Analysis of heart rate variability during meditation by a pattern recognition method

Abstract

The main objective of this study is to investigate patterns of heart rate variability during concentration meditation to understand its effects on health. Our method consisted of three major stages: Signal acquisition, Feature extraction, and Classification. The input signals are RR interval signals which were collected from 105 subjects. By K-mean clustering method, the signals could be classified into 3 clusters corresponding to state of quiet mind (Samadhi state), intermediate state, and normal state. The results indicate that meditation and ordinary quiet sitting have significantly different effects on Autonomic Nervous System. In addition, it should be noted that meditation has different effects on health depending on frequency of the resonant peak that each meditator can achieve. © 2011 CCAL.