Template Matching and Matrix Profile for Signal Quality Assessment of Carotid and Femoral Laser Doppler Vibrometer Signals

Enhancing Multichannel Laser-Doppler Vibrometry Signals with Application to (Carotid-Femoral) Pulse Transit Time Estimation

Pulse-wave velocity (PWV) can be used to quantify arterial stiffness, allowing for a diagnosis of this condition. Multi-beam laser-doppler vibrometry offers a cheap, non-invasive and user-friendly alternative to measuring PWV, and its feasibility has been previously demonstrated in the H2020 project CARDIS. The two handpieces of the prototype CARDIS device measure skin displacement above main arteries at two different sites, yielding an estimate of the pulse-transit time (PTT) and, consequently, PWV. The presence of multiple beams (channels) on each handpiece can be used to enhance the underlying signal, improving the quality of the signal for PTT estimation and further analysis. We propose two methods for multi-channel LDV data processing: beamforming and beamforming-driven ICA. Beamforming is done by an SNR-weighted linear combination of the time-aligned channels, where the SNR is blindly estimated from the signal statistics. ICA uses the beamformer to resolve its inherent permutation and scale ambiguities. Both methods yield a single enhanced signal at each handpiece, where spurious peaks in the individual channels as well as stochastic noise are well suppressed in the output. Using the enhanced signals yields individual PTT estimates with a low spread compared to the baseline approach. While the enhancement is introduced in the context of PTT estimation, the approaches can be used to enhance signals in other biomedical applications of multi-channel LDV as well.

Improving the accuracy and robustness of carotid-femoral pulse wave velocity measurement using a simplified tube-load model

Arterial stiffness, as measured by pulse wave velocity, for the early non-invasive screening of cardiovascular disease is becoming ever more widely used and is an independent prognostic indicator for a variety of pathologies including arteriosclerosis. Carotid-femoral pulse wave velocity (cfPWV) is regarded as the gold standard for aortic stiffness. Existing algorithms for cfPWV estimation have been shown to have good repeatability and accuracy, however, further assessment is needed, especially when signal quality is compromised. We propose a method for calculating cfPWV based on a simplified tube-load model, which allows for the propagation and reflection of the pulse wave. In-vivo cfPWV measurements from 57 subjects and numerical cfPWV data based on a one-dimensional model were used to assess the method and its performance was compared to three other existing approaches (waveform matching, intersecting tangent, and cross-correlation). The cfPWV calculated using the simplified tube-load model had better repeatability than the other methods (Intra-group Correlation Coefficient, ICC = 0.985). The model was also more accurate than other methods (deviation, 0.13 ms⁻¹) and was more robust when dealing with noisy signals. We conclude that the determination of cfPWV based on the proposed model can accurately and robustly evaluate arterial stiffness.