4 accepted papers
Wearable sensors today can unobtrusively collect rich time-series of physiological states and human movement patterns over a prolonged period. Gaining a better understanding of how an individual's physiological responses vary in different workplace environments can be valuable in understanding human…
Generating accurate ground truth representations of human subjective experiences and judgements is essential for advancing our understanding of human-centered constructs such as emotions. Often, this requires the collection and fusion of annotations from several people where each one is subject to v…
Gaining a better understanding of how people move about and interact with their environment is an important piece of understanding human behavior. Careful analysis of individuals' deviations or variations in movement over time can provide an awareness about changes to their physical or mental state…
Human annotations are of integral value in human behavior studies and in particular for the generation of ground truth for behavior prediction using various machine learning methods. These often subjective human annotations are especially required for studies involving measuring and predicting hidde…