Stand-alone segmentation of blood flow pulsatility measured with diffuse correlation spectroscopy

Area of Science:

• Biomedical Optics
• Physiological Monitoring
• Signal Processing

Background:

• Diffuse correlation spectroscopy (DCS) measures blood flow.
• Accurate blood flow index (BFI) segmentation is crucial for waveform analysis.
• Current methods often rely on exogenous physiological references.

Purpose of the Study:

• To develop and validate a stand-alone BFI pulse segmentation method using wavelet analysis.
• To assess the feasibility of quantifying BFI waveform morphology without external references.
• To evaluate the agreement between wavelet-based and traditional segmentation methods.

Main Methods:

• A novel wavelet-based segmentation technique was applied to the BFI signal.
• The method utilizes the signal's cardiac frequency component.
• BFI waveform morphology was quantified in 30 healthy adults and compared to results using a blood pressure reference.

Main Results:

• The wavelet-based segmentation method successfully identified BFI pulses.
• Waveform morphology features derived from the wavelet approach showed strong agreement with those obtained using a blood pressure reference.
• This indicates high reliability of the stand-alone method.

Conclusions:

• A stand-alone wavelet-based BFI segmentation method is effective for diffuse correlation spectroscopy.
• This approach offers a promising alternative for quantifying BFI waveform morphology.
• It simplifies the measurement process by removing the need for exogenous references.