A combined method to reduce motion artifact and power line interference for wearable healthcare systems

Author(s):  
Sunjoo Hong ◽  
Kiseok Song ◽  
Long Yan ◽  
Hoi-Jun Yoo
Author(s):  
IMTEYAZ AHMAD ◽  
F. ANSARI ◽  
U.K. DEY

Background: The electrocardiogram(ECG) has the considerable diagnostic significance, and applications of ECG monitoring are diverse and in wide use. Noises that commonly disturb the basic electrocardiogram are power line interference(PLI), instrumentation noise, external electromagnetic field interference, noise due to random body movements and respiration movements. These noises can be classified according to their frequency content. It is essential to reduce these disturbances in ECG signal to improve accuracy and reliability. The bandwidth of the noise overlaps that of wanted signals, so that simple filtering cannot sufficiently enhance the signal to noise ratio. It is difficult to apply filters with fixed filter co-efficients to reduce these noise. Adaptive filter technique is required to overcome this problem as the filter coefficients can be varied to track the dynamic variations of the signals. Adaptive filter based on the least mean square (LMS) algorithm and recursive least squares (RLS) algorithm are applied to noisy ECG to reduce 50 Hz power line noise and motion artifact noise. Method: ECG signal is taken from physionet database. A ECG signal (without noise) was mixed with constant 0.1 mVp-p 50 Hz interference and motion artifact noise processed with Adaptive filter based on the least mean square (LMS) algorithm and recursive least squares (RLS) algorithm. Simulation results are also shown. Performance of filters are analyzed based on SNR and MSE.


2015 ◽  
Vol 37 (1) ◽  
pp. 25-40 ◽  
Author(s):  
Lin Xu ◽  
Michael J Rooijakkers ◽  
Chiara Rabotti ◽  
Jan Peuscher ◽  
Massimo Mischi

Author(s):  
Martina Ladrova ◽  
Radek Martinek ◽  
Jan Nedoma ◽  
Marcel Fajkus

Electromyogram (EMG) recordings are often corrupted by the wide range of artifacts, which one of them is power line interference (PLI). The study focuses on some of the well-known signal processing approaches used to eliminate or attenuate PLI from EMG signal. The results are compared using signal-to-noise ratio (SNR), correlation coefficients and Bland-Altman analysis for each tested method: notch filter, adaptive noise canceller (ANC) and wavelet transform (WT). Thus, the power of the remaining noise and shape of the output signal are analysed. The results show that the ANC method gives the best output SNR and lowest shape distortion compared to the other methods.


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