Cross-Bifrequency Analysis of Cardiorespiratory Interactions at Rest and Zen Meditation
International Conference on Systems and Informatics November 1, 2019 DOI: 10.1109/icsai48974.2019.9010252 (opens in new tab) via Semantic Scholar
Summary
AI-generated from the abstractA modified self-organizing map (IwSOM) that weights input features differently is used to analyze cross-bifrequency maps of heart rate and respiration during Zen-meditation and resting states. The cross-bispectral analysis quantifies quadratic phase coupling between cardiac and respiratory oscillators. IwSOM classification shows that the rest session of the control group is characterized by coupling frequencies where respiratory rate resonates with heart rate at 0.05 Hz. Zen-meditation exhibits strong resonance between heart rate and respiration in the same low frequency range, indicating distinct cardiorespiratory interaction patterns during meditation compared to rest.
Study at a glance
| Characteristics | Observational study Peer reviewed |
|---|---|
| Population | Human participants in Zen-meditation and resting states |
| Intervention | Zen-meditation |
| Keywords | Computer science Mathematics Psychology |
| Key finding | Zen-meditation produces strong resonance between heart rate and respiration in the low frequency range (0.05 Hz), while the control group's rest session shows coupling at the same frequency. |
Abstract
SOM (self-organizing map) is modified to encode the cross-bifrequency map that evaluates the cardiorespiratory interactions at Zen-meditation and resting states. The effectiveness of meditation on stress manipulation has aroused the attention of researchers. Cardiovascular and respiratory systems are very important in manipulating both mental and physical health in the stressful environment. Cross-bispectral analysis, applied to heart-rate (HR) and respiratory (RP) sequences, quantifies the degree of phase coupling between different spectral components of two signals. The resulted cross-bifrequency map reveals the property of quadratic coupling between two oscillators, the cardiac and respiratory systems. Conventional SOM weights equally each attribute of the input (feature) vector. However, some attributes of the input vector may play a more decisive role in recognition task. We accordingly propose the input-weighted SOM (IwSOM). According to the IwSOM classification, rest session of control group is characterized by a series of coupling frequencies of which the respiratory rate (RR) is in resonance with HR at 0.05 Hz. The Zen-meditation bifrequency exhibits strong resonance between HR and RP in the same low frequency range.