Energy Efficient Heart Rate Sensing using a Painted Electrode ECG Wearable

Sammy Krachunov, Christopher Beach, Alexander J. Casson, James Pope, Xenofon Fafoutis, Robert Piechocki, Ian Craddock

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

16 Citations (Scopus)
333 Downloads (Pure)

Abstract

Many countries are facing burdens on their health care systems due to ageing populations. A promising strategy to address the problem is to allow selected people to remain in their homes and be monitored using recent advances in wearable devices, saving in-hospital resources. With respect to heart monitoring, wearable devices to date have principally used optical techniques by shining light through the skin. However, these techniques are severely hampered by motion artifacts and are limited to heart rate detection. Further, these optical devices consume a large amount of power in order to receive a sufficient signal, resulting in the need for frequent battery recharging. To address these shortcomings we present a new wrist ECG wearable that is similar to the clinical approach for heart monitoring. Our device weighs less than 30 g, and is ultra low power, extending the battery lifetime to over a month to make the device more appropriate for in-home health care applications. The device uses two electrodes activated by the user to measure the voltage across the wrists. The electrodes are made from a flexible ink and can be painted on to the device casing, making it adaptable for different shapes and users. In this paper we show how the ECG sensor can be integrated into an existing IoT wearable and compare the device's accuracy against other common commercial devices.
Original languageEnglish
Title of host publication2017 Global Internet of Things Summit (GIoTS 2017)
Subtitle of host publicationProceedings of a meeting held 6-9 June 2017, Geneva, Switzerland
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages297-302
Number of pages6
ISBN (Electronic)9781509058730
ISBN (Print)9781509058747
DOIs
Publication statusPublished - Aug 2017

Structured keywords

  • Digital Health

Keywords

  • Digital Health

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