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 34 of 104
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 the 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 drowsiness detection. The work includes hardware and software design. The hardware was 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, which combines 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 resulting compact 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 of HS ReutlingenGromer, Markus; Salb, David; Walzer, Thomas; Martínez Madrid, Natividad
URN:urn:nbn:de:bsz:rt2-opus4-25031
DOI:https://doi.org/10.1016/j.procs.2019.09.366
ISSN:1877-0509
Erschienen in:Procedia computer science
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Journal article
Language:English
Publication year:2019
Tag:ECG; automative; biomedical signal capturing; drowsiness; sleep
Volume:159
Page Number:9
First Page:1938
Last Page:1946
DDC classes:004 Informatik
Open access?:Ja
Licence (German):License Logo  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International