Remote heart rate variability for emotional state monitoring

Several researches have been conducted to recognize emotions using various modalities such as facial expressions, gestures, speech or physiological signals. Among all these modalities, physiological signals are especially interesting because they are mainly controlled by the autonomic nervous system...

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Bibliographic Details
Published in2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI) pp. 153 - 156
Main Authors Benezeth, Yannick, Li, Peixi, Macwan, Richard, Nakamura, Keisuke, Gomez, Randy, Yang, Fan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2018
Subjects
Biomedical monitoring
Cameras
Emotion recognition
Heart rate variability
Monitoring
Resonant frequency
Sensors
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Summary:Several researches have been conducted to recognize emotions using various modalities such as facial expressions, gestures, speech or physiological signals. Among all these modalities, physiological signals are especially interesting because they are mainly controlled by the autonomic nervous system. It has been shown for example that there is an undeniable relationship between emotional state and Heart Rate Variability (HRV). In this paper, we present a methodology to monitor emotional state from physiological signals acquired remotely. The method is based on a remote photoplethysmography (rPPG) algorithm that estimates remote Heart Rate Variability (rHRV) using a simple camera. We first show that the rHRV signal can be estimated with a high accuracy (more than 96% in frequency domain). Then, frequency-feature of rHRV is calculated and we show that there is a strong correlation between the rHRV feature and different emotional states. This observation has been validated on 12 out of 16 volunteers and video-induced emotions which opens the way to contactless monitoring of emotions from physiological signals.
DOI:10.1109/BHI.2018.8333392