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Non-invasive Analytics Based Smart System for Diabetes Monitoring

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Internet of Things (IoT) Technologies for HealthCare (HealthyIoT 2017)

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Abstract

Wearable devices have made it possible for health providers to monitor a patient’s health remotely using actuators, sensors and other mobile communication devices. Internet of Things for Medical Devices is poised to revolutionize the functioning of the healthcare industry by providing an environment where the patient data is transmitted via a gateway onto a secure cloud based platforms for storage, aggregation and analytics. This paper proposes new set of wearable devices - a smart neck band, smart wrist band and a pair of smart socks - to continuously monitor the condition of diabetic patients. These devices consist of different sensors working in tandem form a network that reports food intake, heart rate, skin moisture, ambient temperature, walking patterns and weight gain/loss. The devices with the aid of controllers send all the sensor values as a packet via Bluetooth to the Mobile App. With the help of Machine Learning algorithm, we have predicted the change in patient status and alert them.

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Author information

Authors and Affiliations

  1. Ericsson Research, Ericsson India Global Services Pvt. Ltd., Chennai, India

    M. Saravanan

  2. School of Electronics Engineering, VIT University, Chennai, India

    R. Shubha

Authors
  1. M. Saravanan
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  2. R. Shubha
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Corresponding author

Correspondence to M. Saravanan .

Editor information

Editors and Affiliations

  1. Mälardalen University, VästerĂ¥s, Sweden

    Mobyen Uddin Ahmed

  2. Mälardalen University, VästerĂ¥s, Sweden

    Shahina Begum

  3. University of Angers, Angers, France

    Jean-Baptiste Fasquel

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Saravanan, M., Shubha, R. (2018). Non-invasive Analytics Based Smart System for Diabetes Monitoring. In: Ahmed, M., Begum, S., Fasquel, JB. (eds) Internet of Things (IoT) Technologies for HealthCare. HealthyIoT 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 225. Springer, Cham. https://doi.org/10.1007/978-3-319-76213-5_13

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  • DOI: https://doi.org/10.1007/978-3-319-76213-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76212-8

  • Online ISBN: 978-3-319-76213-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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