| Project/Area Number |
11650437
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Measurement engineering
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| Research Institution | Kinki University |
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Principal Investigator |
KIKKAWA Sho Kinki University, Department of Electronic System and Information Engineering, Professor, 生物理工学部, 教授 (30075329)
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| Co-Investigator(Kenkyū-buntansha) |
YOSHIDA Hisashi Kinki University, Department of Electronic System and Information Engineering, Lecturer, 生物理工学部, 講師 (50278735)
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| Project Period (FY) |
1999 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥3,100,000 (Direct Cost: ¥3,100,000)
Fiscal Year 2002: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2001: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2000: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1999: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | mental stress / non-stationary signal / time-frequency analysis / EEG / effective bandwidth / meteorological data / entropy / レニーのα次ダイバージェンス / 多重変調点過程 / 心拍数変動 / 間隔変調パルス列 / 振幅変調 / 時間-周波数表現 / Renyiのエントロピー / 気温変動強度 / 雲画像解析 / 局所等価帯域幅 / αエントロピー / α等価帯域幅 / ストレス / 脳波アルファ波 / クレペリン検査 / 局所平均周波数(瞬時周波数) / Wigner-Ville分布 / 局所分散(時変帯域) / 時変等価帯域幅 / ストレス負荷 / 生体信号 |
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| Research Abstract |
The state of mental stress is often measured and estimated by using EEG and/or ECG. Since feature of these signals and the mental state change with time, we have to deal them as non-stationary data. Therefore we have to develop effective methods for non-stationary data analysis.
The theory of time-frequency analysis is known as a powerful tool to analyze non-stationary signals like biomedical signals.
In this project, we tried to find effective parameters by which we can extract essential characteristics of a random process and analyze and interpret the non-stationary signals. In the theory of random processes, many kind of effective bandwidths have been proposed and used very often in may branches. How ever there have been few effort to unity them. We proposed a general class of infinite effective bandwidths which includes all the essential traditional bandwidths. The class is defined by Renyi's alpha-order entropy and gives unified expression of the bandwidths. We call them alpha-order bandwidths, W-alpha. The concept of W-alpha is easily expand to non-stationary analysis. Then we proposed time varying W-alpha based of time-frequency distributions and showed that the time varying W-alpha is effective by simulation analysis. We applied them to EEG analysis measured from persons who are put mental stress by been a task of Uchida-Kraepelin. We showed the method is useful to track alpha-bandwidth of EEG.
Meteorological conditions are essential factors which affect human mental state. In the late stage of this project, we began to develop methods to analyze meteorological data, that is, image data from some meteorological satellites, temperature data, rainfall data, etc. We tried apply information theoretical concepts, like entropy and divergence to our methods. We have been showing these information theoretical concepts are very powerful to our purpose.
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