Experimental Discussion on Measurement of Mental Workload--Evaluation of Mental Workload by HRV Measures--

Atsuo MURATA

Experimental Discussion on Measurement of Mental Workload--Evaluation of Mental Workload by HRV Measures--

Atsuo MURATA

Full Text Views

0

Cite this

Summary :

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.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E77-A No.2 pp.409-416

Publication Date: 1994/02/25

Publicized

Online ISSN

DOI

Type of Manuscript: PAPER

Category: Ergonomics and medical Engineering

Cite this

Copy

Atsuo MURATA, "Experimental Discussion on Measurement of Mental Workload--Evaluation of Mental Workload by HRV Measures--" in IEICE TRANSACTIONS on Fundamentals, vol. E77-A, no. 2, pp. 409-416, February 1994, doi: .
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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e77-a_2_409/_p

Copy

@ARTICLE{e77-a_2_409,
author={Atsuo MURATA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Experimental Discussion on Measurement of Mental Workload--Evaluation of Mental Workload by HRV Measures--},
year={1994},
volume={E77-A},
number={2},
pages={409-416},
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.},
keywords={},
doi={},
ISSN={},
month={February},}

Copy

TY - JOUR
TI - Experimental Discussion on Measurement of Mental Workload--Evaluation of Mental Workload by HRV Measures--
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 409
EP - 416
AU - Atsuo MURATA
PY - 1994
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E77-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 1994
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.
ER -