Paper Info
Title
Remote heart rate variability for emotional state monitoring
Abstract
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.
Year
DOI
Venue
2018
10.1109/BHI.2018.8333392
2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)
Keywords
Field
DocType
remote heart rate variability,emotional state monitoring,physiological signals,autonomic nervous system,remote photoplethysmography algorithm,rHRV signal,different emotional states,frequency domain,emotion recognition
Modalities,Frequency domain,Autonomic nervous system,Photoplethysmogram,Computer science,Heart rate variability,Gesture,Speech recognition,Correlation,Facial expression
Conference
ISBN
Citations 
PageRank 
978-1-5386-2406-7
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Yannick Benezeth139926.11
Peixi Li200.34
Richard Macwan3165.11
Keisuke Nakamura418928.91
Randy Gomez57628.11
Fan Yang6115.91