Projects
Human ECG Signal Processing
This project, part of my Circuits and Signals: Biomedical Applications course, focused on capturing, filtering, and analyzing human electrocardiogram (ECG) signals. My lab partner and I designed an ECG acquisition system, applying analog filtering and digital signal processing to extract clean cardiac waveforms.
Using an instrumentation amplifier, we captured raw ECG signals from surface electrodes and refined them with high-pass and low-pass filters to remove noise and interference. The conditioned signal was then digitized using the NI USB-6001 A/D converter for further analysis in MATLAB.
In MATLAB, we applied Fourier analysis and digital filtering, including a notch filter to eliminate 60 Hz power line interference. We also extracted key physiological insights, such as heart rate estimation using peak detection and frequency-domain analysis.
Takeaways:
- Worked closely with my lab partner to design, test, and troubleshoot an ECG amplifier circuit for processing heart rate signals.
- Improved proficiency with the oscilloscope, function generator, and digital multimeter (DMM) to measure, visualize, and analyze signals effectively.
- Utilized MATLAB programming for signal analysis, including filtering and Fourier transforms.
- Implemented filtering techniques to reduce noise and enhance signal clarity.
- Gained hands-on experience with signal acquisition and processing tools used in biomedical applications.
Teamwork and hands-on practice were key to mastering signal analysis techniques and refining my ability to work with lab instrumentation in real-world scenarios.
Project Images
High pass and low pass filter combined circuit diagram
ECG Circuit implemented on a protoboard
MATLAB FFT plot of ECG signal, based on the 1.55Hz peak, you can estimate my teammate's heart rate to be 60s × 1.55Hz = 93bpm, within a normal resting range