Improving Pulse Rate Measurements During Random Motion Using a Wearable Multichannel Reflectance Photoplethysmograph

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2016 Mar 10

PMID 26959034

Citations 15

Authors

Kristen M Warren

Joshua R Harvey

Ki H Chon

Yitzhak Mendelson

Affiliations

Soon will be listed here.

Abstract

Photoplethysmographic (PPG) waveforms are used to acquire pulse rate (PR) measurements from pulsatile arterial blood volume. PPG waveforms are highly susceptible to motion artifacts (MA), limiting the implementation of PR measurements in mobile physiological monitoring devices. Previous studies have shown that multichannel photoplethysmograms can successfully acquire diverse signal information during simple, repetitive motion, leading to differences in motion tolerance across channels. In this paper, we investigate the performance of a custom-built multichannel forehead-mounted photoplethysmographic sensor under a variety of intense motion artifacts. We introduce an advanced multichannel template-matching algorithm that chooses the channel with the least motion artifact to calculate PR for each time instant. We show that for a wide variety of random motion, channels respond differently to motion artifacts, and the multichannel estimate outperforms single-channel estimates in terms of motion tolerance, signal quality, and PR errors. We have acquired 31 data sets consisting of PPG waveforms corrupted by random motion and show that the accuracy of PR measurements achieved was increased by up to 2.7 bpm when the multichannel-switching algorithm was compared to individual channels. The percentage of PR measurements with error ≤ 5 bpm during motion increased by 18.9% when the multichannel switching algorithm was compared to the mean PR from all channels. Moreover, our algorithm enables automatic selection of the best signal fidelity channel at each time point among the multichannel PPG data.

Citing Articles

Performance Assessment of Heartbeat Detection Algorithms on Photoplethysmograph and Functional NearInfrared Spectroscopy Signals.

Bizzego A, Esposito G Sensors (Basel). 2023; 23(7).

PMID: 37050728 PMC: 10099230. DOI: 10.3390/s23073668.

Edge-Enabled Heart Rate Estimation from Multisensor PPG Signals.

Chen X, Zhu F, Zhao H J Healthc Eng. 2023; 2023:4682760.

PMID: 36875750 PMC: 9977552. DOI: 10.1155/2023/4682760.

A Wearable and Real-Time Pulse Wave Monitoring System Based on a Flexible Compound Sensor.

Kang X, Zhang J, Shao Z, Wang G, Geng X, Zhang Y Biosensors (Basel). 2022; 12(2).

PMID: 35200393 PMC: 8870208. DOI: 10.3390/bios12020133.

Comparison of Wearable and Clinical Devices for Acquisition of Peripheral Nervous System Signals.

Bizzego A, Gabrieli G, Furlanello C, Esposito G Sensors (Basel). 2020; 20(23).

PMID: 33260880 PMC: 7730565. DOI: 10.3390/s20236778.

Motion Artifact Reduction in Wearable Photoplethysmography Based on Multi-Channel Sensors with Multiple Wavelengths.

Lee J, Kim M, Park H, Kim I Sensors (Basel). 2020; 20(5).

PMID: 32182772 PMC: 7085621. DOI: 10.3390/s20051493.

References

Orphanidou C, Bonnici T, Charlton P, Clifton D, Vallance D, Tarassenko L . Signal-quality indices for the electrocardiogram and photoplethysmogram: derivation and applications to wireless monitoring. IEEE J Biomed Health Inform. 2014; 19(3):832-8. DOI: 10.1109/JBHI.2014.2338351. View

Mendelson Y, Ochs B . Noninvasive pulse oximetry utilizing skin reflectance photoplethysmography. IEEE Trans Biomed Eng. 1988; 35(10):798-805. DOI: 10.1109/10.7286. View

Wang L, Lo B, Yang G . Multichannel Reflective PPG Earpiece Sensor With Passive Motion Cancellation. IEEE Trans Biomed Circuits Syst. 2013; 1(4):235-41. DOI: 10.1109/TBCAS.2007.910900. View

Krishnan R, Natarajan B, Warren S . Two-stage approach for detection and reduction of motion artifacts in photoplethysmographic data. IEEE Trans Biomed Eng. 2010; 57(8):1867-76. DOI: 10.1109/TBME.2009.2039568. View

