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HeartSense: Estimating Heart Rate from Smartphone Photoplethysmogram Using Adaptive Filter and Interpolation

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Abstract

In recent days, physiological sensing using smartphones is gaining attention everywhere for preventive health-care. In this paper, we propose a 2-stage approach for robust heart rate (HR) calculation from photoplethysmogram (PPG) signal, captured using smartphones. Firstly, Normalized Least Mean Square (NLMS) based adaptive filter is used to clean up the noisy PPG signal. Then, heart rate is calculated from the frequency spectrum, which is further fine-tuned using different interpolation techniques. Experimental results, show that the overall HR calculation improves significantly due to the proposed 2-stage approach.

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Notes

  1. 1.

    http://itee.uq.edu.au/~davel/uqvitalsignsdataset/download.html.

  2. 2.

    At 30 Hz, 512 samples amount to  17 sec video.

  3. 3.

    www.pulseoximeter.org/cms50d.html.

References

  1. Allen, J.: Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28, R1–R39 (2007)

    Article  Google Scholar 

  2. Candan, C.: A method for fine resolution frequency estimation from three dft samples. IEEE Signal Process. Lett. 18(6), 351–354 (2011)

    Article  Google Scholar 

  3. Ghose, A., Sinha, P., Bhaumik, C., Sinha, A., Agrawal, A., Choudhury, A.D.: Ubiheld: ubiquitous healthcare monitoring system for elderly and chronic patients. In: Proceedings of the 2013 ACM conference on Pervasive and Ubiquitous Computing Adjunct Publication, pp. 1255–1264, ACM (2013)

    Google Scholar 

  4. Hayes, M.H.: Statistical Digital Signal Processing and Modeling. John Wiley & Sons, New York (2009)

    Google Scholar 

  5. Jacobsen, E., Kootsookos, P.: Fast, accurate frequency estimators. IEEE Signal Process. Mag. 24(3), 123–125 (2007)

    Article  Google Scholar 

  6. Kurylyak, Y., Lamonaca, F., Grimaldi, D.: Smartphone Based Photoplethysmogram Measurement. River Publishers, Aalborg (2012)

    Google Scholar 

  7. Pal, A., Sinha, A., Choudhury, A., Chattopadhyay, T., Visvanathan, A.: A robust heart rate detection using smart-phone video. In: MobileHealth Workshop in MobiHoc (2013)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Innovation Lab, Tata Consultancy Services Ltd., Kolkata, India

    Anirban Dutta Choudhury, Aditi Misra, Arpan Pal, Rohan Banerjee, Avik Ghose & Aishwarya Visvanathan

Authors
  1. Anirban Dutta Choudhury
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  2. Aditi Misra
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  3. Arpan Pal
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  4. Rohan Banerjee
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  5. Avik Ghose
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  6. Aishwarya Visvanathan
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Corresponding author

Correspondence to Rohan Banerjee .

Editor information

Editors and Affiliations

  1. CREATE-NET, Trento, Italy

    Raffaele Giaffreda

  2. University of Trento, Trento, Italy

    Radu-Laurentiu Vieriu

  3. Management Consultant, Edna Pasher Ph.D & Associates, Tel Aviv, Israel

    Edna Pasher

  4. Management Consultant, Edna Pasher Ph.D & Associates, Tel Aviv, Israel

    Gabriel Bendersky

  5. University of Applied Sciences, Institute of Information Systems, Delémont, Switzerland

    Antonio J. Jara

  6. University of Beira Interior, Covilhã, Portugal

    Joel J.P.C. Rodrigues

  7. IBM Research Laboratory, Haifa, Israel

    Eliezer Dekel

  8. IBM Research, Haifa, Israel

    Benny Mandler

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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Choudhury, A.D., Misra, A., Pal, A., Banerjee, R., Ghose, A., Visvanathan, A. (2015). HeartSense: Estimating Heart Rate from Smartphone Photoplethysmogram Using Adaptive Filter and Interpolation. In: Giaffreda, R., et al. Internet of Things. User-Centric IoT. IoT360 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-319-19656-5_29

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  • DOI: https://doi.org/10.1007/978-3-319-19656-5_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19655-8

  • Online ISBN: 978-3-319-19656-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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