Abstract
This paper proposes a motion artifact (MA) removal method in the photoplethysmographic (PPG) signal for accurate heart rate estimation. PPG signal is easy to acquire, but it is easily distorted by body movement. In this study, MA is analyzed using acceleration signals and removed in the PPG spectrum for accurate heart rate estimation. The proposed method progressively removes three-axis acceleration spectra in order of spectral power. The performance was confirmed by comparing heart rate estimation errors one case that MA was removed with another case that MA was not removed. After removing MA and applying two peak tracking methods in 12 data sets, the mean absolute error (MAE) of the beat per minute (BPM) is lower than conventional methods.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Allen, J.: Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28(3), R1–R39 (2007)
Zhang, Z., Pi, Z., Liu, B.: TROIKA: a general framework for heart rate monitoring using wrist-type photoplethysmographic signals during intensive physical exercise. IEEE Trans. Biomed. Eng. 62(2), 522–531 (2015)
Kim, B.S., Yoo, S.K.: Motion artifact reduction in photoplethysmography using independent component analysis. IEEE Trans. Biomed. Eng. 53(3), 566–568 (2006)
Lee, B., Han, J., Baek, H.J., Shin, J.H., Park, K.S., Yi, W.J.: Improved elimination of motion artifacts from a photoplehysmographic signal using a Kalman smoother with simultaneous accelerometry. Physiol. Meas. 31(12), 1585–1603 (2010)
Krishnan, R., Natarajan, B., Warren, S.: Two-stage approach for detection and reduction of motion artifacts in photoplethysmographic data. IEEE Trans. Biomed. Eng. 57(8), 1867–1876 (2010)
López, S.M., Giannetti, R., Dotor, M.L., Silveria, J.P., Golmayo, D., Miguel-Tobal, F., Bilbao, A., Galindo Canales, M., Martn Escudero, P., et al.: Heuristic algorithm for photoplethysmographic heart rate tracking during maximal exercise test. J. Med. Biol. Eng. 32(3), 181–188 (2012)
Sun, B., Zhang, Z.: Photoplethysmography-based heart rate monitoring using asymmetric least squares spectrum subtraction and Bayesian decision theory. IEEE Sens. J. 15(12), 7161–7168 (2015)
Ram, M., Madhav, K.V., Krishna, E.H., Komalla, N.R., Reddy, K.A.: A novel approach for motion artifact reduction in PPG signals based on AS-LMS adaptive Iter. IEEE Trans. Instrum. Meas. 61(5), 1445–1457 (2012)
Yousefi, R., Nourani, M., Ostadabbas, S., Panahi, I.: A motion-tolerant adaptive algorithm for wearable photoplethysmographic biosensors. IEEE J. Biomed. Health Inform. 18(2), 670–681 (2014)
Reddy, K.A., George, B., Kumar, V.J.: Use of fourier series analysis for motion artifact reduction and data compression of photoplethysmographic signals. IEEE Trans. Instrum. Meas. 58(5), 1706–1711 (2009)
Zhang, Z.: Undergraduate students compete in the IEEE signal processing cup: part 3. IEEE Signal Process. Mag. 32(6), 13–116 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
An, J.H., Song, H., Shin, HC. (2017). Progressive Motion Artifact Removal in PPG Signal for Accurate Heart Rate Estimation. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_92
Download citation
DOI: https://doi.org/10.1007/978-981-10-5041-1_92
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5040-4
Online ISBN: 978-981-10-5041-1
eBook Packages: EngineeringEngineering (R0)