Hong Enriquez R, Sautie Castellanos M, Falcon Rodriguez J, Caceres J . Analysis of the photoplethysmographic signal by means of the decomposition in principal components. Physiol Meas. 2002; 23(3):N17-29. DOI: 10.1088/0967-3334/23/3/402. View

Foo J, Wilson S . A computational system to optimise noise rejection in photoplethysmography signals during motion or poor perfusion states. Med Biol Eng Comput. 2006; 44(1-2):140-5. DOI: 10.1007/s11517-005-0008-y. View

Li K, Warren S . A wireless reflectance pulse oximeter with digital baseline control for unfiltered photoplethysmograms. IEEE Trans Biomed Circuits Syst. 2013; 6(3):269-78. DOI: 10.1109/TBCAS.2011.2167717. View

Wijshoff R, Mischi M, Veen J, van der Lee A, Aarts R . Reducing motion artifacts in photoplethysmograms by using relative sensor motion: phantom study. J Biomed Opt. 2012; 17(11):117007. DOI: 10.1117/1.JBO.17.11.117007. View

Kim B, Yoo S . Motion artifact reduction in photoplethysmography using independent component analysis. IEEE Trans Biomed Eng. 2006; 53(3):566-8. DOI: 10.1109/TBME.2005.869784. View

10.

Asada H, Jiang H, Gibbs P . Active noise cancellation using MEMS accelerometers for motion-tolerant wearable bio-sensors. Conf Proc IEEE Eng Med Biol Soc. 2007; 2004:2157-60. DOI: 10.1109/IEMBS.2004.1403631. View

11.

Shimazaki T, Hara S, Okuhata H, Nakamura H, Kawabata T . Cancellation of motion artifact induced by exercise for PPG-based heart rate sensing. Annu Int Conf IEEE Eng Med Biol Soc. 2015; 2014:3216-9. DOI: 10.1109/EMBC.2014.6944307. View

12.

Yousefi R, Nourani M, Ostadabbas S, Panahi I . A motion-tolerant adaptive algorithm for wearable photoplethysmographic biosensors. IEEE J Biomed Health Inform. 2014; 18(2):670-81. DOI: 10.1109/JBHI.2013.2264358. View

13.

Salehizadeh S, Dao D, Chong J, McManus D, Darling C, Mendelson Y . Photoplethysmograph signal reconstruction based on a novel motion artifact detection-reduction approach. Part II: Motion and noise artifact removal. Ann Biomed Eng. 2014; 42(11):2251-63. DOI: 10.1007/s10439-014-1030-8. View

14.

Li K, Warren S, Natarajan B . Onboard tagging for real-time quality assessment of photoplethysmograms acquired by a wireless reflectance pulse oximeter. IEEE Trans Biomed Circuits Syst. 2013; 6(1):54-63. DOI: 10.1109/TBCAS.2011.2157822. View

15.

Mannheimer P . The light-tissue interaction of pulse oximetry. Anesth Analg. 2007; 105(6 Suppl):S10-S17. DOI: 10.1213/01.ane.0000269522.84942.54. View

16.

Petterson M, Begnoche V, Graybeal J . The effect of motion on pulse oximetry and its clinical significance. Anesth Analg. 2007; 105(6 Suppl):S78-S84. DOI: 10.1213/01.ane.0000278134.47777.a5. View

17.

Peng F, Zhang Z, Gou X, Liu H, Wang W . Motion artifact removal from photoplethysmographic signals by combining temporally constrained independent component analysis and adaptive filter. Biomed Eng Online. 2014; 13:50. PMC: 4021027. DOI: 10.1186/1475-925X-13-50. View

18.

Chong J, Dao D, Salehizadeh S, McManus D, Darling C, Chon K . Photoplethysmograph signal reconstruction based on a novel hybrid motion artifact detection-reduction approach. Part I: Motion and noise artifact detection. Ann Biomed Eng. 2014; 42(11):2238-50. DOI: 10.1007/s10439-014-1080-y. View

19.

Lee B, Han J, Baek H, Shin J, Park K, Yi W . Improved elimination of motion artifacts from a photoplethysmographic signal using a Kalman smoother with simultaneous accelerometry. Physiol Meas. 2010; 31(12):1585-603. DOI: 10.1088/0967-3334/31/12/003. View

20.

Patterson J, Yang G . Ratiometric artifact reduction in low power reflective photoplethysmography. IEEE Trans Biomed Circuits Syst. 2013; 5(4):330-8. DOI: 10.1109/TBCAS.2011.2161304. View