Moving beyond the controlled environment of the laboratory, the future of healthcare lies in continuous, ambulatory monitoring. However, translating physiological signals into clinical insights in „hostile” real-world settings presents significant challenges due to noise and non-stationarity.
This lecture explores advanced metrics for Autonomic Nervous System (ANS) analysis, emphasizing a multi-modal approach that integrates Heart Rate Variability (HRV) with other physiological signals, such as respiration among others. We will discuss robust signal processing techniques designed to handle the artifacts of daily life and the limitations of wearable technology. Finally, we will examine how these „decoded” signals are being applied to monitor stress and mental health, and provide new screening tools for Obstructive Sleep Apnea (OSA).