Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Driver Stress State Evaluation by Means of Thermal Imaging: A Supervised Machine Learning Approach Based on ECG Signal

9 references·3 citing·52 second hop

FromToDepth

this work references cited by second hop

References

2005Detecting Stress During Real-World Driving Tasks Using Physiological Sensors2,205 cited
2019A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving349 cited
2017Detecting driving stress in physiological signals based on multimodal feature analysis and kernel classifiers245 cited
2005StressCam230 cited
2015Driver stress level detection using HRV analysis149 cited
2018Automatic driver sleepiness detection using EEG, EOG and contextual information145 cited
2020Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review119 cited
2019Driver’s fatigue recognition based on yawn detection in thermal images107 cited
2017Happy-anger emotions classifications from electrocardiogram signal for automobile driving safety and awareness64 cited

Cited by

2022Classification of Drivers’ Mental Workload Levels: Comparison of Machine Learning Methods Based on ECG and Infrared Thermal Signals63 cited
2020On Driver Behavior Recognition for Increased Safety: A Roadmap55 cited
2022Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach40 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work