Studying LF and HF Time Series to Characterize Cardiac Physiological Responses to Mental Fatigue
Heart rate variability (HRV) was largely used to evaluate psychophysiological status of Human at rest as well as during cognitive tasks, for both healthy subjects and patients. Among the approaches used for assessing cardiac autonomic control from HRV analysis, biomarkers such as the power in low an...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-06-01
|
| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/68/1/6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Heart rate variability (HRV) was largely used to evaluate psychophysiological status of Human at rest as well as during cognitive tasks, for both healthy subjects and patients. Among the approaches used for assessing cardiac autonomic control from HRV analysis, biomarkers such as the power in low and high frequencies (LF-HF) are often extracted from short-term recordings lasting 2 to 5 min. Although they correctly reflect the average psychophysiological state of a subject in situation, they fail to analyse cardiac autonomic control over time. For this reason, we suggest investigating the LF-HF biomarkers over time to identify mental fatigue and determine different physiological profiles. The following step consists in defining the set of parameters that characterise the LF-HF time series and that can be interpreted easily by the physiologists. In this work, polynomial models are considered to describe the trends of the LF-HF time series. The latter are then decomposed into decreasing (<i>d</i>) and increasing (<i>i</i>) parts. Finally, the proportion of the <i>i</i> parts of the polynomial trends of the LF and HF powers over time are combined with classically-used metrics to define individual profiles in response to mental fatigue. |
|---|---|
| ISSN: | 2673-4591 |