| Beschreibung |
Physiological computing uses signals from the body and nervous system—such as brain activity (EEG), eye movements and pupil dynamics, electrodermal activity (EDA), and cardiac activity (ECG/heart rate variability, HRV)—to infer user states and enable interactive systems that can sense and adapt to changes in attention, workload, stress, and affect. By linking physiological sensing with computation, these approaches extend human–computer interaction beyond overt actions (e.g., clicks and speech) toward interfaces that can respond to underlying cognitive and emotional processes. This course introduces the physiological foundations relevant to sensing and interpretation (autonomic and central nervous system basics), and provides an overview of key concepts, theories, and methods in physiological computing. We will discuss current research and application areas including affective computing, adaptive user interfaces, psychophysiology in HCI, and emerging brain–computer interface (BCI) paradigms, with attention to practical challenges such as signal quality, artifacts, individual differences, and validity of inference. A central component is hands-on work in the lab. In small groups, students will learn to design and run simple experiments, record multimodal physiological data, and perform basic preprocessing and analysis. Practical sessions will cover (1) eye tracking and pupillometry (gaze behavior, pupil responses), (2) ECG and HRV (cardiac measures linked to arousal, stress, and regulation), and (3) EDA/skin conductance (phasic and tonic components related to sympathetic activation). Students will gain experience with synchronized data collection, feature extraction, and interpretation, and will critically evaluate what physiological measures can—and cannot—tell us about users and their states. |
