A simple filter circuit for denoising biomechanical impact signals

Area of Science:

• Biomedical Engineering
• Signal Processing
• Applied Mathematics

Background:

• Accurate estimation of biomechanical signal acceleration is crucial for analysis.
• Non-stationary signals and noise present significant challenges for traditional filtering methods.
• Existing low-pass filters often struggle with time-varying signal characteristics.

Purpose of the Study:

• To develop a simple and effective scheme for denoising non-stationary biomechanical signals.
• To accurately estimate the second derivative (acceleration) of these signals.
• To improve upon the robustness and efficiency of conventional filtering techniques.

Main Methods:

• Filtering biomechanical signals in fractional Fourier domains.
• Utilizing well-known low-pass filters to create a time-varying cut-off threshold.
• Leveraging the relationship between fractional Fourier transform and time-frequency representations for algorithm design.

Main Results:

• The proposed method effectively denoises non-stationary biomechanical signals.
• The algorithm accurately estimates signal acceleration.
• The filtering scheme demonstrates superior robustness against noise compared to conventional low-pass filters.
• The implemented filter circuit is efficient, using only low-order filters and benefiting from low computational complexity.

Conclusions:

• The fractional Fourier domain filtering scheme provides an effective solution for denoising non-stationary biomechanical signals.
• The method offers a robust and computationally efficient approach for acceleration estimation.
• This technique represents an advancement over traditional filtering methods in biomechanical signal analysis.