Autonomic responses to pressure sensitivity of head, face and neck: Heart rate and skin conductance

Subjective scales are frequently used in the design process of head-related products to assess pressure discomfort. Nevertheless, some users lack fundamental cognitive and motor abilities (e.g., paralyzed patients). Therefore, it is vital to find non-verbal measurements of pressure discomfort and pressure pain. This study gathered the autonomic...

Survey of Affect Representation Schemes in Physiological Automatic Affect Recognition: A Systematic Literature Review

Physiological signals, such as Electroencephalogram (EEG), Glavic Skin Response (GSR), or Body Temperature, are common inputs for Automatic Affect Recognition (AAR) systems. One of the crucial elements of AAR is the Affect Representation Scheme (ARS) used to define the affective states recognized by the system (e.g., happiness, sadness, fear,...

Weakly-supervised Learning for Fine-grained Emotion Recognition using Physiological Signals

Instead of predicting just one emotion for one activity (e.g., video watching), fine-grained emotion recognition enables more temporally precise recognition. Previous works on fine-grained emotion recognition require segment-by-segment, fine-grained emotion labels to train the recognition algorithm. However, experiments to collect these...

On Fine-grained Temporal Emotion Recognition in Video: How to Trade off Recognition Accuracy with Annotation Complexity?

Fine-grained emotion recognition is the process of automatically identifying the emotions of users at a fine granularity level, typically in the time intervals of 0.5s to 4s according to the expected duration of emotions. Previous work mainly focused on developing algorithms to recognize only one emotion for a video based on the user feedback...

Few-shot Learning for Fine-grained Emotion Recognition using Physiological Signals

Fine-grained emotion recognition can model the temporal dynamics of emotions, which is more precise than predicting one emotion retrospectively for an activity (e.g., video clip watching). Previous works require large amounts of continuously annotated data to train an accurate recognition model, however experiments to collect such large...

CEAP-360VR: A Continuous Physiological and Behavioral Emotion Annotation Dataset for 360 VR Videos

Watching 360 videos using Virtual Reality (VR) head-mounted displays (HMDs) provides interactive and immersive experiences, where videos can evoke different emotions. Existing emotion self-report techniques within VR however are either retrospective or interrupt the immersive experience. To address this, we introduce the Continuous...

Adaptive Real-Time PPG Signal Qualification and Pulse Segmentation

Ever since its invention in the 1930s, photoplethysmography (PPG) is a wide-spread technique used for health-monitoring. Via illumination of the human skin with a light source and capturing the light, an estimate of important physiological properties such as the heart rate can be made. This is commonly done with dedicated medical equipment, but...

Corrnet: Fine-grained emotion recognition for video watching using wearable physiological sensors

Recognizing user emotions while they watch short-form videos anytime and anywhere is essential for facilitating video content customization and personalization. However, most works either classify a single emotion per video stimuli, or are restricted to static, desktop environments. To address this, we propose a correlation-based emotion...

HeartPy: A novel heart rate algorithm for the analysis of noisy signals

Heart rate data are often collected in human factors studies, including those into vehicle automation. Advances in open hardware platforms and off-the-shelf photoplethysmogram (PPG) sensors allow the non-intrusive collection of heart rate data at very low cost. However, the signal is not trivial to analyse, since the morphology of PPG waveforms...

Automated feedback on viewing skills lowers accident involvement

The risk of being involved in an accident in the first year after licensing is greater for novice drivers who passed their driving exam the first time than for novice drivers who failed their first driving exam. Enhanced training programmes can shorten the duration of training and can raise the passing rate on the first exam, but can also...

Heart Rate Analysis for Human Factors: Development and Validation of an Open Source Toolkit for Noisy Naturalistic Heart Rate Data

Heart rate data are collected often in human factors studies. Advances in open hardware platforms and offtheshelf photoplethysmogram (PPG) sensors allow the nonintrusive collection of heart rate data at very low cost. However, the signal is not trivial to analyse, since the morphology of PPG waveforms differs from electrocardiogram (ECG)...