A low-pass differentiation filter based on the 2nd-order B-spline wavelet for calculating augmentation index

Area of Science:

• Biomedical Engineering
• Cardiovascular Physiology
• Signal Processing

Background:

• Precise identification of the shoulder point is crucial for calculating the augmentation index (AIx).
• Current methods, like numerical differentiation, for shoulder point extraction are computationally intensive and lack noise resistance.
• Existing techniques pose challenges for accurate AIx calculation in clinical settings.

Purpose of the Study:

• To develop a novel 2nd-order B-spline wavelet-based method for calculating AIx.
• To compare the efficacy and robustness of the proposed method against numerical differentiation and the Savitzky-Golay digital differentiator (SGDD).
• To evaluate the anti-noise capability of the new AIx calculation method.

Main Methods:

• A new AIx calculation method utilizing a 2nd-order B-spline wavelet was developed.
• The proposed wavelet method was compared with numerical differentiation and SGDD.
• All methods were applied to pulse waveforms from 60 healthy subjects, with simulated noise added to assess performance.

Main Results:

• The proposed B-spline wavelet method showed high correlations with numerical differentiation (r=0.998 carotid, r=0.997 radial) and SGDD (r=0.995 carotid, r=0.993 radial).
• The new method exhibited significantly better noise tolerance when simulated noise (>10Hz) was added to pulse waveforms.
• The proposed method proved advantageous in noise resistance compared to the other two techniques.

Conclusions:

• The 2nd-order B-spline wavelet method provides a fast and accurate approach for AIx calculation.
• This novel method offers superior anti-noise capabilities, enhancing its reliability for cardiovascular disease assessment.
• The findings suggest this B-spline wavelet technique is a promising advancement for pulse waveform analysis.