Maritime shift workers sleepiness detection system with multi-modality cues

Sleepiness has been recognized as a causal factor in many round-the-clock industries. While individuals can subjectively express their momentary sleepiness level, sleepiness-related contextual factors (CF) can influence their perception of sleepiness and cognitive performance. In this paper, the sel...

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Main Authors: Balandong, R.P., Tang, T.B., Short, M.A., Saad, N.M.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.30179 /
Published: Institute of Electrical and Electronics Engineers Inc. 2019
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097350825&doi=10.1109%2fACCESS.2019.2929066&partnerID=40&md5=358da65d90f3cdf39afc98bc94232761
http://eprints.utp.edu.my/30179/
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spelling utp-eprints.301792022-03-25T06:36:18Z Maritime shift workers sleepiness detection system with multi-modality cues Balandong, R.P. Tang, T.B. Short, M.A. Saad, N.M. Sleepiness has been recognized as a causal factor in many round-the-clock industries. While individuals can subjectively express their momentary sleepiness level, sleepiness-related contextual factors (CF) can influence their perception of sleepiness and cognitive performance. In this paper, the self-reported sleepiness value (vSRS) was improved by transforming it into a kernel density estimate and the assignment of the class�s score is done using a likelihood ratio test (IvSRS). We integrated multiple CF and IvSRS to model sleepiness using a Bayesian network (BN). The BN produced a single probability estimate calculated based on the prior and posterior probability of the CF and IvSRS. The results showed IvSRS performed better (p < 0.05) in classifying sleepiness to three states, compared to non-modified vSRS. Considering each CF and IvSRS as stand alone indicators, integrating all these information under a BN significantly improved the systems performance (p � 0.05). In addition to being able to function well in the event of missing vSRS, the proposed system has a prediction horizon of 12 h, with F1-measure > 78. © 2019 Institute of Electrical and Electronics Engineers Inc.. All rights reserved. Institute of Electrical and Electronics Engineers Inc. 2019 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097350825&doi=10.1109%2fACCESS.2019.2929066&partnerID=40&md5=358da65d90f3cdf39afc98bc94232761 Balandong, R.P. and Tang, T.B. and Short, M.A. and Saad, N.M. (2019) Maritime shift workers sleepiness detection system with multi-modality cues. IEEE Access, 7 . pp. 98792-98802. http://eprints.utp.edu.my/30179/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Sleepiness has been recognized as a causal factor in many round-the-clock industries. While individuals can subjectively express their momentary sleepiness level, sleepiness-related contextual factors (CF) can influence their perception of sleepiness and cognitive performance. In this paper, the self-reported sleepiness value (vSRS) was improved by transforming it into a kernel density estimate and the assignment of the class�s score is done using a likelihood ratio test (IvSRS). We integrated multiple CF and IvSRS to model sleepiness using a Bayesian network (BN). The BN produced a single probability estimate calculated based on the prior and posterior probability of the CF and IvSRS. The results showed IvSRS performed better (p < 0.05) in classifying sleepiness to three states, compared to non-modified vSRS. Considering each CF and IvSRS as stand alone indicators, integrating all these information under a BN significantly improved the systems performance (p � 0.05). In addition to being able to function well in the event of missing vSRS, the proposed system has a prediction horizon of 12 h, with F1-measure > 78. © 2019 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
format Article
author Balandong, R.P.
Tang, T.B.
Short, M.A.
Saad, N.M.
spellingShingle Balandong, R.P.
Tang, T.B.
Short, M.A.
Saad, N.M.
Maritime shift workers sleepiness detection system with multi-modality cues
author_sort Balandong, R.P.
title Maritime shift workers sleepiness detection system with multi-modality cues
title_short Maritime shift workers sleepiness detection system with multi-modality cues
title_full Maritime shift workers sleepiness detection system with multi-modality cues
title_fullStr Maritime shift workers sleepiness detection system with multi-modality cues
title_full_unstemmed Maritime shift workers sleepiness detection system with multi-modality cues
title_sort maritime shift workers sleepiness detection system with multi-modality cues
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2019
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097350825&doi=10.1109%2fACCESS.2019.2929066&partnerID=40&md5=358da65d90f3cdf39afc98bc94232761
http://eprints.utp.edu.my/30179/
_version_ 1741197362562334720
score 11.62408

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