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Enhancing the Accuracy of Finger-Based Heart Rate Estimation During At-Home Biofeedback Therapy with Smartphone

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Advanced Technologies, Systems, and Applications VIII (IAT 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 644))

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Abstract

Smartphone-based heart rate monitoring is a promising biofeedback therapy tool, but its accuracy is frequently limited by motion artifacts and incorrect finger placement. We present a novel calibration procedure in this study that improves the accuracy of smartphone-based heart rate estimation during biofeedback therapy. Advanced signal processing techniques are used to minimize motion artifacts and optimize finger placement, resulting in a significant reduction in heart rate estimation errors and an increase in correlation coefficients with ground truth measurements. Our findings suggest that, if the calibration procedure is followed correctly, smartphone-based heart rate monitoring can be a reliable and accessible tool for biofeedback therapy in clinical and home-based settings. The proposed method could help improve the effectiveness of biofeedback therapy by allowing patients to more accurately and precisely regulate their physiological states and improve their overall health. As a consequence, an improved calibration procedure has the potential to contribute to the wider adoption of smartphone-based biofeedback therapy, thereby improving access to this effective technique for a broader population.

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Authors and Affiliations

  1. Faculty of Electrical Engineering, University of Tuzla, Tuzla, Bosnia and Herzegovina

    Alma Šećerbegović, Asmir Gogić & Aljo Mujčić

Authors
  1. Alma Šećerbegović
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  2. Asmir Gogić
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  3. Aljo Mujčić
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Corresponding author

Correspondence to Alma Šećerbegović .

Editor information

Editors and Affiliations

  1. University of Sarajevo-Faculty of Civil Engineering, Sarajevo, Bosnia and Herzegovina

    Naida Ademović

  2. International Burch University, Francuske revolucije bb, Ilidža, Bosnia and Herzegovina

    Jasmin Kevrić

  3. University of Utah, Salt Lake City, UT, USA

    Zlatan Akšamija

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Šećerbegović, A., Gogić, A., Mujčić, A. (2023). Enhancing the Accuracy of Finger-Based Heart Rate Estimation During At-Home Biofeedback Therapy with Smartphone. In: Ademović, N., Kevrić, J., Akšamija, Z. (eds) Advanced Technologies, Systems, and Applications VIII. IAT 2023. Lecture Notes in Networks and Systems, vol 644. Springer, Cham. https://doi.org/10.1007/978-3-031-43056-5_31

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