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CleanEMG--power line interference estimation in sEMG using an adaptive least squares algorithm.

G D Fraser¹, A D C Chan, J R Green

¹Department of Systems & Computer Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|January 19, 2012

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This study introduces an adaptive least squares algorithm to estimate and remove power line interference from surface electromyography (sEMG) signals without needing a reference input. The method accurately removes interference, even at low signal-to-noise ratios.

Area of Science:

Biomedical Engineering
Signal Processing
Electrophysiology

Background:

Power line interference is a common artifact in surface electromyography (sEMG) signals.
Accurate sEMG signal acquisition is crucial for reliable clinical assessment and research.
Existing methods for interference removal often require a reference signal, limiting their applicability.

Purpose of the Study:

To develop and evaluate an adaptive least squares algorithm for estimating power line interference in sEMG signals.
To enable power line interference removal without requiring a reference input.
To assess the algorithm's accuracy across various frequencies and signal-to-noise ratios (SNRs).

Main Methods:

An adaptive least squares algorithm was designed to estimate power line interference directly from the sEMG signal.

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The estimated interference was subtracted from the original sEMG signal to remove the artifact.

Simulated sEMG signals were used to evaluate the algorithm's performance under controlled conditions.

Main Results:

The algorithm successfully estimated power line interference without a reference signal.
Accurate estimation of power line interference was achieved for signal-to-noise ratios below 15 dB.
The SNR estimation error at 15 dB was quantified as 14.7995 dB ± 1.6547 dB.

Conclusions:

The proposed adaptive least squares algorithm provides an effective method for estimating and removing power line interference from sEMG signals.
This technique is particularly valuable in scenarios where a reference input is unavailable.
The algorithm demonstrates robust performance, maintaining accuracy even in noisy conditions.