Musical Rhythms Affect Heart Rate Variability: Algorithm and Models
Author(s) -
Huimin Wang,
ShengChieh Huang
Publication year - 2014
Publication title -
advances in electrical engineering
Language(s) - English
Resource type - Journals
eISSN - 2356-6655
pISSN - 2314-7636
DOI - 10.1155/2014/851796
Subject(s) - rhythm , arousal , valence (chemistry) , quiet , heart rate , computer science , speech recognition , psychology , cognitive psychology , communication , audiology , neuroscience , acoustics , physics , biology , medicine , quantum mechanics , blood pressure , endocrinology
There were a lot of psychological music experiments and models but there were few psychological rhythm experiments and models. There were a lot of physiological music experiments but there were few physiological music models. There were few physiological rhythm experiments but there was no physiological rhythm model. We proposed a physiological rhythm model to fill this gap. Twenty-two participants, 4 drum loops as stimuli, and electrocardiogram (ECG) were employed in this work. We designed an algorithm to map tempo, complexity, and energy into two heart rate variability (HRV) measures, the standard deviation of normal-to-normal heartbeats (SDNN) and the ratio of low- and high-frequency powers (LF/HF); these two measures form the physiological valence/arousal plane. There were four major findings. Initially, simple and loud rhythms enhanced arousal. Secondly, the removal of fast and loud rhythms decreased arousal. Thirdly, fast rhythms increased valence. Finally, the removal of fast and quiet rhythms increased valence. Our work extended the psychological model to the physiological model and deepened the musical model into the rhythmic model. Moreover, this model could be the rules of automatic music generating systems
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