Adaptive band-pass filter (ABPF) for tremor extraction from inertial sensor data

Area of Science:

• Biomedical Engineering
• Neuroscience
• Rehabilitation Technology

Background:

• Pathological tremor significantly impacts daily living activities.
• Functional electrical stimulation (FES) shows promise for tremor cancellation.
• Real-time tremor estimation is crucial for effective FES feedback systems.

Purpose of the Study:

• To present a novel adaptive band-pass filter (ABPF) for real-time tremor estimation.
• To evaluate the performance of the ABPF against established methods.
• To demonstrate the feasibility of using ABPF for FES tremor cancellation.

Main Methods:

• Developed an adaptive band-pass filter (ABPF) for zero-phase lag tremor estimation.
• Utilized inertial sensor data for tremor analysis.
• Compared ABPF performance with the weighted-frequency Fourier linear combiner (WFLC) using synthetic and patient data.

Main Results:

• The ABPF demonstrated comparable performance to the WFLC in tremor extraction.
• ABPF showed faster adaptation capabilities.
• The proposed filter exhibited higher accuracy and robustness in tremor estimation.

Conclusions:

• The adaptive band-pass filter (ABPF) is a simple, implementable, and effective tool for real-time tremor estimation.
• ABPF shows potential for enhancing functional electrical stimulation (FES) systems for tremor management.
• This method offers a promising approach for improving the quality of life for individuals with pathological tremor.