access icon openaccess Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device

Wearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantive studies of their performance when measuring the physiology of ambulatory patients. In this Letter, the authors investigate the reliability of the heart-rate (HR) sensor in an exemplar ‘wearable’ wrist-worn monitoring system (the Microsoft Band 2); their experiments quantify the propagation of error from (i) the photoplethysmogram (PPG) acquired by pulse oximetry, to (ii) estimation of HR, and (iii) subsequent calculation of HR variability (HRV) features. Their experiments confirm that motion artefacts account for the majority of this error, and show that the unreliable portions of HR data can be removed, using the accelerometer sensor from the wearable device. The experiments further show that acquired signals contain noise with substantial energy in the high-frequency band, and that this contributes to subsequent variability in standard HRV features often used in clinical practice. The authors finally show that the conventional use of long-duration windows of data is not needed to perform accurate estimation of time-domain HRV features.

Inspec keywords: photoplethysmography; medical signal processing; acceleration measurement; signal denoising; feature extraction; biomedical equipment; body sensor networks; accelerometers; oximetry; time-domain analysis; patient monitoring

Other keywords: pulse oximetry; wearable physiological-monitoring device; accelerometer sensor; ambulatory patients; exemplar wearable wrist-worn monitoring system; time-domain HRV features; long-duration windows; substantial energy; clinical practice; acquired signals; photoplethysmogram; HR variability features; error propagation profiling; noise; heart-rate sensor; HR estimation; PPG-HRV features; high-frequency band; consumer domain

Subjects: Biology and medical computing; Signal processing and detection; Optical and laser radiation (medical uses); Optical and laser radiation (biomedical imaging/measurement); Haemodynamics, pneumodynamics; Sensing devices and transducers; Digital signal processing; Sensing and detecting devices; Velocity, acceleration and rotation measurement; Wireless sensor networks; Velocity, acceleration and rotation measurement; Patient diagnostic methods and instrumentation

References

    1. 1)
      • 16. Lin, W.-H., Wu, D., Li, C., et al: ‘Comparison of heart rate variability from PPG with that from ECG’. The Int. Conf. Health Informatics, 2014, pp. 213215.
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
      • 13. Jeyhani, V., Mahdiani, S., Peltokangas, M., et al: ‘Comparison of HRV parameters derived from photoplethysmography and electrocardiography signals’. IEEE 2015 37th Annual Int. Conf. on Engineering in Medicine and Biology Society (EMBS), 2015, pp. 59525955.
    7. 7)
      • 3. Clifton, D.A., Pimentel, M.A.F., Niehaus, K., et al: ‘Intelligent electronic health systems’, in Eren, H., Webster, J.G. (Eds.): ‘Telemedicine and electronic medicine’ (CRC Press, 2015), pp. 7397.
    8. 8)
    9. 9)
    10. 10)
      • 8. Han, H., Kim, M.-J., Kim, J.: ‘Development of real-time motion artifact reduction algorithm for a wearable photoplethysmography’. IEEE 29th Annual Int. Conf. on Engineering in Medicine and Biology Society (EMBS, 2007), 2007, pp. 15381541.
    11. 11)
    12. 12)
      • 6. Orphanidou, C., Bonnici, T., Charlton, P., et al: ‘Signal quality indices for the electrocardiogram and photoplethysmogram: derivation and applications to wireless monitoring’, IEEE J. Biomed. Health Inf., 2015, 19, (3), pp. 832838.
    13. 13)
      • 15. Bolanos, M., Nazeran, H., Haltiwanger, E.: ‘Comparison of heart rate variability signal features derived from electrocardiography and photoplethysmography in healthy individuals’. IEEE 28th Annual Int. Conf. on Engineering in Medicine and Biology Society (EMBS'06, 2006), 2006, pp. 42894294.
    14. 14)
    15. 15)
      • 10. Lee, J., Matsumura, K., Yamakoshi, K.-i., et al: ‘Comparison between red, green and blue light reflection photoplethysmography for heart rate monitoring during motion’. IEEE 2013 35th Annual Int. Conf. on Engineering in Medicine and Biology Society (EMBS), 2013, pp. 17241727.
    16. 16)
    17. 17)
      • 20. Teng, X.F., Zhang, Y.T.: ‘Study on the peak interval variability of photoplethysmogtaphic signals’. 2003 IEEE Engineering in Medicine and Biology Society (EMBS) Asian-Pacific Conf. on Biomedical Engineering, 2003, pp. 140141.
    18. 18)
    19. 19)
      • 9. Lee, C.M., Zhang, Y.T.: ‘Reduction of motion artifacts from photoplethysmographic recordings using a wavelet denoising approach’. IEEE 2003, Medicine and Biology Society (EMBS), Asian-Pacific Conf. on Biomedical Engineering, 2003, pp. 194195.
    20. 20)
    21. 21)
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