Related Experiment Video
Updated: Jan 20, 2026
Acquisition and Analysis of an ECG electrocardiography Signal
Published on: April 30, 2023
Comparison of multiple cardiac signal acquisition technologies for heart rate variability analysis
P Charlier1,2, M Cabon1, C Herman1
1INSERM, CHU Lille, CIC-IT 1403, 59000, Lille, France.
Insights
This study evaluated multiple sensors for heart rate variability (HRV) analysis. Piezoplethysmocardiography showed the best agreement with electrocardiography for HRV assessment.
Area of Science:
- Biomedical Engineering
- Physiology
- Cardiovascular Research
Background:
- Heart rate variability (HRV) analysis is crucial for assessing autonomic nervous system regulation.
- Existing HRV methods require specific cardiac beat intervals, necessitating reliable data acquisition.
- Various technologies like ECG, PCG, and seismocardiography record cardiac activity, but their HRV analysis capabilities need further validation.
Purpose of the Study:
- To develop a multi-sensor technology for simultaneous cardiac activity monitoring.
- To investigate the feasibility of using diverse sensors (ECG, PCG, seismocardiography, PPG, piezoplethysmocardiography) for HRV analysis.
- To compare the agreement of different sensors with ECG for HRV parameter computation.
Main Methods:
- Developed a novel system for simultaneous recording of ECG, PCG, seismocardiography, PPG, and piezoplethysmocardiography.
- Collected data during postural changes to induce physiological variations.
- Computed and analyzed various HRV parameters from each sensor's data.
Main Results:
- Most sensors were adequate for mean heart rate (HR) calculation.
- Significant variations in agreement were observed among sensors for different HRV analysis methods.
- Piezoplethysmocardiography demonstrated superior agreement with ECG compared to other sensors for most HRV indexes.
Conclusions:
- While several sensors can measure mean HR, their suitability for comprehensive HRV analysis varies.
- Piezoplethysmocardiography emerges as a promising non-invasive method for reliable HRV assessment, showing strong correlation with ECG.
- Further research is warranted to optimize multi-sensor integration for advanced autonomic nervous system evaluation.
Abstract:
Heart rate variability analysis is a recognized non-invasive tool that is used to assess autonomic nervous system regulation in various clinical settings and medical conditions. A wide variety of HRV analysis methods have been proposed, but they all require a certain number of cardiac beats intervals. There are many ways to record cardiac activity: electrocardiography, phonocardiography, plethysmocardiography, seismocardiography. However, the feasibility of performing HRV analysis with these technologies and particularly their ability to detect autonomic nervous system changes still has to be studied. In this study, we developed a technology allowing the simultaneous monitoring of electrocardiography, phonocardiography, seismocardiography, photoplethysmocardiography and piezoplethysmocardiography and investigated whether these sensors could be used for HRV analysis. We therefore tested the evolution of several HRV parameters computed from several sensors before, during and after a postural change. The main findings of our study is that even if most sensors were suitable for mean HR computation, some of them demonstrated limited agreement for several HRV analyses methods. We also demonstrated that piezoplethysmocardiography showed better agreement with ECG than other sensors for most HRV indexes.
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