ECG (Electrocardiogram) Design Project

Jude K.

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ECG (Electrocardiogram) Design Project

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ECG Electrocardiogram, Design Project, circuit, instrumentation amplifier, passive band pass filter

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This project designed and built a circuit to get the ECG signal, which consisted of the instrumentation amplifier to amplify the ECG signal, a 60 Hz notch filter for removing power line noise, and a passive band-pass filter tuned to the typical ECG frequency range. The circuit was integrated, and the human subjects gave an ECG signal that was, in turn, digitized and processed via the Arduino microcontroller. The critical difficulties were applying the filter frequencies per specification and making it less noisy. The ultimate circuit performance was to the specifications, but some experimental values for component values and frequencies did not match the theoretical ones. Enhancements, including using higher precision components, additional filtering techniques, and design improvements, are suggested to increase the accuracy, noise immunity, and morphological fidelity of reproduced ECG waveforms. This project I did by myself taught me the practical problems with signal acquisition and processing.

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[...] "Characterization of T wave amplitude, duration and morphology changes during hemodialysis: Relationship with serum electrolyte levels and heart rate." IEEE Transactions on Biomedical Engineering 68.8 (2020): 2467-2478. Li, Dayi, et al. comprehensive review of improving power quality using active power filters." Electric Power Systems Research 199 (2021): 107389. Subba, Tanuja, and Tejbanta Chingtham. "Comparative Analysis of Machine Learning Algorithms with Advanced Feature Extraction for ECG Signal Classification." IEEE Access (2024). [...]

[...] "Dispersion of ventricular repolarization: Temporal and spatial." World Journal of Cardiology 12.9 (2020): 437. Ribeiro, Antônio H., et al. "Automatic diagnosis of the 12-lead ECG using a deep neural network." Nature Communications 11.1 (2020): 1760. Almuhanna, Mohammed Ahmed, et al. "Tachycardia Evaluation and its Management Approach, Literature Review." World Journal of Environmental Biosciences 11.1-2022 (2022): 4-8. Uwaechia, Anthony Ngozichukwukas, and Dzati Athiar Ramli. comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges." IEEE Access 9 (2021): 97760-97802. Bukhari, Hassaan A., et al. [...]

[...] Yet, such algorithms can be used for automated feature extraction, beat detection, and classifying arrhythmias This is crucial in comparing the received ECG signals with the norms established in clinics and through literature to validate the accuracy and clinical significance of the findings. This would be an advantage in pursuing coordinated attempts by medical personnel and a higher number of participants for testing. Such alliances can provide precious feedback about the system's performance, point out where to improve, and ensure that the results are of sufficient quality for diagnostic and therapy purposes. Reference Manju, B. R., and B. Akshaya. "Simulation of pathological ECG signal using transform method." Procedia Computer Science 171 (2020): 2121-2127. [...]

[...] Filters with notch features have eliminated any 60 Hz noise that power lines and other electrical interference sources may have caused. The bandpass filter picked up the significant frequency components of the ECG signal, commonly from 0.05 Hz to 100 Hz while at the same time reducing the unwanted frequency components not within the selected range. A significant problem during the design and testing process was the inability to accurately get the correct gain and filter characteristics with the available resistor and capacitor values. [...]

[...] These approaches may aid in pattern recognition, waveform analysis, and the location of features or abnormalities within the ECG signal. Nonetheless, manual interpretation of the obtained data by trained healthcare experts is still indispensable for correct diagnosis and choice of treatment regimen. The figure below illustrates ECG waveforms representing normal and abnormal patterns. Although the ECG is an effective diagnostic tool, it is vital to consider that it only assesses the heart's electrical activity. Other clinical assessments and tests should be added to the diagnosis for a complete picture of the patient's cardiovascular health. [...]

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