Literature DB >> 17946618

Comparison of heart rate variability signal features derived from electrocardiography and photoplethysmography in healthy individuals.

M Bolanos1, H Nazeran, E Haltiwanger.   

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.

Mesh:

Year:  2006        PMID: 17946618     DOI: 10.1109/IEMBS.2006.260607

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  19 in total

1.  Comparison of foot finding methods for deriving instantaneous pulse rates from photoplethysmographic signals.

Authors:  Mathilde C Hemon; Justin P Phillips
Journal:  J Clin Monit Comput       Date:  2015-04-24       Impact factor: 2.502

2.  A Survey of Challenges and Opportunities in Sensing and Analytics for Risk Factors of Cardiovascular Disorders.

Authors:  Nathan C Hurley; Erica S Spatz; Harlan M Krumholz; Roozbeh Jafari; Bobak J Mortazavi
Journal:  ACM Trans Comput Healthc       Date:  2020-12-30

3.  Analysis of heart rate variability during auditory stimulation periods in patients with schizophrenia.

Authors:  Saime Akdemir Akar; Sadık Kara; Fatma Latifoğlu; Vedat Bilgiç
Journal:  J Clin Monit Comput       Date:  2014-05-16       Impact factor: 2.502

4.  Comparison between Electrocardiographic and Earlobe Pulse Photoplethysmographic Detection for Evaluating Heart Rate Variability in Healthy Subjects in Short- and Long-Term Recordings.

Authors:  Basilio Vescio; Maria Salsone; Antonio Gambardella; Aldo Quattrone
Journal:  Sensors (Basel)       Date:  2018-03-13       Impact factor: 3.576

5.  An Autonomic Network: Synchrony Between Slow Rhythms of Pulse and Brain Resting State Is Associated with Personality and Emotions.

Authors:  Ehsan Shokri-Kojori; Dardo Tomasi; Nora D Volkow
Journal:  Cereb Cortex       Date:  2018-09-01       Impact factor: 5.357

6.  Design Rationale and Performance Evaluation of the Wavelet Health Wristband: Benchtop Validation of a Wrist-Worn Physiological Signal Recorder.

Authors:  Onur Dur; Reinier van Mourik; Colleen Rhoades; Man Suen Ng; Ragwa Elsayed; Maulik D Majmudar
Journal:  JMIR Mhealth Uhealth       Date:  2018-10-16       Impact factor: 4.773

7.  How Laboratory Experiments Can Be Exploited forMonitoring Stress in the Wild: A Bridge BetweenLaboratory and Daily Life.

Authors:  Yekta Said Can; Dilara Gokay; Dilruba Reyyan Kılıç; Deniz Ekiz; Niaz Chalabianloo; Cem Ersoy
Journal:  Sensors (Basel)       Date:  2020-02-04       Impact factor: 3.576

8.  Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device.

Authors:  Davide Morelli; Leonardo Bartoloni; Michele Colombo; David Plans; David A Clifton
Journal:  Healthc Technol Lett       Date:  2018-02-12

9.  Electrocardiogram Sampling Frequency Range Acceptable for Heart Rate Variability Analysis.

Authors:  Ohhwan Kwon; Jinwoo Jeong; Hyung Bin Kim; In Ho Kwon; Song Yi Park; Ji Eun Kim; Yuri Choi
Journal:  Healthc Inform Res       Date:  2018-07-31

10.  Physical Workload Tracking Using Human Activity Recognition with Wearable Devices.

Authors:  Jose Manjarres; Pedro Narvaez; Kelly Gasser; Winston Percybrooks; Mauricio Pardo
Journal:  Sensors (Basel)       Date:  2019-12-19       Impact factor: 3.576

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.