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Lowering the Sampling Rate: Heart Rate Response during Cognitive Fatigue
Cognitive fatigue is a mental state characterised by feelings of tiredness and impaired cognitive functioning due to sustained cognitive demands. Frequency-domain heart rate variability (HRV) features have been found to vary as a function of cognitive fatigue. However, it has yet to be determined wh...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139121/ https://www.ncbi.nlm.nih.gov/pubmed/35624616 http://dx.doi.org/10.3390/bios12050315 |
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author | Lee, Kar Fye Alvin Chan, Elliot Car, Josip Gan, Woon-Seng Christopoulos, Georgios |
author_facet | Lee, Kar Fye Alvin Chan, Elliot Car, Josip Gan, Woon-Seng Christopoulos, Georgios |
author_sort | Lee, Kar Fye Alvin |
collection | PubMed |
description | Cognitive fatigue is a mental state characterised by feelings of tiredness and impaired cognitive functioning due to sustained cognitive demands. Frequency-domain heart rate variability (HRV) features have been found to vary as a function of cognitive fatigue. However, it has yet to be determined whether HRV features derived from electrocardiogram data with a low sampling rate would remain sensitive to cognitive fatigue. Bridging this research gap is important as it has substantial implications for designing more energy-efficient and less memory-hungry wearables to monitor cognitive fatigue. This study aimed to examine (1) the level of agreement between frequency-domain HRV features derived from lower and higher sampling rates, and (2) whether frequency-domain HRV features derived from lower sampling rates could predict cognitive fatigue. Participants (N = 53) were put through a cognitively fatiguing 2-back task for 20 min whilst their electrocardiograms were recorded. Results revealed that frequency-domain HRV features derived from sampling rate as low as 125 Hz remained almost perfectly in agreement with features derived from the original sampling rate at 2000 Hz. Furthermore, frequency domain features, such as normalised low-frequency power, normalised high-frequency power, and the ratio of low- to high-frequency power varied as a function of increasing cognitive fatigue during the task across all sampling rates. In conclusion, it appears that sampling at 125 Hz is more than adequate for frequency-domain feature extraction to index cognitive fatigue. These findings have significant implications for the design of low-cost wearables for detecting cognitive fatigue. |
format | Online Article Text |
id | pubmed-9139121 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91391212022-05-28 Lowering the Sampling Rate: Heart Rate Response during Cognitive Fatigue Lee, Kar Fye Alvin Chan, Elliot Car, Josip Gan, Woon-Seng Christopoulos, Georgios Biosensors (Basel) Article Cognitive fatigue is a mental state characterised by feelings of tiredness and impaired cognitive functioning due to sustained cognitive demands. Frequency-domain heart rate variability (HRV) features have been found to vary as a function of cognitive fatigue. However, it has yet to be determined whether HRV features derived from electrocardiogram data with a low sampling rate would remain sensitive to cognitive fatigue. Bridging this research gap is important as it has substantial implications for designing more energy-efficient and less memory-hungry wearables to monitor cognitive fatigue. This study aimed to examine (1) the level of agreement between frequency-domain HRV features derived from lower and higher sampling rates, and (2) whether frequency-domain HRV features derived from lower sampling rates could predict cognitive fatigue. Participants (N = 53) were put through a cognitively fatiguing 2-back task for 20 min whilst their electrocardiograms were recorded. Results revealed that frequency-domain HRV features derived from sampling rate as low as 125 Hz remained almost perfectly in agreement with features derived from the original sampling rate at 2000 Hz. Furthermore, frequency domain features, such as normalised low-frequency power, normalised high-frequency power, and the ratio of low- to high-frequency power varied as a function of increasing cognitive fatigue during the task across all sampling rates. In conclusion, it appears that sampling at 125 Hz is more than adequate for frequency-domain feature extraction to index cognitive fatigue. These findings have significant implications for the design of low-cost wearables for detecting cognitive fatigue. MDPI 2022-05-10 /pmc/articles/PMC9139121/ /pubmed/35624616 http://dx.doi.org/10.3390/bios12050315 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lee, Kar Fye Alvin Chan, Elliot Car, Josip Gan, Woon-Seng Christopoulos, Georgios Lowering the Sampling Rate: Heart Rate Response during Cognitive Fatigue |
title | Lowering the Sampling Rate: Heart Rate Response during Cognitive Fatigue |
title_full | Lowering the Sampling Rate: Heart Rate Response during Cognitive Fatigue |
title_fullStr | Lowering the Sampling Rate: Heart Rate Response during Cognitive Fatigue |
title_full_unstemmed | Lowering the Sampling Rate: Heart Rate Response during Cognitive Fatigue |
title_short | Lowering the Sampling Rate: Heart Rate Response during Cognitive Fatigue |
title_sort | lowering the sampling rate: heart rate response during cognitive fatigue |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139121/ https://www.ncbi.nlm.nih.gov/pubmed/35624616 http://dx.doi.org/10.3390/bios12050315 |
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