Key result
Doppler signal spectral analysis reliably distinguishes femoral artery occlusion from healthy controls.
Why the study?
The ability of principal component analysis over power spectral densities to differentiate femoral artery occlusion from healthy blood flow was investigated.
Can principal component analysis of Doppler signals differentiate between patients with femoral artery occlusion and healthy subjects?
Observational
Can principal component analysis of Doppler signals differentiate between patients with femoral artery occlusion and healthy subjects?
Principal component analysis of Doppler signals is a promising signal processing method to differentiate between healthy subjects and patients with femoral artery occlusion.
May support noninvasive femoral occlusion detection; leaves open clinical utility pending validation studies.
The aim of this study is to scrutinize the ability of principal component analysis (PCA) over power spectral densities (PSD) for common femoral artery blood flow study. Doppler femoral artery signals of patients with occluded arteries and of healthy subjects were recorded. Then, power spectral densities of these signals were obtained using the Welch method. To clearly determine the difference between the groups of occluded patients and healthy subjects, PCA was implemented with patients and healthy matrices derived from PSD. The basic differences between the healthy and occluded patients were acquired with 1st principal component. The use of PCA of physiological waveforms is presented as a powerful method likely to be incorporated into future medical signal processing.
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Kara et al. (2005) conducted an observational in Femoral artery occlusion. Principal component analysis (PCA) over power spectral densities (PSD) of Doppler signals vs. Healthy subjects was evaluated on Differentiation between occluded patients and healthy subjects. Principal component analysis of power spectral densities from Doppler signals successfully differentiated between patients with femoral artery occlusion and healthy subjects.
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