Sensor Integration for Behavior Monitoring

Emerging biosensor devices capture signals indicative of the generative processes in the human body, such as of the activity of the brain, heart, and sweat. The combination of such biosignals with machine learning methodologies presents a great potential in monitoring human behavior in ambulatory settings and a longitudinal manner. However, these also create several challenges related to the varying ambulatory context, diversity of human physiology, and variable temporal resolution of the corresponding biosignals. This chapter provides an overview of studies that have employed biosignals to estimate cognitive, affective, and conative facets of human behavior. It further discusses challenges associated with these studies, as well as future opportunities in the domain of human behavior monitoring via biosignal measures for well-being, health, and education applications.