Castaldo, Rossana, Montesinos-Silva, Luis and Pecchia, Leandro (2018) Ultra-short entropy for mental stress detection. In: World Congress on Medical Physics and Biomedical Engineering 2018, Prague, 3-8 Jun 2018. Published in: IFMBE Proceedings, 68/2 pp. 287-291. ISBN 9789811090370. doi:10.1007/978-981-10-9038-7_53 ISSN 1680-0737.
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Abstract
Approximate Entropy (ApEn) and Sample Entropy (SampEn) are measures of signals’ complexity and are widely used in Heart Rate Variability (HRV) analysis. In particular, recent studies proved that almost all the features measuring complexity of RR series statistically decreased during the stress and therefore, thus showing ability to detect stress. However, the choice of the similarity threshold r and minimum data length N required for their computation are still controversial. In fact, most entropy measures are considered not reliable for recordings shorter than 5 min and different threshold values r have shown to affect the analysis thus leading to incorrect conclusions.
Therefore, the aim of this study was to understand the impact of changing parameters r and N for the computation of ApEn and SampEn and to select the optimal parameters to detect stress in healthy subjects. To accomplish it, 84 RR series, extracted from electrocardiography signals acquired during real-life stress, were analyzed. ApEn and SampEn were estimated for two different values of r computed using previously published methods and for N = {100, 200, 300, 400, 500} data points. The statistical significance for the differences in mean ApEn and SampEn values was assessed by non-parametric tests.
The two methods used to compute r produced entropy values significantly different over different N values. In contrast, ApEn and SampEn showed consistency in differentiating rest and stress conditions for different input parameters. More specifically, ApEnChon and SampEnChon showed to have a better discrimination power between stressed subjects and resting subjects on ultra-short recordings (N < 500).
| Item Type: | Conference Item (Speech) |
|---|---|
| Subjects: | Q Science > QP Physiology T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering |
| Library of Congress Subject Headings (LCSH): | Heart beat -- Measurement, Heart rate monitoring, Heart beat -- Mathematical models, Stress (Psychology) -- Measurement, Signal processing, Entropy |
| Journal or Publication Title: | IFMBE Proceedings |
| Publisher: | Springer, Singapore |
| ISBN: | 9789811090370 |
| ISSN: | 1680-0737 |
| Book Title: | World Congress on Medical Physics and Biomedical Engineering 2018 |
| Editor: | Lhotska, L. and Lacković, I. and Ibbott, G. |
| Official Date: | June 2018 |
| Dates: | Date Event June 2018 Published 1 April 2018 Accepted |
| Volume: | 68/2 |
| Page Range: | pp. 287-291 |
| DOI: | 10.1007/978-981-10-9038-7_53 |
| Status: | Peer Reviewed |
| Publication Status: | Published |
| Re-use Statement: | This is a post-peer-review, pre-copyedit version of an article published in IFMBE Proceedings. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-981-10-9038-7_53 |
| Access rights to Published version: | Restricted or Subscription Access |
| Date of first compliant deposit: | 6 August 2018 |
| Date of first compliant Open Access: | 30 May 2019 |
| RIOXX Funder/Project Grant: | Project/Grant ID RIOXX Funder Name Funder ID |
| Conference Paper Type: | Speech |
| Title of Event: | World Congress on Medical Physics and Biomedical Engineering 2018 |
| Type of Event: | Conference |
| Location of Event: | Prague |
| Date(s) of Event: | 3-8 Jun 2018 |
| URI: | https://wrap.warwick.ac.uk/106519/ |
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