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

Psychiatry Investigation 2020년 17권 9호 p.960 ~ 965
Sheridan David C., Dehart Ryan, Lin Amber, Sabbaj Michael, Baker Steven D.,
소속 상세정보
 ( Sheridan David C. ) - Oregon Health and Science University Department of Emergency Medicine
 ( Dehart Ryan ) - Oregon Health and Science University Department of Emergency Medicine
 ( Lin Amber ) - Oregon Health and Science University Department of Emergency Medicine
 ( Sabbaj Michael ) - Oregon Health and Science University Department of Emergency Medicine
 ( Baker Steven D. ) - Oregon Health and Science University Department of Emergency Medicine

Abstract


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.

키워드

Heart rate variability; Artifact; Suicidality; Mental health

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