Use of Mobile Technology Paired with Heart Rate Monitor to Remotely Quantify Behavioral Health Markers among Military Reservists and First Responders
| Autor: | Laura Strange, Marion Lane, Derek Ramirez, Gregory F. Lewis, Maria I. Davila, Amanda Lewis, Randy Eckhoff, Timothy R. Morgan, Belinda Weimer, Jessica Kelley Morgan, Paul Kizakevich, Laurel Hourani, Sreelatha Meleth |
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| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Technology medicine.medical_treatment Biofeedback Autonomic Nervous System 050105 experimental psychology 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation Heart Rate Heart rate Medicine Heart rate variability Humans 0501 psychology and cognitive sciences Vagal tone business.industry 05 social sciences Heart rate monitor Public Health Environmental and Occupational Health Emergency Responders Repeated measures design General Medicine Autonomic nervous system Military Personnel Behavioral medicine business 030217 neurology & neurosurgery |
| Zdroj: | Military medicine. 186(Suppl 1) |
| ISSN: | 1930-613X |
| Popis: | Introduction Heart rate variability (HRV) is a biological marker that reflects an individual’s autonomic nervous system regulation. Psychological resilience is an individual’s ability to recover from an adverse event and return to physiological homeostasis and mental well-being, indicated by higher resting HRV. The Biofeedback Assisted Resilience Training (BART) study evaluates a resilience-building intervention, with or without HRV biofeedback. This article evaluates the feasibility of remote psychophysiological research by validating the HRV data collected. Materials and Methods The BART platform consists of a mobile health application (BART app) paired to a wearable heart rate monitor. The BART app is installed on the participant’s personal phone/tablet to track and collect self-report psychological and physiological data. The platform collects raw heart rate data and processes HRV to server as online biofeedback. The raw data is processed offline to derive HRV for statistical analysis. The following HRV parameters are validated: inter-beat interval, respiratory sinus arrhythmia, low-frequency HRV, biofeedback HRV, and heart period. Bland–Altman and scatter plots are used to compare and contrast online and offline HRV measures. Repeated-measures ANOVA are used to compared means across tasks during the stress (rest, stress, and recovery) and training (rest and paced breathing) sessions in order to validate autonomic nervous system changes to physiological challenges. Results The analyses included 245 participants. Bland–Altman plots showed excellent agreement and minimal bias between online and offline unedited inter-beat interval data during the stress session. RMANOVA during the training session indicated a significant strong effect on biofeedback HRV, F(11,390) = 967.96, P Conclusions The BART digital health platform supports remote behavioral and physiological data collection, intervention delivery, and online HRV biofeedback. |
| Databáze: | OpenAIRE |
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