| Project/Area Number |
61550296
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | Nagoya Institute of Technology |
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Principal Investigator |
ISHII Naohiro Nagoya Institute of Technology, Fuculty of Engineering, 工学部, 教授 (50004619)
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| Co-Investigator(Kenkyū-buntansha) |
OOTA Tatsuro Nagoya University, School of Medicine, 医学部, 講師 (00109323)
IWATA Akira Nagoya Institute of Technology, Fuculty of Engineering, 工学部, 助教授 (10093098)
IKEDA Tetsuo Nagoya Institute of Technology, Fuculty of Engineering, 工学部, 教授 (50005253)
SUZUMURA Nobuo Nagoya Institute of Technology, Fuculty of Engineering, 工学部, 教授 (10023102)
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| Project Period (FY) |
1986 – 1987
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| Project Status |
Completed (Fiscal Year 1987)
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| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1987: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1986: ¥1,600,000 (Direct Cost: ¥1,600,000)
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| Keywords | EEG analysis / EOG analysis / Nonstationary Analysis / Spindle Anslysis / Wave Recognition Method / 睡眠紡錘波 / 律動性眼球運動 |
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| Research Abstract |
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".
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