禪坐腦電波之時變頻譜的空間特性研究(II)

Abstract

主持人自 1998 即開始將醫學工程研究經驗投入於禪坐之生理、意識等現象的探 討，已有相當成果。主要以科學化方法來探討禪定過程中之腦電波特性變化，以禪 宗佛法之修行者為主要研究對象；以先進之數位訊號處理的方法理論，從大量記錄 之多通道禪坐腦電波中，進行時域、頻域分析。其中觀察到某些特性，值得進一步 探究其腦部動態機制與空間定位之關聯性。 『壓力』深切影響現代人身心健康，臨床上雖已證實「靜坐」是最佳減壓方法之 一。本實驗群過去從皮膚阻抗、心電圖和心率變異之分析結果，已觀察到禪坐之舒壓 效果；如何進一步建立科學量化機制，來評估禪坐舒壓效益，為時下迫切之課題。 為瞭解禪坐下之腦電波的頻率空間特性如何隨時間演變，本研究計畫分兩年探 討，並已於第一年間（96 年八月至97 年七月）完成實驗環境與流程之規劃，同時 已發展演算法、用之於30 通道禪坐腦電波之時變頻空特性分析。本計畫所提第二年 度之研究重點在於：（一）建立禪坐腦電波之空間特性 (MBM)，（二）探討禪坐過 程中之MBM 演變情形(MBMS)，（三）以MBM 與其他生理參數關聯性，探討禪坐 舒解壓力的機制。研究過程中，除了進行大量腦電波記錄實驗，亦將發展多元化之 數位訊號分析方法，來定性和量化MBM。

Since 1988, the principal investigator has been devoted to the research on physiological and mental/conscious phenomena under Zen meditation. A number of important results have been reported, of which we mainly focus on investigating the EEG (electroencephalograph) characteristics based on the scientific approach. Subjects of the experiment practice the Zen-Buddhist meditation. From a large amount of meditation EEG signals acquired, we characterized their temporal and spectral features by a number of advanced DSP methodologies. Some particular findings aroused our attention of further exploring the spatial foci that generate such kind of Zen brain dynamics. It has been well noticed that ‘stress’ significantly affects modern health both in physiology and psychology. Meditation has been proved in clinics to be one of the best stress-manipulation methods. Our research group has observed the stress-releasing effects of Zen meditation based on galvanometric skin resistance (GSR), electrocardiograph (ECG), and heart-rate variability (HRV). It would be an urgent task to develop a scientific, quantitative principle for evaluating the meditation effects on stress reduction. To understand the time-varying spatio-spectral phenomena of brain electrical activities under Zen-meditation state, we designed the experimental protocol and environment for collecting EEG and other physiological signals in the first-year study (August 2007 to July 2008). In addition, methods and algorithms have been developed for quantitative analysis of time varying spatio-spectral characteristics of 30-channel meditation EEG. Research plan for the following year will then be aimed at: (1) establishment of meditation brain mapping (MBM), (2) investigation of time-varying MBMs, or the MBM Scenario (MBMS), and (3) study of meditation effect on stress manipulation based on correlation between MBM and other physiological parameters. In addition to the large amount of meditation EEG recordings, this study requires the development of multi-faceted DSP methods to characterize complex MBMS.