Power Line Noise Reduction for Bio-Sensing Applications Using N-Path Notch Filter

Author(s):  
Nicodimus RETDIAN ◽  
Takeshi SHIMA
Author(s):  
IMTEYAZ AHMAD ◽  
F. ANSARI ◽  
U.K. DEY

Background: 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. The present paper deals with the digital filtering method to reduce 50 Hz power line noise artifacts in the ECG signal. 4th order Butterworth notch filters(BW=.5 Hz) is used to reduce 50 Hz power line noise interference(PLI) from ECG signals and its performance is compared with Adaptve filters. Method: ECG signal is taken from physionet database. ECG signal (with PLI noise of different frequencies) were processed by Butterworth notch filters of bandwidths of 0.5 Hz. Ringing Artifact is observed in the output. ECG signal (with PLI noise of different frequencies) were processed by Adaptive filters no ringing effect seen. Wavelet filtering applied clean ECG were observed. Result: Performance is compared based on SNR and MSE of Butterworth notch filter and adaptive filters and output of wallet filtering were observed. Conclusion: RLS adaptive filter give better performance as compared to IIR Butterworth and LMS. Clean ECG were seen when filtering using symlet8 wavelet was done.


2014 ◽  
Vol 543-547 ◽  
pp. 2687-2691 ◽  
Author(s):  
Ahmed Kareem Abdullah ◽  
Chao Zhu Zhang ◽  
Si Yao Lian

An enhanced blind source separation algorithm based on Stone's BSS approach is proposed, to reject the Electrooculogram (EOG) artifact and power line noise (50Hz) from simulated and real human Electroencephalography (EEG) signals without the notch filter, in order not to lose any useful EEG data around the 50-Hz. The proposed algorithm which called efficient Stones BSS (ESBSS) has been compared with four well-known BSS algorithms over super-Gaussian, sub-Gaussian artifacts and EEG signals with a linear mixture. In Original Stones BSS, the half-life values taken as a constant, typically (hlong≥100 hShort), but in the proposed work, an optimization procedure is used to change these values until the maximum temporal predictability is found. The real EEG data are taken from Imperial College London using a computerized EEG device with eight electrodes placed according to the 10-20 system.


Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2568
Author(s):  
Tadeas Bednar ◽  
Branko Babusiak ◽  
Michal Labuda ◽  
Milan Smetana ◽  
Stefan Borik

A capacitive measurement of the biosignals is a very comfortable and unobtrusive way suitable for long-term and wearable monitoring of health conditions. This type of sensing is very susceptible to noise from the surroundings. One of the main noise sources is power-line noise, which acts as a common-mode voltage at the input terminals of the acquisition unit. The origin and methods of noise reduction are described on electric models. Two methods of noise removal are modeled and experimentally verified in the paper. The first method uses a passive capacitive grounding electrode, and the second uses an active capacitive Driven Right Leg (DRL) electrode. The effect of grounding electrode size on noise suppression is experimentally investigated. The increasing electrode area reduces power-line noise: the power of power-line frequency within the measured signal is 70.96 dB, 59.13 dB, and 43.44 dB for a grounding electrode area of 1650 cm2, 3300 cm2, and 4950 cm2, respectively. The capacitive DRL electrode shows better efficiency in common-mode noise rejection than the grounding electrode. When using an electrode area of 1650 cm2, the DRL achieved 46.3 dB better attenuation than the grounding electrode at power-line frequency. In contrast to the grounding electrode, the DRL electrode reduces a capacitive measurement system’s financial costs due to the smaller electrode area made of the costly conductive textile.


2016 ◽  
Vol 8 ◽  
pp. 7-9
Author(s):  
J. Dhoulath Beegum ◽  
D. Chithraprasad ◽  
Alan Jacob ◽  
D.S. Ananthakrishnan ◽  
Gayatri Nair ◽  
...  

2019 ◽  
Vol 13 (2) ◽  
pp. 171-178
Author(s):  
Xiongwen Zhao ◽  
Hui Zhang ◽  
Liang Li ◽  
Wenbing Lu ◽  
Yi Ding ◽  
...  

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