Feelscan

Feelscan is a term used in affective computing and psychophysiology to describe technologies and methods that measure and interpret human affect, or felt emotion, through sensor data collected from users. In practice, feelscan systems integrate multiple modalities to infer emotional states such as engagement, arousal, or valence. Common inputs include facial expression analysis, vocal prosody, heart rate variability, skin conductance, pupil dilation, and, in some cases, electroencephalography. Data from these sources are processed with machine learning models to produce interpretable outputs that can inform research, product design, or clinical assessment.

History and scope: The exact terminology and standards for feelscan are not uniformly defined, and the concept predates contemporary labeling. Related work in the field has evolved through psychophysiology, human-computer interaction, and affective computing since the late 20th century. Feelscan approaches vary widely in sensors, data fusion strategies, and interpretation frameworks, reflecting evolving goals and privacy considerations.

Technology and architecture: A typical feelscan system comprises sensor hardware (wearables, cameras, or microphones), data acquisition and synchronization, feature extraction, and a modeling layer that maps signals to emotional states. Some implementations emphasize real-time feedback for applications like user experience testing or interactive media, while others focus on offline analysis for research or clinical purposes. Privacy, consent, and data security are central concerns due to the sensitive nature of affective data.

Applications and limitations: Uses include usability testing, market research, education and training, entertainment, and clinical monitoring. Limitations involve individual differences in emotional expression, context dependency, potential biases in training data, and ongoing debates about the accuracy and interpretability of affective inferences.

See also: Affective computing, emotion recognition, psychophysiology, biometrics.