Paper
30 March 2012 Music close to one's heart: heart rate variability with music, diagnostic with e-bra and smartphone
Shantala Hegde, Prashanth Shyam Kumar, Pratyush Rai, Gyanesh N. Mathur, Vijay K. Varadan
Author Affiliations +
Abstract
Music is a powerful elicitor of emotions. Emotions evoked by music, through autonomic correlates have been shown to cause significant modulation of parameters like heart rate and blood pressure. Consequently, Heart Rate Variability (HRV) analysis can be a powerful tool to explore evidence based therapeutic functions of music and conduct empirical studies on effect of musical emotion on heart function. However, there are limitations with current studies. HRV analysis has produced variable results to different emotions evoked via music, owing to variability in the methodology and the nature of music chosen. Therefore, a pragmatic understanding of HRV correlates of musical emotion in individuals listening to specifically chosen music whilst carrying out day to day routine activities is needed. In the present study, we aim to study HRV as a single case study, using an e-bra with nano-sensors to record heart rate in real time. The e-bra developed previously, has several salient features that make it conducive for this study- fully integrated garment, dry electrodes for easy use and unrestricted mobility. The study considers two experimental conditions:- First, HRV will be recorded when there is no music in the background and second, when music chosen by the researcher and by the subject is playing in the background.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shantala Hegde, Prashanth Shyam Kumar, Pratyush Rai, Gyanesh N. Mathur, and Vijay K. Varadan "Music close to one's heart: heart rate variability with music, diagnostic with e-bra and smartphone", Proc. SPIE 8344, Nanosensors, Biosensors, and Info-Tech Sensors and Systems 2012, 83440R (30 March 2012); https://doi.org/10.1117/12.916793
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Cited by 5 scholarly publications.
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KEYWORDS
Heart

Electrocardiography

Autoregressive models

Blood pressure

Brain

Diagnostics

Electrodes

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