Physiological Data

Physiological data analysis focuses on extracting meaningful information from various bodily signals (e.g., ECG, EEG, EDA) to understand human physiological states and behaviors. Current research emphasizes developing robust and generalizable machine learning models, including convolutional and recurrent neural networks, transformers, and generative adversarial networks, to analyze these often noisy and heterogeneous data streams, particularly longitudinal data from wearable sensors. This field is crucial for advancing healthcare through personalized medicine, improving human-computer interaction, and enhancing safety in high-stakes environments like driving and air traffic control, by enabling more accurate and timely assessments of cognitive load, stress, and other crucial factors.