Study of Information Processing in Neural Systems by Measuring EEG,EOG and EMG.

通过测量脑电图、眼电图和肌电图研究神经系统的信息处理。

基本信息

批准号：
61550296
负责人：
ISHII Naohiro
金额：
$ 1.34万
依托单位：
Nagoya Institute of Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (C)
财政年份：
1986
资助国家：
日本
起止时间：
1986 至 1987
项目状态：
已结题

项目摘要

We can observe neural information by measuring the surface activity of electrical potentials, which is EEG( electroencephalography ), EOG( electrooculogram ) and EMG ( electromyogram ). We have been studying the research of quantitative analysis of sleeping and consciousness by measuring the EEG, EOG and EMG at the same time. In this study, we developed the analysis method to extract the more detail information from the surface body. In the frequency domain, power spectral methods are often used by dividing the total frequency range into several bandwidths. In the time domain, wave recognition method has been developed to characterize he EEG waves as an extension of the xero-crossing method. The wave recognition method is improved to pick up the direction of the EEG wave. The wave direction implies computation of the amplitude of the EEG wave from the values of the peak and the bottom of the wave. The method developed here improves the recognition rate of waves. Next, the EEG data have been sampled under the 100 Hz sampling, which is extremely slow sampling in the value. But we could measure correctly the EEG wave frequency , by introducing an interpolation function after the 100Hz sampling. This method reduces the data amount greatly. Thus overnight sleeping data can be stored in the computer and processed easily. These studies are published as paper titles,"Measurement method for frequency analysis of spindle waves in EEG", "Studies of wave recognition method in EEG analysis".

我们可以通过测量电位的表面活动来观察神经信息，这就是EEG（脑电图）、EOG（眼电图）和EMG（肌电图）。我们一直在研究通过同时测量脑电图、眼电图和肌电图来定量分析睡眠和意识的研究。在本研究中，我们开发了从表面体中提取更多详细信息的分析方法。在频域中，通常通过将总频率范围划分为多个带宽来使用功率谱方法。在时域中，波识别方法已被开发来表征EEG波，作为xero-crossing方法的扩展。改进了波识别方法以拾取脑电波的方向。波方向意味着根据波的峰值和谷值计算 EEG 波的幅度。这里开发的方法提高了波浪的识别率。接下来，脑电图数据是在100 Hz采样下进行采样的，这在数值上是非常慢的采样。但我们可以通过在100Hz采样后引入插值函数来正确测量脑电波频率。该方法大大减少了数据量。因此，夜间睡眠数据可以存储在计算机中并易于处理。这些研究以论文标题《脑电图纺锤波频率分析的测量方法》、《脑电图分析中波识别方法的研究》发表。