Volltext-Downloads (blau) und Frontdoor-Views (grau)
The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 14 of 113
Back to Result List

ECG sensor for detection of driver’s drowsiness

  • Fatigue and drowsiness are responsible for a significant percentage of road traffic accidents. There are several approaches to monitor the driver’s drowsiness, ranging from the driver’s steering behavior to analysis of the driver, e.g. eye tracking, blinking, yawning or electrocardiogram (ECG). This paper describes the development of a low-cost ECG sensor to derive heart rate variability (HRV) data for the drowsiness detection. The work includes the hardware and the software design. The hardware has been implemented on a printed circuit board (PCB) designed so that the board can be used as an extension shield for an Arduino. The PCB contains a double, inverted ECG channel including low-pass filtering and provides two analog outputs to the Arduino, that combined them and performs the analog-to-digital conversion. The digital ECG signal is transferred to an NVidia embedded PC where the processing takes place, including QRS-complex, heart rate and HRV detection as well as visualization features. The compact resulting sensor provides good results in the extraction of the main ECG parameters. The sensor is being used in a larger frame, where facial-recognition-based drowsiness detection is combined with ECG-based detection to improve the recognition rate under unfavorable light or occlusion conditions.

Download full text files

Export metadata

Additional Services

Search Google Scholar

Statistics

frontdoor_oas
Metadaten
Author:Markus Gromer, David Salb, Thomas WalzerORCiD, Natividad Martínez MadridORCiD, Ralf SeepoldORCiDGND
URN:urn:nbn:de:bsz:kon4-opus4-21587
DOI:https://doi.org/10.1016/j.procs.2019.09.366
ISSN:1877-0509
Parent Title (English):23rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2019), 4 - 6 September 2019, Budapest, Hungary; (Procedia Computer Science)
Volume:159
Document Type:Conference Proceeding
Language:English
Year of Publication:2019
Release Date:2020/01/08
Tag:ECG; Drowsiness; Automotive; Sleep; Biomedical Signal Capturing
First Page:1938
Last Page:1946
Institutes:Fakultät Informatik
DDC functional group:004 Informatik
Open Access?:Ja
Relevance:Peer reviewed nach anderen Listungen (mit Nachweis zum Peer Review Verfahren)
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International