Physiological parameter response to variation of mental workload
Previous studies have examined how individual physiological measures respond to changes in mental demand and subjective reports of mental workload. This study explores the response of multiple physiological parameters, measured simultaneously and quantifies the added value of each of the measures wh...
| Main Authors: | , , , , , |
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| Format: | Article |
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Sage
2017
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| Online Access: | https://eprints.nottingham.ac.uk/45218/ |
| _version_ | 1848797091744186368 |
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| author | Marinescu, Adrian Sharples, Sarah Campbell Ritchie, Alastair Sanchez Lopez, Tomas McDowell, Michael Morvan, Herve |
| author_facet | Marinescu, Adrian Sharples, Sarah Campbell Ritchie, Alastair Sanchez Lopez, Tomas McDowell, Michael Morvan, Herve |
| author_sort | Marinescu, Adrian |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Previous studies have examined how individual physiological measures respond to changes in mental demand and subjective reports of mental workload. This study explores the response of multiple physiological parameters, measured simultaneously and quantifies the added value of each of the measures when estimating the level of demand.
The study presented was conducted in laboratory conditions and required participants to perform a custom-designed visual-motor task that imposed varying levels of demand. The data collected consisted of: physiological measurements (heart inter-beat intervals, breathing rate, pupil diameter, facial thermography); subjective ratings of workload from the participants (ISA and NASA-TLX); and the performance measured within the task.
Facial thermography and pupil diameter were demonstrated to be good candidates for non-invasive mental workload measurements; for 7 out of 10 participants, pupil diameter showed a strong correlation (with R values between 0.61 and 0.79 at a significance value of 0.01) with mean ISA normalized values. Facial thermography measures added on average 47.7% to the amount of variability in task performance explained by a regression model. As with the ISA ratings, the relationship between the physiological measures and performance showed strong inter-participant differences, with some individuals demonstrating a much stronger relationship between workload and performance measures than others.
The results presented in this paper demonstrate that physiological monitoring can be used for non-invasive real-time measurement of workload, assuming models have been appropriately trained on previously recorded data from the user population. Facial thermography combined with measurement of pupil diameter are strong candidates for real-time monitoring of workload due to the availability and non-intrusive nature of current technology. The study also demonstrates the importance of identifying whether an individual is one who demonstrates a strong relationship between physiological measures and experienced workload measures before physiological measures are applied uniformly. This is a feasible proposition in a setting such as aircraft cockpits, where pilots are drawn from a relatively small, targeted and managed population. |
| first_indexed | 2025-11-14T19:58:22Z |
| format | Article |
| id | nottingham-45218 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:58:22Z |
| publishDate | 2017 |
| publisher | Sage |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-452182020-05-04T19:09:55Z https://eprints.nottingham.ac.uk/45218/ Physiological parameter response to variation of mental workload Marinescu, Adrian Sharples, Sarah Campbell Ritchie, Alastair Sanchez Lopez, Tomas McDowell, Michael Morvan, Herve Previous studies have examined how individual physiological measures respond to changes in mental demand and subjective reports of mental workload. This study explores the response of multiple physiological parameters, measured simultaneously and quantifies the added value of each of the measures when estimating the level of demand. The study presented was conducted in laboratory conditions and required participants to perform a custom-designed visual-motor task that imposed varying levels of demand. The data collected consisted of: physiological measurements (heart inter-beat intervals, breathing rate, pupil diameter, facial thermography); subjective ratings of workload from the participants (ISA and NASA-TLX); and the performance measured within the task. Facial thermography and pupil diameter were demonstrated to be good candidates for non-invasive mental workload measurements; for 7 out of 10 participants, pupil diameter showed a strong correlation (with R values between 0.61 and 0.79 at a significance value of 0.01) with mean ISA normalized values. Facial thermography measures added on average 47.7% to the amount of variability in task performance explained by a regression model. As with the ISA ratings, the relationship between the physiological measures and performance showed strong inter-participant differences, with some individuals demonstrating a much stronger relationship between workload and performance measures than others. The results presented in this paper demonstrate that physiological monitoring can be used for non-invasive real-time measurement of workload, assuming models have been appropriately trained on previously recorded data from the user population. Facial thermography combined with measurement of pupil diameter are strong candidates for real-time monitoring of workload due to the availability and non-intrusive nature of current technology. The study also demonstrates the importance of identifying whether an individual is one who demonstrates a strong relationship between physiological measures and experienced workload measures before physiological measures are applied uniformly. This is a feasible proposition in a setting such as aircraft cockpits, where pilots are drawn from a relatively small, targeted and managed population. Sage 2017-09-30 Article PeerReviewed Marinescu, Adrian, Sharples, Sarah, Campbell Ritchie, Alastair, Sanchez Lopez, Tomas, McDowell, Michael and Morvan, Herve (2017) Physiological parameter response to variation of mental workload. Human Factors . ISSN 1547-8181 mental workload human performance facial-thermography pupil diameter physiological measures http://journals.sagepub.com/doi/10.1177/0018720817733101 doi:10.1177/0018720817733101 doi:10.1177/0018720817733101 |
| spellingShingle | mental workload human performance facial-thermography pupil diameter physiological measures Marinescu, Adrian Sharples, Sarah Campbell Ritchie, Alastair Sanchez Lopez, Tomas McDowell, Michael Morvan, Herve Physiological parameter response to variation of mental workload |
| title | Physiological parameter response to variation of mental workload |
| title_full | Physiological parameter response to variation of mental workload |
| title_fullStr | Physiological parameter response to variation of mental workload |
| title_full_unstemmed | Physiological parameter response to variation of mental workload |
| title_short | Physiological parameter response to variation of mental workload |
| title_sort | physiological parameter response to variation of mental workload |
| topic | mental workload human performance facial-thermography pupil diameter physiological measures |
| url | https://eprints.nottingham.ac.uk/45218/ https://eprints.nottingham.ac.uk/45218/ https://eprints.nottingham.ac.uk/45218/ |