Experimental discussion on measurement of mental workload - evaluation of mental workload by HRV measures -

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The aim of this study is to evaluate mental workload (MWL) quantitatively by HRV (Heart Rate Variability) measures. The electrocardiography and the respiration curve were recorded in five different epochs (1) during a rest condition and (2) during mental arithmetic tasks (addition). In the experiment, subjects added two numbers. The work levels (figures of the number in the addition) were set to one figure, two figures, three figures and four figures. The work level had effects on the mean percent correct, the number of answers and the mean processing time. The psychological evaluation on mental workload obtained by the method of paired comparison increased with the work level. Among the statistical HRV measures, the number of peak and trough waves could distinguish between the rest and the mental loading. However, mental workload for each work level was not evaluated quantitatively by the measure. The HRV measures were also calculated from the power spectrum estimated by the autoregressive (AR) model identification. The ratio of the low frequency power to the high frequency power increased linearly with the work level. In conclusion, the HRV measures obtained by the AR power spectrum analysis were found to be sensitive to changes of mental workload.

Original languageEnglish
Pages (from-to)409-416
Number of pages8
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE77-A
Issue number2
Publication statusPublished - Feb 1994
Externally publishedYes

Fingerprint

Heart Rate Variability
Workload
Figure
Evaluation
Power spectrum
Power Spectrum
Mental arithmetic
Electrocardiography
Paired Comparisons
Spectrum Analysis
Power Analysis
Spectrum analysis
Model Identification
Respiration
Autoregressive Model
Identification (control systems)
Percent
Low Frequency
Linearly
Processing

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems
  • Electrical and Electronic Engineering

Cite this

@article{705f9df393f14fa1a58adf03f482603f,
title = "Experimental discussion on measurement of mental workload - evaluation of mental workload by HRV measures -",
abstract = "The aim of this study is to evaluate mental workload (MWL) quantitatively by HRV (Heart Rate Variability) measures. The electrocardiography and the respiration curve were recorded in five different epochs (1) during a rest condition and (2) during mental arithmetic tasks (addition). In the experiment, subjects added two numbers. The work levels (figures of the number in the addition) were set to one figure, two figures, three figures and four figures. The work level had effects on the mean percent correct, the number of answers and the mean processing time. The psychological evaluation on mental workload obtained by the method of paired comparison increased with the work level. Among the statistical HRV measures, the number of peak and trough waves could distinguish between the rest and the mental loading. However, mental workload for each work level was not evaluated quantitatively by the measure. The HRV measures were also calculated from the power spectrum estimated by the autoregressive (AR) model identification. The ratio of the low frequency power to the high frequency power increased linearly with the work level. In conclusion, the HRV measures obtained by the AR power spectrum analysis were found to be sensitive to changes of mental workload.",
author = "Atsuo Murata",
year = "1994",
month = "2",
language = "English",
volume = "E77-A",
pages = "409--416",
journal = "IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences",
issn = "0916-8508",
publisher = "Maruzen Co., Ltd/Maruzen Kabushikikaisha",
number = "2",

}

TY - JOUR

T1 - Experimental discussion on measurement of mental workload - evaluation of mental workload by HRV measures -

AU - Murata, Atsuo

PY - 1994/2

Y1 - 1994/2

N2 - The aim of this study is to evaluate mental workload (MWL) quantitatively by HRV (Heart Rate Variability) measures. The electrocardiography and the respiration curve were recorded in five different epochs (1) during a rest condition and (2) during mental arithmetic tasks (addition). In the experiment, subjects added two numbers. The work levels (figures of the number in the addition) were set to one figure, two figures, three figures and four figures. The work level had effects on the mean percent correct, the number of answers and the mean processing time. The psychological evaluation on mental workload obtained by the method of paired comparison increased with the work level. Among the statistical HRV measures, the number of peak and trough waves could distinguish between the rest and the mental loading. However, mental workload for each work level was not evaluated quantitatively by the measure. The HRV measures were also calculated from the power spectrum estimated by the autoregressive (AR) model identification. The ratio of the low frequency power to the high frequency power increased linearly with the work level. In conclusion, the HRV measures obtained by the AR power spectrum analysis were found to be sensitive to changes of mental workload.

AB - The aim of this study is to evaluate mental workload (MWL) quantitatively by HRV (Heart Rate Variability) measures. The electrocardiography and the respiration curve were recorded in five different epochs (1) during a rest condition and (2) during mental arithmetic tasks (addition). In the experiment, subjects added two numbers. The work levels (figures of the number in the addition) were set to one figure, two figures, three figures and four figures. The work level had effects on the mean percent correct, the number of answers and the mean processing time. The psychological evaluation on mental workload obtained by the method of paired comparison increased with the work level. Among the statistical HRV measures, the number of peak and trough waves could distinguish between the rest and the mental loading. However, mental workload for each work level was not evaluated quantitatively by the measure. The HRV measures were also calculated from the power spectrum estimated by the autoregressive (AR) model identification. The ratio of the low frequency power to the high frequency power increased linearly with the work level. In conclusion, the HRV measures obtained by the AR power spectrum analysis were found to be sensitive to changes of mental workload.

UR - http://www.scopus.com/inward/record.url?scp=0028381306&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0028381306&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0028381306

VL - E77-A

SP - 409

EP - 416

JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

SN - 0916-8508

IS - 2

ER -