Evaluation of MAC Protocols for Vital Sign Monitoring within Smart Home Environment

One of the appealing applications of smart home is remote monitoring of vital signs, such as heart and respiratory, which has gained more attention during the last two decades. The recent developments in IoT, sensing devices, and smart technologies increased the demand for such technology due to the need for devices that can continuously monitor physiological signals and offer further analysis and interpretations. Real-time monitoring systems record, measure, and monitor the vital sign activity for several reasons, such as early detection of heart problems, patient watching and athlete’s issues, This requires the use of MAC (medium access control) protocol which helps in the identification of several issues in the operation of medical sensors, such as traffic identification and sensing, collision detection, and the availability of free channels. In this paper, a fuzzy analytic hierarchy process (AHP)-based algorithm is proposed for the performance analysis of several MAC protocols that are intended for monitoring medical signal in the human body, such as vital signals. Five different protocols were analyzed according to several performance metrics using a quantitative ranking based on the proposed algorithm. The work concludes by suggesting a new protocol that combines the two most efficient ones and taking advantage of the features of each.

[1]  Olivier Berder,et al.  TAD-MAC: Traffic-Aware Dynamic MAC Protocol for Wireless Body Area Sensor Networks , 2012, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[2]  Ryuji Kohno,et al.  Reservation-Based Dynamic TDMA Protocol for Medical Body Area Networks , 2009, IEICE Trans. Commun..

[3]  Yong Liang Guan,et al.  A Comprehensive Study of IoT and WSN MAC Protocols: Research Issues, Challenges and Opportunities , 2018, IEEE Access.

[4]  Pijush Kanti Dutta Pramanik,et al.  WBAN: Driving e-healthcare Beyond Telemedicine to Remote Health Monitoring , 2019, Telemedicine Technologies.

[5]  Jindong Tan,et al.  Heartbeat-driven medium-access control for body sensor networks , 2010, IEEE Trans. Inf. Technol. Biomed..

[6]  Omer Gurewitz,et al.  RI-MAC: a receiver-initiated asynchronous duty cycle MAC protocol for dynamic traffic loads in wireless sensor networks , 2008, SenSys '08.

[7]  C. Kahraman Multi-Criteria Decision Making Methods and Fuzzy Sets , 2008 .

[8]  Gerald Albaum,et al.  The Likert Scale Revisited , 1997 .

[9]  Jihong Liu,et al.  Survey of Wearable EEG and ECG Acquisition Technologies for Body Area Network , 2018, IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society.

[10]  Zahoor Ali Khan,et al.  Energy-aware Peering Routing Protocol for indoor hospital Body Area Network Communication , 2012, ANT/MobiWIS.

[11]  Minglei Shu,et al.  A MAC Protocol for Medical Monitoring Applications of Wireless Body Area Networks , 2015, Sensors.

[12]  Daji Qiao,et al.  LB-MAC: A Lifetime-Balanced MAC Protocol for Sensor Networks , 2012, WASA.

[13]  Partha Pratim Ray A survey on Internet of Things architectures , 2018, J. King Saud Univ. Comput. Inf. Sci..

[14]  C. Hwang,et al.  Fuzzy Multiple Attribute Decision Making Methods , 1992 .

[15]  Zhibo Pang,et al.  Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges , 2017, Sensors.

[16]  Saurabh Pal,et al.  Automated Real-Time Processing of Single Lead Electrocardiogram for Simultaneous Heart Rate and Respiratory Rate Monitoring , 2017 .

[17]  Nilanjan Dey,et al.  Developing residential wireless sensor networks for ECG healthcare monitoring , 2017, IEEE Transactions on Consumer Electronics.

[18]  Andreas Terzis,et al.  A-MAC , 2012, ACM Trans. Sens. Networks.

[19]  Mohamed F. Younis,et al.  Interference Mitigation Techniques in Wireless Body Area Networks , 2019, Mission-Oriented Sensor Networks and Systems.

[20]  Siti Asilah Yah,et al.  Energy-Efficient Remote Healthcare Monitoring Using IoT: A Review of Trends and Challenges , 2016, ICC 2016.

[21]  Ricardo A. L. Rabêlo,et al.  MAC Layer Protocols for Internet of Things: A Survey , 2019, Future Internet.

[22]  R. Jegan,et al.  Sensor Based Smart Real Time Monitoring of Patients Conditions Using Wireless Protocol , 2018, Int. J. E Health Medical Commun..

[23]  Amjad Gawanmeh,et al.  Analysis of MAC Protocols for Real-Time Monitoring of Heart and Respiratory Signals , 2018, 2018 IEEE 43rd Conference on Local Computer Networks Workshops (LCN Workshops).

[24]  Kyung Sup Kwak,et al.  Performance Analysis of Preamble-Based TDMA Protocol for Wireless Body Area Network , 2008 .

[25]  Zeashan Hameed Khan,et al.  Artificial Pancreas Coupled Vital Signs Monitoring for Improved Patient Safety , 2013 .

[26]  Rakesh Kumar,et al.  Technological aspects of WBANs for health monitoring: a comprehensive review , 2019, Wirel. Networks.

[27]  Robert Simon Sherratt,et al.  A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments , 2016, Sensors.

[28]  Christoph Lenzen,et al.  PulseSync: An Efficient and Scalable Clock Synchronization Protocol , 2015, IEEE/ACM Transactions on Networking.

[29]  Mohamed F. Younis,et al.  Energy-aware Gateway Selection for Increasing the Lifetime of Wireless Body Area Sensor Networks , 2012, Journal of Medical Systems.

[30]  Eryk Dutkiewicz,et al.  BodyMAC: Energy efficient TDMA-based MAC protocol for Wireless Body Area Networks , 2009, 2009 9th International Symposium on Communications and Information Technology.

[31]  Javier Del Ser,et al.  Online heart monitoring systems on the internet of health things environments: A survey, a reference model and an outlook , 2020, Inf. Fusion.

[32]  Amy M. Lieberman,et al.  The ASL-CDI 2.0: An updated, normed adaptation of the MacArthur Bates Communicative Development Inventory for American Sign Language , 2020, Behavior Research Methods.

[33]  David A. Clifton,et al.  Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review , 2017, IEEE Reviews in Biomedical Engineering.

[34]  Kris Steenhaut,et al.  Review and Classification of Multichannel MAC Protocols for Low-Power and Lossy Networks , 2017, IEEE Access.

[35]  Miriam M. R. Vollenbroek-Hutten,et al.  A standardized validity assessment protocol for physiological signals from wearable technology: Methodological underpinnings and an application to the E4 biosensor , 2019, Behavior research methods.