Implanted medical devices as future of wireless healthcare monitoring: Investigation and performance evaluation using novel numerical modeling
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Authors: Akbar, M.S., Yu, H. and Cang, S.
Journal: 2016 22nd International Conference on Automation and Computing, ICAC 2016: Tackling the New Challenges in Automation and Computing
© 2016 Chinese Automation and Computing Society. The patient monitoring through implant medical devices under medical implant communication service (MICS) band has significantly increased due to growing healthcare expenses, an aging population, and successful deployment of wearable home-based medical monitoring in telemedicine. Recent literature lacks the performance evaluation mechanisms and discussion of MICS band in terms of quality of service (QoS); whereas, every implantable device has specified QoS requirements in terms of delay and throughput. This issue raises a serious concern while deploying implant devices that either the communications protocols are capable of providing specified QoS for this device or not. Moreover, MICS band works under two modes i.e., connected and unconnected, the decision which band is suitable for which type of application still needs more discussion. In this paper, we address the issues regarding appropriate performance evaluation model of MICS and selection of suitable mode of MICS according to application requirement. First, we discuss about the issues of different layers of MICS band including application, physical and MAC layer with respect to deployment challenges. Second, we develop a numerical model for the performance evaluation of the MICS band under connected and unconnected modes. This model computes the estimated communication delay and provides maximum throughput (MT) values for the transmission of the data frame under mentioned band modes. For the best of our knowledge, the proposed numerical model for the estimation of total end-to-end delay and MT is the first numerical model for MICS band. At the end, we provide the comparative analysis of the connected and unconnected modes which helps the healthcare professionals to choose an appropriate mode for different implant devices.