光谱图
短时傅里叶变换
心音图
时频分析
滑动窗口协议
信号(编程语言)
计算机科学
语音识别
傅里叶变换
傅里叶分析
模式识别(心理学)
人工智能
声学
数学
窗口(计算)
计算机视觉
物理
滤波器(信号处理)
操作系统
数学分析
程序设计语言
作者
Abdelghani Djebbari,F. Bereksi Reguig
标识
DOI:10.1109/icecs.2000.913008
摘要
In this paper, we present results of the PCG (phonocardiogram) signal analysis using the STFT (Short-Time Fourier Transform). Because of the nonstationarity of the PCG signal, it is important to maintain an analysing time window as short as possible to guaranty the stationarity hypothesis over small analysed segments. This will reduce the frequency resolution of the resulting spectrogram. However by adjusting the sliding time window, we can reach an acceptable result. The spectrogram is calculated by using first, short length sliding window to generate a temporal representation of the PCG, then longer length sliding window in order to generate a spectral representation of the PCG power. The resolution in such representations depend directly on the sliding window length. The temporal representation allows heart sounds and cardiac cycle durations to be measured. Whereas the spectrum, assuming a good frequency resolution, allows spectral characterisation of each heart sound. The results we obtained on normal PCG signal, show that the STFT analysis provides a clear comprehension of the cardiac events when the spectra are represented in the time-frequency scale basis. Such results confirm the normal aspects of the analysed PCG signal.
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