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Data Reliability and Quality in Body Area Networks for Diabetes Monitoring

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Body Area Network Challenges and Solutions

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

In wireless body area network (WBAN), data captured from different types of wearable, invasive, minimally invasive, or non-invasive sensors have the immense potential to contribute for real-time decisions and effective healthcare services for better diabetes monitoring. Low quality data can be misleading and thus result in inaccurate diagnosis, ineffective health decision-making, and even loss of lives. High data reliability and quality is of paramount importance in WBAN to ensure wide systems’ adoption and technological acceptance. Based on existing literature on WBAN systems, sensor technologies and data quality (DQ) dimensions, a framework is proposed to ensure high data quality and reliability in WBANs for effective and real-time diabetes monitoring. The framework is composed of a set of DQ dimensions to verify that the information gleaned from sensors, processed, and delivered are of high quality so that diabetes patients and healthcare professionals are able to make reliable, high-precision diagnoses, and real-time treatment decisions. Potential research directions are pointed out for further optimization of data quality and reliability in Body Area Network (BAN) on the sensor level, network level, and human-centric level.

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Authors and Affiliations

  1. Department of Information Technology, Curtin Mauritius, Moka, Mauritius

    Geshwaree Huzooree

  2. Department of Digital Technologies, University of Mauritius, Reduit, Mauritius

    Kavi Kumar Khedo

  3. Central Health Laboratory, Victoria Hospital, Ministry of Health & Quality of Life, Candos, Mauritius

    Noorjehan Joonas

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  1. Geshwaree Huzooree
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  2. Kavi Kumar Khedo
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  3. Noorjehan Joonas
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Correspondence to Geshwaree Huzooree .

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  1. Department of ECE, Sri Krishna College of Technology, Coimbatore, TN, India

    R. Maheswar

  2. Vel Tech Rangarajan Dr. Sagunthala R&D, Institute of Science and Technology, Chennai, TN, India

    G. R. Kanagachidambaresan

  3. Department of ECE, SSN College of Engineering, Chennai, TN, India

    R. Jayaparvathy

  4. Indian Institute of Information Technology and Management - Kerala (IIITM-K), Trivandrum, KL, India

    Sabu M. Thampi

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Huzooree, G., Khedo, K.K., Joonas, N. (2019). Data Reliability and Quality in Body Area Networks for Diabetes Monitoring. In: Maheswar, R., Kanagachidambaresan, G., Jayaparvathy, R., Thampi, S. (eds) Body Area Network Challenges and Solutions. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-00865-9_4

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