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Automatic detection of rapid eye movements by discrete wavelet transform
Author(s) -
Tsuji Yoichi,
Satoh Hideki,
Itoh Nobuyuki,
Sekiguchi Yuuki,
Nagasawa Kazuyuki
Publication year - 2000
Publication title -
psychiatry and clinical neurosciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.609
H-Index - 74
eISSN - 1440-1819
pISSN - 1323-1316
DOI - 10.1046/j.1440-1819.2000.00676.x
Subject(s) - discrete wavelet transform , wavelet , artificial intelligence , eye movement , electrooculography , wavelet transform , haar wavelet , computer vision , computer science , pattern recognition (psychology) , haar , stationary wavelet transform , function (biology) , evolutionary biology , biology
In order to detect rapid eye movements (REM) automatically, the Discrete Wavelet Transform was applied to each 8‐s segment of electrooculogram (EOG) data for 30 min of 8 h of normal sleep. The Haar function was used as an analysing wavelet because this function is similar to the REM waveform. By shifting the phase of the analysing wavelet by π/4 of the function, 96% of REM could be detected. The artifacts caused by body movements could be detected simultaneously by this method. Computing time required for the detection of REM was only 11 s for 30 min EOG data.