The effect of sounds on nonlinear measures of heart rate variability
Authors: Belova Mariia , Dimitriev Dmitry , Dimitriev Aleksei , Indeykina Olga 
Published: June 2021

Purpose and methodThis purpose of the study is to determine changes in nonlinear heart rate variability (HRV) measures during the passive listening of sounds. Twenty subjects (all women) participated in the study. Subjects listened to four sounds: (1) white noise, (2) the road traffic noise, (3) excitatory music (Diamanda Galas' Women with Steak Knives, (4) lullaby (Ba Mo Leanabh (O My Baby), Arr. William Jackson and Mackenzie, Fiona McKenzie). Emotional responses were assessed with The Affect Grid. The experiment consisted of 5 min sessions (rest and listening). RR intervals were recorded during both sessions. Fractal scaling exponents of HRV were quantified by means of the detrended fluctuation analysis (DFA). Three indices of Poincaré plots were calculated: the width of the cloud (SD1), the length of the cloud (SD2) and the ratio SD2/SD1. The complexity of attractor was assessed by calculation of correlation dimension (D2) and entropy measures (ApEn, SampEn). The following measures were derived from recurrence plot (RP): mean line length (Lmean), maximum line length (Lmax), recurrence rate (REC), determinism (DET), and Shannon entropy of line length distribution (ShanEn). We chose a tolerance level to achieve the REC =5% in accordance with a suggestion of Webber (2007). Freidman ANOVA and Wilcoxon matched‐pairs signed‐ranks tests were used to determine the significance of differences between measurements. Data are mean ± SE.ResultsExcitatory music was interpreted as unpleasant and arousing (valence: −3.07 ± 0.23; arousal: 2.00 ± 0.30). Lullaby was associated with positive emotion with negative arousal (valence: 2.19 ± 0.21; arousal: −1.53 ± 0.28). White noise induced negative valence (−2.53 ± 0.2) and positive arousal (0.95 ± 0.25), road traffic noise induced negative valence (−1.19 ± 0.24) and very low arousal (0.48 ± 0.22). The levels of valence were significantly different across the 4 stimuli (Friedman ANOVA: χ2 = 131.92, p < 0.001). This difference was present in pairs of sounds (Wilcoxon: p < 0.05). The results were the same for arousal (Friedman ANOVA: χ2 = 73.14, p < 0.001). Results of calculation of complexity measures (ApEn, SampEn, D2) exhibit non‐significant differences between rest and sound listening (p > 0.05). Sound listening produces non‐significant response changes in short‐range fractal scaling exponent of DFA (p > 0.05). There was a significant increase in long‐range fractal scaling exponent during excitatory music listening (from 0.40 ± 0.06 to 0.52 ± 0.07). During excitatory music, exposure was found significantly higher values of Lmean, Lmax, and ShanEn (p < 0.05). The RP indexes when listening to the white noise, traffic noise and lullaby showed no significant changes (Wilcoxon: p > 0.05). Poincare plot analysis of RR sequences reveals a significant decrease of the standard deviation of the instantaneous beat‐to‐beat variability data (SD1) during excitatory music listening (p < 0.01). The changes in the length of the cloud (SD2) and SD2/SD1 ratio were nonsignificant (p > 0.05).Support or Funding InformationThis abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.