An Improved Self-Adaptive Filter Based on LMS Algorithm for Filtering 50Hz Interference in ECG Signals

Weiting, Yuan; Zhou, Runjing

doi:10.1109/icemi.2007.4351057

Cited by 19 publications

(9 citation statements)

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“…An ECG signal can be used to measure the rate and abnormality (if present) of heartbeats, to detect disease or damage to the heart, and also to observe the effect of drugs or devices which alter the heart activity. Generally, the amplitude range of a normal ECG signal is 10 mV to 5 mV and the frequency range is 0.05-100 Hz [1]. In recent times, automated ECG analysis has gained immense popularity in the area of telemedicine [2].…”

Section: Introductionmentioning

confidence: 99%

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Fractal and EMD based removal of baseline wander and powerline interference from ECG signals

Agrawal¹,

Gupta²

2013

Computers in Biology and Medicine

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Section: Introductionmentioning

confidence: 99%

“…A number of methods have been proposed to remove baseline wander noise from ECG signals [1,[7][8][9][10][11][12][13][14][15][16][17][18][19]. A classical method of baseline wander noise removal is high pass filtering with cut off frequency of 0.7 Hz [10].…”

Section: Introductionmentioning

confidence: 99%

Fractal and EMD based removal of baseline wander and powerline interference from ECG signals

Agrawal¹,

Gupta²

2013

Computers in Biology and Medicine

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“…The activity of heart can be monitored by the electrodes (or leads) placed at different positions on the human body. Usually, for a normal ECG signal, the frequency range is 0.05-100 Hz and the amplitude lies in the range from 10μV to 5mV [1]. An ECG can be used to assess the heart rhythm, for diagnosis of heart abnormalities, and also for the purpose of telemedicine.…”

Section: Introductionmentioning

confidence: 99%

Projection operator based removal of baseline wander noise from ECG signals

Agrawal

Gupta

2013

2013 Asilomar Conference on Signals, Systems and Computers

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In this paper, we propose a novel method for baseline wander removal from a noisy ECG signal. We use projection operator based approach to remove baseline wander noise from the ECG signal. The noise subspace is generated using sample functions of the first order fBm processes characterizing baseline wander noise. The orthogonal projection of noisy ECG signal onto the noise subspace provides an estimate of baseline wander noise. The estimated noise is subtracted from the noisy input signal to obtain noise-free ECG signal. Performance comparison with other baseline wander removal methods shows the efficacy of the proposed method.

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“…However, such filter banks would cause information loss of target signals since the frequency range largely overlaps for the biopotential signals and power line interference [35]. Hence, a number of improved filtering techniques have been proposed over the years to minimize interferences in biopotential recordings [36][37][38][39][40]. For instance, Tomasini et al used an adaptive power line interference filter to estimate the fundamental frequency and harmonics of power line interference, and the estimated interference was subtracted from the noise-affected biosignal [22].…”

Section: Introductionmentioning

confidence: 99%

Effective Biopotential Signal Acquisition: Comparison of Different Shielded Drive Technologies

et al. 2018

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Biopotential signals are mainly characterized by low amplitude and thus often distorted by extraneous interferences, such as power line interference in the recording environment and movement artifacts during the acquisition process. With the presence of such large-amplitude interferences, subsequent processing and analysis of the acquired signals becomes quite a challenging task that has been reported by many previous studies. A number of software-based filtering techniques have been proposed, with most of them being able to minimize the interferences but at the expense of distorting the useful components of the target signal. Therefore, this study proposes a hardware-based method that utilizes a shielded drive circuit to eliminate extraneous interferences on biopotential signal recordings, while also preserving all useful components of the target signal. The performance of the proposed method was evaluated by comparing the results with conventional hardware and software filtering methods in three different biopotential signal recording experiments (electrocardiogram (ECG), electro-oculogram (EOG), and electromyography (EMG)) on an ADS1299EEG-FE platform. The results showed that the proposed method could effectively suppress power line interference as well as its harmonic components, and it could also significantly eliminate the influence of unwanted electrode lead jitter interference. Findings from this study suggest that the proposed method may provide potential insight into high quality acquisition of different biopotential signals to greatly ease subsequent processing in various biomedical applications.

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An Improved Self-Adaptive Filter Based on LMS Algorithm for Filtering 50Hz Interference in ECG Signals

Cited by 19 publications

References 0 publications

Fractal and EMD based removal of baseline wander and powerline interference from ECG signals

Fractal and EMD based removal of baseline wander and powerline interference from ECG signals

Projection operator based removal of baseline wander noise from ECG signals

Effective Biopotential Signal Acquisition: Comparison of Different Shielded Drive Technologies

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