Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable

Ryan McConville, Gareth Archer, Ian Craddock, Herman ter Horst, Robert Piechocki, James Pope, Raul Santos-Rodriguez

Research output: Contribution to conferenceConference Paper

Abstract

In this paper we study the prediction of heart rate from acceleration using a wrist worn wearable. Although existing photoplethysmography (PPG) heart rate sensors provide reliable measurements, they use considerably more energy than accelerometers and have a major impact on battery life of wearable devices. By using energy-efficient accelerometers to predict heart rate, significant energy savings can be made. Further, we are interested in understanding patient recovery after a heart rate intervention, where we expect a variation in heart rate over time. Therefore, we propose an online approach to tackle the concept as time passes. We evaluate the methods on approximately 4 weeks of free living data from three patients over a number of months. We show that our approach can achieve good predictive performance (e.g., 2.89 Mean Absolute Error) while using the PPG heart rate sensor infrequently (e.g., 20.25% of the samples).
Original languageEnglish
Publication statusPublished - 20 Aug 2018
EventKDD Workshop on Machine Learning for Medicine and Healthcare - London, United Kingdom
Duration: 20 Aug 2018 → …

Workshop

WorkshopKDD Workshop on Machine Learning for Medicine and Healthcare
CountryUnited Kingdom
CityLondon
Period20/08/18 → …

Structured keywords

  • Digital Health

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  • Projects

    EurValve

    Craddock, I. J.

    1/02/1631/01/19

    Project: Research, Parent

    SPHERE (EPSRC IRC)

    Craddock, I. J., Coyle, D. T., Flach, P. A., Kaleshi, D., Mirmehdi, M., Piechocki, R. J., Stark, B. H., Ascione, R., Ashburn, A. M., Burnett, M. E., Damen, D., Gooberman-Hill, R. J. S., Harwin, W. S., Hilton, G., Holderbaum, W., Holley, A. P., Manchester, V. A., Meller, B. J., Stack, E. & Gilchrist, I. D.

    1/10/1330/09/18

    Project: Research, Parent

    Cite this

    McConville, R., Archer, G., Craddock, I., ter Horst, H., Piechocki, R., Pope, J., & Santos-Rodriguez, R. (2018). Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable. Paper presented at KDD Workshop on Machine Learning for Medicine and Healthcare , London, United Kingdom.