Heart Rate Variability Analysis: How Much Artifact Can We Remove?

Sheridan David C.; Dehart Ryan; Lin Amber; Sabbaj Michael; Baker Steven D.

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자료유형: 학술저널

저자정보: Sheridan David C. (Department of Emergency Medicine Oregon Health & Science University) Dehart Ryan (Department of Emergency Medicine Oregon Health & Science University) Lin Amber (Department of Emergency Medicine Oregon Health & Science University) Sabbaj Michael (Department of Emergency Medicine Oregon Health & Science University) Baker Steven D. (Department of Emergency Medicine Oregon Health & Science University)

저널정보: 대한신경정신의학회 PSYCHIATRY INVESTIGATION PSYCHIATRY INVESTIGATION 제17권 제9호

발행연도: 2020.1

수록면: 960 - 965 (6page)

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Objective Heart rate variability (HRV) evaluates small beat-to-beat time interval (BBI) differences produced by the heart and suggested as a marker of the autonomic nervous system. Artifact produced by movement with wrist worn devices can significantly impact the validity of HRV analysis. The objective of this study was to determine the impact of small errors in BBI selection on HRV analysis and produce a foundation for future research in mental health wearable technology.Methods This was a sub-analysis from a prospective observational clinical trial registered with clinicaltrials.gov (NCT03030924). A cohort of 10 subject’s HRV tracings from a wearable wrist monitor without any artifact were manipulated by the study team to represent the most common forms of artifact encountered.Results Root mean square of successive differences stayed below a clinically significant change when up to 5 beats were selected at the wrong time interval and up to 36% of BBIs was removed. Standard deviation of next normal intervals stayed below a clinically significant change when up to 3 beats were selected at the wrong time interval and up to 36% of BBIs were removed. High frequency HRV shows significant changes when more than 2 beats were selected at the wrong time interval and any BBIs were removed.Conclusion Time domain HRV metrics appear to be more robust to artifact compared to frequency domains. Investigators examining wearable technology for mental health should be aware of these values for future analysis of HRV studies to improve data quality.

#Heart rate variability #Artifact #Suicidality #Mental health.

참고문헌 (20)

참고문헌 신청

Schiweck C / 2019 / Heart rate and high frequency heart rate variability during stress as biomarker for clinical depression. A systematic review / Psychol Med 49:200~211

Wu L / 2014 / Prediction of heart rate variability on cardiac sudden death in heart failure patients : a systematic review / Int J Cardiol 174:857~860

Goldenberg I / 2019 / Heart Rate Variability for Risk Assessment of Myocardial Ischemia in Patients Without Known Coronary Artery Disease : The HRV-DETECT(Heart Rate Variability for the Detection of Myocardial Ischemia)Study / J Am Heart Assoc 8:e014540

1996 / Heart Rate Variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology / Eur Heart J 17:354~381

Singh N / 2018 / Heart rate variability : an old metric with new meaning in the era of using mhealth technologies for health and exercise training guidance. Part one : physiology and methods / Arrhythm Electrophysiol Rev 7:193~198

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