Classical music significantly increased heart rate variability (RMSSD) compared to electronic music (regression coefficient 1.517), although white noise produced the highest variability across all metrics.
RCT (n=242)
Randomized
Single-blind
No
Does listening to different music genres, tempos, and white noise improve heart rate variability in a general population?
242 participants from the general public at a music festival (Lowlands, the Netherlands), median age 28, 56.2% female. Exclusion criteria: self-reported hearing impairment, permanent atrial fibrillation, or pacemaker dependency.
Listening to 3-minute fragments of white noise and four music genres (classical, rock, electronic, and personal music) via active noise-cancelling headphones. Participants were randomized to a slow tempo group (70-95 BPM) or a fast tempo group (120-140 BPM).
Within-subject comparison across the different music genres and white noise (which was intended as a baseline measurement).
Heart rate variability (HRV) metrics including standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences (RMSSD), low-frequency power (LF), and high-frequency power (HF), calculated using the last two minutes of each 3-minute measurement.surrogate
White noise and slow classical music significantly enhance heart rate variability compared to other music genres, suggesting potential simple therapeutic interventions for autonomic modulation.
Effect estimate: Regression coefficient 1.517 (95% CI 0.191-2.844)
p-value: p=0.025
AIMS: Low heart rate variability (HRV) is associated with increased morbidity and mortality in various health conditions. Music can enhance HRV, but it remains unclear which music characteristics are most effective. This study aimed to assess the impact of music genre, white noise, tempo, and personal music preferences on HRV. METHODS: In this single-blind, randomised, within-subject study, participants without atrial fibrillation or pacemaker dependency listened to three-minute fragments of white noise and four music genres (classical, rock, electronic and a personal music) in random order. Participants were randomised to a slow or fast tempo group. Heart beats were recorded using a smartwatch containing a photoplethysmography (PPG) sensor; non-sinus beats were excluded using a custom algorithm. HRV was analysed using a general linear mixed model adjusted for heart rate, sex, age and tempo, with interaction analysis for tempo effects. RESULTS: A total of 242 participants were included. White noise was associated with the highest HRV across all tested metrics: standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences (RMSSD), low-frequency power (LF), and high-frequency power (HF). Furthermore, HRV (RMSSD) was higher during classical music compared to electronic and personal music (P = 0.025 and P = 0.030). Interaction analysis showed the latter was due to differences only in slow music tempo. CONCLUSION: Slow, classical music enhances HRV more than electronic or personal music, suggesting its therapeutic potential. Remarkably, white noise showed the greatest increase in HRV compared to all music genres, possibly due to its consistent and monotonous sound characteristics inducing a relaxation response and increased parasympathetic activity.
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Shari Pepplinkhuizen
Amsterdam Neuroscience
Nicole J. van Steijn
Amsterdam Neuroscience
E. Madelief Marsman
Amsterdam Neuroscience
Complementary Therapies in Medicine
University of Amsterdam
Tilburg University
Amsterdam University Medical Centers
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Pepplinkhuizen et al. (Fri,) conducted a rct in Healthy participants (n=242). Classical music and white noise vs. Electronic, rock, and personal music was evaluated on Heart rate variability (RMSSD) (Regression coefficient 1.517, 95% CI 0.191-2.844, p=0.025). Classical music significantly increased heart rate variability (RMSSD) compared to electronic music (regression coefficient 1.517), although white noise produced the highest variability across all metrics.
synapsesocial.com/papers/6a1758b43275b64d0e6e892b — DOI: https://doi.org/10.1016/j.ctim.2025.103288
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