2018 International Seminar on Application for Technology of Information and Communication · 2018 · 19 citations · 1 references
EngineeringBioengineeringBiomedical EngineeringBiomedical Signal ProcessingBiosensorsSensorsAlerting SystemsCardiac Signal ProcessingCardiovascular MonitoringSignal DetectionVital Signs AssessmentWearable Health TechnologiesDriver Drowsiness DetectionDriver Monitoring SystemsHeart RateHeart Rate MonitoringHeartbeat MonitoringPhotoplethysmogram Signal ProcessingPhotoplethysmographyPhysiological Signal Monitoring
Most traffic accidents are caused by negligence of the driver in managing rest time when driving; driver was sleepy and so could not control the vehicle. Therefore, it is necessary to have a device that can detect sleepiness and warn the driver beforehand so that the driver can avoid the accident. The development of this drowsiness detection system is using the heartbeat as a source of data to be retrieved using Photoplethysmography sensor. The system then classifies and determines the drowsiness level of the driver based on his/her heartbeat. This system uses Arduino Nano and Odroid XU4 as the processing unit and has LCD to display the output. The developed system has the success rate up to 96.52%. From this work, it has been proven that a person's sleep condition will affect the heart rate.
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Heart rate during sleep: implications for monitoring training status.
Miriam R Waldeck · PubMed · 2003 · 29 citations · Full text