Noninvasive Diagnosis of Cerebrovascular Diseases Based on the Characteristics of Blood Flow Noise
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概要
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Intracranial blood flow noise measuring and analyzing system were developed to detect the cerebrovascular diseases such as aneurysm, stenosis and occlusion in their early stage. To realize the effective measuring of the sound known as the 'bruit,' dedicated PVDF-film based sensor working on the closed eyelid was designed. FFT spectrums and Wigner distributions were used as analyzing methods to clarify both the precise spectrum and the time variance of the signals. Thirty normal people without any history of cerebrovascular disease were tested with the system to estimate the characteristics of the background noise. Thirteen patients, including eight stenosis, four aneurysm and one occlusion, were studied with the system. FFT spectral differences between patient and normal existed over the frequency range from 0.5 kHz to 1.2 kHz. In this range apparent increases of the signal components' power were observed for the patients. Numerically, this tendency was confirmed by the power difference between 750 Hz and 1.5 kHz, which could be the possible index of the existence diagnosis for cerebrovascular diseases. The shape of the FFT spectral pattern showed some difference between stenosis and aneurysm. In stenosis cases, it seemed that there existed the flat level from 0.4 kHz to 1.2 kHz, while in aneurysm cases the power decreases smoothly as frequency increases from the peak around 0.7 kHz. Time variance of the bruit according to the cardiac cycle could be seen in the cases of stenosis from 30% to 50%, but not in the cases from 40% to 90%. This fact suggested the possibility to diagnose the extent of the stenosis. In most cases, recognizable spectral peak around 0.7 kHz were observed. Although the physical meanings of those peaks were not so clear, still it was the apparent characteristics and might be including important information.
- 一般社団法人電子情報通信学会の論文
- 1995-12-25
著者
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Kobayashi Kenji
Faculty Of Agriculture Nagoya University
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Hasegawa Jun
Faculty Of Engineering Takushoku University
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