Design of ECG Signals Filter Circuit Based on OTA Filtering
DOI:
https://doi.org/10.54097/hset.v32i.4983Keywords:
Electrocardiograph (ECG) signals, operational transconductance amplifier (OTA), 50Hz power line interferenceAbstract
The ECG signal reflects the physiological characteristics of the heart to a certain extent and is an extremely important clinical reference for the diagnosis, treatment, and prevention of cardiovascular diseases. However, the ECG signal is affected by various noises during the acquisition process, especially the 50Hz noise from power lines which makes the diagnosis and analysis of ECG difficult. In this paper, a transconductance amplifier with strong practical applications is proposed and designed to filter out interference from ECG signals in power lines, based on the characteristics of ECG signals and the ability of differential signals to effectively resist external common-mode noise. This amplifier is able to effectively filter out 50Hz interference from power lines and features a high common-mode rejection ratio and low power consumption, in addition to using relatively few components and low production costs.
Downloads
References
Durgam, R., Tamil, S., and Raj, N. Design of Low Voltage Low Power High Gain Operational Transconductance Amplifier. U.Porto Journal of Engineering, 2021.7(4):103–110.
Kumari, N. Design and Analysis of Two-Stage Operational Transconductance Amplifier with Compensation Capacitor. Engineering and Technology Journal, 2017. 28.
Zhang, J., Zhang, H., Sun, Q., and Zhang, R. A Low-Noise, Low-Power Amplifier With Current-Reused OTA for ECG Recordings. IEEE Transactions on Biomedical Circuits and Systems, 2018. 12(3):700–708.
K., C., & S., B. A Survey on various Machine Learning Approaches for ECG Analysis. International Journal of Computer Applications, 2017.163(9): 25–33.
Hassanien, A. E., Kilany, M., and Houssein, E. H. ECG signals classification: a review. International Journal of Intelligent Engineering Informatics. 2017. 5(4): 376.
Kusumoto, F. ECG Interpretation: From Pathophysiology to Clinical Application (2nd ed. 2020 ed.). Springer. 2020.
Chatterjee, S., Thakur, R. S., Yadav, R. N., Gupta, L., and Raghuvanshi, D. K. Review of noise removal techniques in ECG signals. IET Signal Processing. 2020. 14(9):569–590.
BH, P. C., Raju, D., and Krishna, J. Denoising of ECG Signal Using Multi-Resolution Techniques Based On Stationary Wavelet Transformation With Different Coefficients. International Journal of Engineering and Computer Science. 2016. 456.
Mourad, N. ECG denoising based on successive local filtering. Biomedical Signal Processing and Control. 2022.73 103-431.
Stott, F. D., & Weller, C. Biomedical amplifiers using integrated circuits. Medical & Biological Engineering. 1976. 14(6): 684–687.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.







