Key result
Continuous wavelet transform of pulse waveforms correlates moderately with reflected wave peaks at R ~0.68.
Why the study?
Evaluation of pulse wave analysis for early diagnosis of arteriosclerosis requires effective extraction of age- and stiffness-dependent reflected wave components.
Evaluation of a pulse wave is effective for the early diagnosis of arteriosclerosis because the pulse wave contains the reflected wave that is the age- and stiffness-dependent component. In this study, we attempted to extract the parameter reflecting the component by pulse wave analysis using continuous wavelet transform. The Morlet wavelet was used as the mother wavelet. We then investigated the relationship between the parameter and the reflected wave that was extracted from the pulse wave by our previously reported separation technique. Consequently, the result of wavelet transform of the differentiated pulse waveform changed markedly owing to age and had medium correlation with the peak of the reflected wave ( R =0.68).
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Saito et al. (2011) studied Arteriosclerosis. Time-frequency analysis of pulse wave using continuous wavelet transform was evaluated on Correlation between the wavelet transform parameter of the differentiated pulse waveform and the peak of the reflected wave (R = 0.68). Time-frequency analysis of the differentiated pulse waveform using continuous wavelet transform showed a medium correlation with the peak of the reflected wave (R = 0.68).
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