A New Method for Analyzing Transition Heart Rate Variability Using Wavelet Transforms.
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概要
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Heart rate variability data contains well-defined rhythms which have been shown to contain physiological information. The spectral components of heart rate variability data can be used clinically to assess the autonomic nervous system. The FFT, MEM and AR methods are used for calculating power spectral density functions, and, a stationary time series is needed for several minutes. These methods cannot analyze the transient change in frequency information. The wavelet transforms shows good time and frequency resolution, especially for the analysis of non-stationary signals. In wavelet transforms, a time series for 20 or 30 seconds is necessary. Therefore, frequency information is not obtained for 20 or 30 seconds from the starting point of the measurement. Moreover, the frequency information around the transient change is the average value before and after the change. We proposed a method for extracting accurate frequency information from the starting point of the measurement or from the part of transient change, when the heart rate variability is analyzed using wavelet transforms. The effectiveness of this method was confirmed by applying our results to the simulation data and R-R interval time series data. The proposed method determined the transitional change in the frequency information, which is not possible using classical methods. The transitional change in the autonomous nerve function were estimated using our method.
- 一般社団法人 日本生体医工学会の論文
一般社団法人 日本生体医工学会 | 論文
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