Detecting, Predicting, and Preventing Driver Drowsiness with Wrist-Wearable Devices

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Rodrigues, C (Author) Other; Faria, BM (Author) Other; reis, lp (Author) FEUP

Conference proceedings International

Title: PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2021)

Pages: 109-120

20th EPIA Conference on Artificial Intelligence (EPIA)

ELECTR NETWORK, SEP 07-09, 2021

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Other information

Authenticus ID: P-00V-DS4

DOI: 10.1007/978-3-030-86230-5_9

Abstract (EN): Insufficient sleep is a prominent problem in modern society with several negative effects and risks. One of the most serious consequences is traffic accidents caused by drowsy driving. Current solutions are focused on detecting drowsiness, where individuals need to reach a certain drowsiness level to receive an alarm, which may be too late to react. In this context, it is relevant to develop a wearable system that integrates the prediction of drowsiness and its prevention. By predicting the drowsy state, the driver can be warned in advance while still alert. To minimize further incidents, the reason why a state of drowsiness occurs must be identified, caused by a sleep disorder or sleep deprivation. The contribution of this work is to review the main scientific and commercial solutions, and perform automatic sleep staging based on heart rate variability. Results show that, although promising, this approach requires a larger dataset to consider a user-dependent scenario.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12