmatic Children. Master of Science Thesis, Tampere University of Technology.
[37]  Shaffer, F. and Ginsberg, J.P. (2017) An Overview of Heart Rate Variability Metrics and Norms. Frontiers in Public Health, 5, 1-17.
https://doi.org/10.3389/fpubh.2017.00258
[38]  Tjolleng, A., Jung, K., Hong, W., Lee, W., Lee, B., You, H., Son, J. and Park, S. (2017) Classification of a Driver’s Cognitive Workload Levels Using Artificial Neural Network on ECG Signals. Applied Ergonomics, 59, 326-332.
https://doi.org/10.1016/j.apergo.2016.09.013
[39]  Task Force of The European Society of Cardiology (1996) Guidelines Heart Rate Variability. European Heart Journal, 17, 354-381.
[40]  Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology (1997) Heart Rate Variability: Standards of Measurement, Physiological Interpretation, and Clinical Use. Circulation, 93, 1043-1065.
[41]  Billman, G., Huikuri, H., Sacha, J. and Trimmel, K. (2015) An Introduction to Heart Rate Variability: Methodological Considerations and Clinical Applications. Frontiers in Physiology, 6, 1-3.
https://doi.org/10.3389/fphys.2015.00055
[42]  Kleiger, R.E., Stein, P.K. and Bigger, J.T. (2005) Heart Rate Variability: Measurement and Clinical Utility. Annals of Noninvasiv Electrocardiology, 10, 88-101.
https://doi.org/10.1111/j.1542-474X.2005.10101.x
[43]  Singh, D., Vinod, K. and Saxena, S. (2004) Sampling Frequency of the RR Interval Time Series for Spectral Analysis of Heart Rate Variability. Journal of Medical Engineering & Technology, 28, 263-272.
https://doi.org/10.1080/03091900410001662350
[44]  Patel, M., Lal, S.K., Kavanagh, D. and Rossiter, P. (2011) Applying Neural Network Analysis on Heart Rate Variability Data to Assess Driver Fatigue. Expert Systems with Applications, 38, 7235-7242.
https://doi.org/10.1016/j.eswa.2010.12.028
[45]  Brennan, M., Palaniswami, M. and Kamen, P.W. (2001) Do Existing Measures of Poincare Plot Geometry Reflect Nonlinear Features of Heart Rate Variability? IEEE Transactions on Biomedical Engineering, 48, 1342-1347.
https://doi.org/10.1109/10.959330
[46]  Niskanen, J.P., Tarvainen, M.P., Ranta-Aho, P.O. and Karjalainen, P.A. (2004) Software for Advanced HRV Analysis. Computer Methods and Programs in Biomedicine, 76, 73-81.
https://doi.org/10.1016/j.cmpb.2004.03.004
[47]  Ribeiro, D., Fu, L., Carlos, L.D. and Cunha, J.P. (2011) A Novel Dry Active Biosignal Electrode Based on an Hybrid Organic-Inorganic Interface Material. IEEE Sensors Journal, 11, 2241-2245.
https://doi.org/10.1109/JSEN.2011.2114649
[48]  Xie, L., Yang, G., Mäntysalo, M., Xu, L.L., Jonsson, F. and Zheng, L.R. (2012) Heterogeneous Integration of Bio-Sensing System On-Chip and Printed Electronics. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2, 672-682.
[49]  Chandrakar, C. and Kowar, M.K. (2012) Denoising ECG Signals Using Adaptive Filter Algorithm. International Journal of Soft Computing and Engineering, 2, 120-123.
[50]  Luong, D.T., Thuan, N.D. and Hoang, D.H. (2015) Removal of Power Line Interference from Electrocardiograph (ECG) Using Proposed Adaptive Filter Algorithm. Global Journal of Computer Science and Technology, 15.

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