Research on Driver Emotion Classification Based on ECG Signals

Anlin Liu*, and Kunmei Zhang

Abstract

Traffic includes factors that affect people, vehicles, and the environment. According to official data, traffic accidents caused directly or indirectly by human factors account for over 90% of the total number of traffic accidents, of which 70% are caused by vehicle drivers. Studying driver characteristics and considering driver factors in traffic safety has become an increasingly popular topic in the field of traffic safety. Driving emotions, as one of the driver characteristics, have a strong correlation with driving behavior. This article designs a simulated driving experiment and collects the electrocardiogram (ECG) indicators of drivers in driving with pleasure and anger during the experiment. The KNN clustering algorithm is used to classify and analyze the driver’s emotions.

Keywords

driving safety; driving emotions; electrocardiogram; clustering algorithm

Cite This Article

Zhang, K., Liu, A. (2023). Research on Driver Emotion Classification Based on ECG Signals. International Journal of Scientific Advances (IJSCIA), Volume 4| Issue 4: Jul-Aug 2023, Pages 605-608, URL: https://www.ijscia.com/wp-content/uploads/2023/08/Volume4-Issue4-Jul-Aug-No.479-605-608.pdf

Volume 4 | Issue 4: Jul-Aug 2023