Article,
Facilitating ambulatory heart rate variability analysis using accelerometry-based classifications of body position and self-reported sleep
Contributors
Rietz, Marlene
0000-0002-6422-6215
[1]
[2]
Schmidt-Persson, Jesper
0000-0002-9475-0341
[2]
[3]
Rasmussen, Martin Gillies Banke
0000-0002-2114-2185
[2]
[4]
Sørensen, Sarah Overgaard
0000-0002-3953-3387
[2]
Mortensen, Sofie Rath
0000-0002-9550-1507
[2]
[5]
Brage, Soren
0000-0002-1265-7355
[2]
[6]
Kristensen, Peter Lund
0000-0002-5666-9614
[2]
Grøntved, Anders
0000-0003-1584-679X
[2]
Brønd, Jan Christian
0000-0001-6718-3022
(Corresponding author)
[2]
Affiliations
- [1] Karolinska Institutet [NORA names: Sweden; Europe, EU; Nordic; OECD];
- [2] University of Southern Denmark [NORA names: SDU University of Southern Denmark; University; Denmark; Europe, EU; Nordic; OECD];
- [3] University College Copenhagen [NORA names: KP University College Copenhagen; College; Denmark; Europe, EU; Nordic; OECD];
- [4] Odense University Hospital [NORA names: Region of Southern Denmark; Hospital; Denmark; Europe, EU; Nordic; OECD];
- [5] Næstved, Slagelse and Ringsted Hospitals [NORA names: Region Zealand; Hospital; Denmark; Europe, EU; Nordic; OECD];
(... more)
Abstract
Objective.This study aimed to examine differences in heart rate variability (HRV) across accelerometer-derived position, self-reported sleep, and different summary measures (sleep, 24 h HRV) in free-living settings using open-source methodology.Approach.HRV is a biomarker of autonomic activity. As it is strongly affected by factors such as physical behaviour, stress, and sleep, ambulatory HRV analysis is challenging. Beat-to-beat heart rate (HR) and accelerometry data were collected using single-lead electrocardiography and trunk- and thigh-worn accelerometers among 160 adults participating in the SCREENS trial. HR files were processed and analysed in the RHRV R package. Start time and duration spent in physical behaviours were extracted, and time and frequency analysis for each episode was performed. Differences in HRV estimates across activities were compared using linear mixed models adjusted for age and sex with subject ID as random effect. Next, repeated-measures Bland-Altman analysis was used to compare 24 h RMSSD estimates to HRV during self-reported sleep. Sensitivity analyses evaluated the accuracy of the methodology, and the approach of employing accelerometer-determined episodes to examine activity-independent HRV was described.Main results.HRV was estimated for 31 289 episodes in 160 individuals (53.1% female) at a mean age of 41.4 years. Significant differences in HR and most markers of HRV were found across positions [Mean differences RMSSD: Sitting (Reference) - Standing (-2.63 ms) or Lying (4.53 ms)]. Moreover, ambulatory HRV differed significantly across sleep status, and poor agreement between 24 h estimates compared to sleep HRV was detected. Sensitivity analyses confirmed that removing the first and last 30 s of accelerometry-determined HR episodes was an accurate strategy to account for orthostatic effects.Significance.Ambulatory HRV differed significantly across accelerometry-assigned positions and sleep. The proposed approach for free-living HRV analysis may be an effective strategy to remove confounding by physical activity when the aim is to monitor general autonomic stress.
