• DocumentCode
    3128545
  • Title

    Comparison of Heart Rate Variability Signal Features Derived from Electrocardiography and Photoplethysmography in Healthy Individuals

  • Author

    Bolanos, M. ; Nazeran, H. ; Haltiwanger, E.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Texas Univ., El Paso, TX
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    4289
  • Lastpage
    4294
  • Abstract
    The heart rate variability (HRV) signal is indicative of autonomic regulation of the heart rate (HR). It could be used as a noninvasive marker in monitoring the physiological state of an individual. Currently, the primary method of deriving the HRV signal is to acquire the electrocardiogram (ECG) signal, apply appropriate QRS detection algorithms to locate the R wave and its peak, find the RR intervals, and perform suitable interpolation and resampling to produce a uniformly sampled tachogram. This process could sometimes result in errors in the HRV signal due to drift, electromagnetic and biologic interference, and the complex morphology of the ECG signal. The photoplethysmographic (PPG) signal has the potential to eliminate the problems with the ECG signal to derive the HRV signal. To investigate this point, a PDA-based system was developed to simultaneously record ECG and PPG signals to facilitate accurately controlled sampling and recording durations. Two healthy young volunteers participated in this pilot study to evaluate the applicability of our approach. To improve data quality, ECG and PPG recordings were acquired three times/subject. A comparison between different features of the HRV signals derived from both methods was performed to test the validity of using PPG signals in HRV analysis. We used autoregressive (AR) modeling, Poincare´ plots, cross correlation, standard deviation, arithmetic mean, skewness, kurtosis, and approximate entropy (ApEn) to derive and compare different measures from both ECG and PPG signals. This study demonstrated that our PDA-based system was a convenient and reliable means for acquisition of PPG-derived and ECG-derived HRV signals. The excellent agreement between different measures of HRV signals acquired from both methods provides potential support for the idea of using PPGs instead of ECGs in HRV signal derivation and analysis in ambulatory cardiac monitoring of healthy individuals
  • Keywords
    Poincare mapping; autoregressive processes; correlation methods; electrocardiography; plethysmography; ECG signal; Poincare plots; QRS detection algorithms; ambulatory cardiac monitoring; approximate entropy; autonomic regulation; autoregressive modeling; biologic interference; cross correlation; electrocardiography; electromagnetic interference; heart rate variability signal; kurtosis; noninvasive marker; photoplethysmography; physiological state monitoring; skewness; tachogram; Biomedical monitoring; Detection algorithms; Electrocardiography; Electromagnetic interference; Heart rate; Heart rate variability; Interpolation; Morphology; Signal analysis; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260607
  • Filename
    4462749