Key result
Emotion classification using pulse rate variability obtained via remote photoplethysmography from a simple RGB camera achieved an accuracy rate of around 60% on the CAS(ME)2 dataset.
Why the study?
Heart rhythm fluctuations reflect autonomic nervous system activity during emotional excitation, but evaluating emotional state using pulse rate variability from remote photoplethysmography required investigation.
Remote photoplethysmography using a simple RGB camera can assess emotional states via pulse rate variability with moderate accuracy.
Humans are continually exposed to emotional stimuli. Gesture, voice intonation, and facial expressions are among the most popular cues that describe our changing emotions. However, the physiological systems that govern our bodily functions are also impacted by the different emotions that we feel. Psychophysiology is a science concerned with the existing relationship between the psychic state of a person and the physiological signals their body emits. In fact, this connection is due to the autonomic nervous system activity, whose sympathetic nerves get sparked when a person is emotionally excited. One particular physiological phenomenon has turned out to be an excellent indicator of the autonomic function. It is the spontaneous fluctuations in the heart rhythms, which can be described by the pulse rate variability (PRV). In this work, the PRV is obtained using remote photoplethysmography. We prove that from a simple RGB camera, it is possible to assess the emotional state of a person by analysing their pulse rate variations. This optimistic finding is supported by surprising results and an accuracy rate of around 60% on the CAS(ME) 2 dataset. This is the first study to propose an emotion classification based on a physiological signal analysis using CAS(ME) 2 .
No takes yet. Share an insight, caveat, or question.
Sabour et al. (2019) studied Emotional state. Remote photoplethysmography via RGB camera was evaluated on Emotion classification accuracy. Emotion classification using pulse rate variability obtained via remote photoplethysmography from a simple RGB camera achieved an accuracy rate of around 60% on the CAS(ME)2 dataset.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: