The Real-Time Application of an Additional HRV Reduction Algorithm to Detect Negative Psychosocial States

Abstract

Abstract: Unobtrusively identifying adverse psychosocial states in everyday life would offer intriguing possibilities to trigger just-in-time adaptive interventions (JITAIs). Previously, we simulated algorithms to predict psychosocial states by means of cardiac data (so-called, additional, nonmetabolic heart rate variability reductions; AddHRVr). For the first time, this study implemented the AddHRVr algorithm in real-time mode to evaluate whether we could predict stress, perseverative cognition, or low-quality social interactions. We applied an ecological momentary assessment (EMA) in a sample of 36 participants for five consecutive days. The functioning of the AddHRVr algorithm did not translate into real-world application, and higher stress, perseverative cognition, or low-quality social interactions following the AddHRVr trigger could not be confirmed. Further data simulations were conducted to evaluate the reasons for the algorithm’s malfunctioning. We provide recommendations for future studies and call for further research and technical refinements to better align simulation approaches with real-time applications.