2020
DOI: 10.1007/978-3-030-65871-7_13
|View full text |Cite
|
Sign up to set email alerts
|

Automatic Detection and Prediction of the Transition Between the Behavioural States of a Subject Through a Wearable CPS

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

1
1
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 8 publications
1
1
0
Order By: Relevance
“…Results of the experimental validation are reported: two test sessions were performed, one in domestic environments and one in realistic driving environments by using a dynamic driving simulator. The results confirm the results obtained in the previous work (Groppo et al, 2020), and the capability of the proposed algorithm in predicting sleep while driving using a physiological signal that can be collected at the wrist of the driver.INDEX TERMS Drowsiness onset detection, sleep onset, accident prevention.…”
supporting
confidence: 88%
See 1 more Smart Citation
“…Results of the experimental validation are reported: two test sessions were performed, one in domestic environments and one in realistic driving environments by using a dynamic driving simulator. The results confirm the results obtained in the previous work (Groppo et al, 2020), and the capability of the proposed algorithm in predicting sleep while driving using a physiological signal that can be collected at the wrist of the driver.INDEX TERMS Drowsiness onset detection, sleep onset, accident prevention.…”
supporting
confidence: 88%
“…Although PPG-based analysis is an established methodology in sleep medicine, the main novelty of this paper lies in using PPG to predict sleep before it takes place. The paper improves the work presented in [19] in two main directions. It adds the calibration part that makes the algorithm adaptable to the wearer physiology, and it introduces the motion artifact removal functions.…”
Section: Introductionmentioning
confidence: 52%