The physiological measurement and evaluation of empathy of video content.

The COVID-19 pandemic has led to a surge in video content consumption, but measuring viewers' empathy towards the content has been limited to subjective evaluations or attached physiological apparatus. In this study, we introduced a novel non-contact physiological method for measuring empathy towards video content by assessing the synchronization of facial micromovements between the subject and object (i.e.

Recognition of Empathy from Synchronization between Brain Activity and Eye Movement.

In the era of user-generated content (UGC) and virtual interactions within the metaverse, empathic digital content has become increasingly important. This study aimed to quantify human empathy levels when exposed to digital media. To assess empathy, we analyzed brain wave activity and eye movements in response to emotional videos.

Recognition of Emotion by Brain Connectivity and Eye Movement.

Simultaneous activation of brain regions (i.e., brain connection features) is an essential mechanism of brain activity in emotion recognition of visual content.

Significant Measures of Gaze and Pupil Movement for Evaluating Empathy between Viewers and Digital Content.

The success of digital content depends largely on whether viewers empathize with stories and narratives. Researchers have investigated the elements that may elicit empathy from viewers. Empathic response involves affective and cognitive processes and is expressed through multiple verbal and nonverbal modalities.

Non-Contact Measurement of Empathy Based on Micro-Movement Synchronization.

Tracking consumer empathy is one of the biggest challenges for advertisers. Although numerous studies have shown that consumers' empathy affects purchasing, there are few quantitative and unobtrusive methods for assessing whether the viewer is sharing congruent emotions with the advertisement. This study suggested a non-contact method for measuring empathy by evaluating the synchronization of micro-movements between consumers and people within the media.

An Empathy Evaluation System Using Spectrogram Image Features of Audio.

Watching videos online has become part of a relaxed lifestyle. The music in videos has a sensitive influence on human emotions, perception, and imaginations, which can make people feel relaxed or sad, and so on. Therefore, it is particularly important for people who make advertising videos to understand the relationship between the physical elements of music and empathy characteristics.

Fusion Method to Estimate Heart Rate from Facial Videos Based on RPPG and RBCG.

Remote sensing of vital signs has been developed to improve the measurement environment by using a camera without a skin-contact sensor. The camera-based method is based on two concepts, namely color and motion. The color-based method, remote photoplethysmography (RPPG), measures the color variation of the face generated by reflectance of blood, whereas the motion-based method, remote ballistocardiography (RBCG), measures the subtle motion of the head generated by heartbeat.

Embodied Emotion Recognition Based on Life-Logging.

Embodied emotion is associated with interaction among a person's physiological responses, behavioral patterns, and environmental factors. However, most methods for determining embodied emotion has been considered on only fragmentary independent variables and not their inter-connectivity. This study suggests a method for determining the embodied emotion considering interactions among three factors: the physiological response, behavioral patterns, and an environmental factor based on life-logging.

Vision-Based Measurement of Heart Rate from Ballistocardiographic Head Movements Using Unsupervised Clustering.

Heart rate has been measured comfortably using a camera without the skin-contact by the development of vision-based measurement. Despite the potential of the vision-based measurement, it has still presented limited ability due to the noise of illumination variance and motion artifacts. Remote ballistocardiography (BCG) was used to estimate heart rate from the ballistocardiographic head movements generated by the flow of blood through the carotid arteries.