Key result
Arduino Uno and AD620 prototype detects ECG and EMG signals with ~20% mean error.
Why the study?
This study aimed to design and test a simple, portable system using an Arduino Uno microcontroller and an AD620 instrumentation amplifier to detect, amplify, and analyze low-amplitude EMG and ECG biological signals.
Answers are grounded in this paper and cite their sources.
This hardware engineering study demonstrates that a low-cost Arduino Uno and AD620 amplifier prototype can successfully acquire basic ECG and EMG signals for educational and non-clinical prototyping purposes.
This study aims to design and test a simple system for measuring electromyogram (EMG) and electrocardiogram (ECG) signals using an Arduino Uno microcontroller and the IC AD620 instrumentation amplifier. The system was developed to detect, amplify, and analyze low-amplitude biological signals. The development process included literature review, component selection, circuit and PCB design, and performance testing of the prototype, which involved robustness, reliability, sensitivity, voltage testing, and error analysis using MAE, MSE, RMSE, and MAPE parameters. The test results indicate that the system is capable of detecting EMG signals with amplitudes ranging from 0.1–1.5 mV and ECG signals from 0.1–1.0 mV. The system utilizes a cascaded amplification with a total gain of 1000 times, consisting of the AD620 instrumentation amplifier (100×) and the LM358 operational amplifier (10×). A bandpass filter with a cutoff frequency of 2.2 Hz (high-pass) and 480 Hz (low-pass) was used effectively to reduce noise. The error values obtained MAE of 0.66 V, MSE of 0.438 V², RMSE of 0.662 V, and MAPE of 19.54% indicate that the device performs reasonably well for an initial prototype. The measured values of Vpp and Vrms were consistent with theoretical calculations, recorded at 9.8 V and 3.46 V respectively, showing negligible error deviations within the measurement instrument's resolution limits. The prototype demonstrated stable performance in environmental conditions ranging from 25–40°C with up to 70% humidity and operated normally after 20 test cycles. These results suggest that the system has potential for further development as a portable health monitoring device.
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Setiawan et al. (2026) studied Electromyogram (EMG) and electrocardiogram (ECG) biosignal acquisition. Portable biomedical instrumentation prototype using Arduino Uno microcontroller, AD620 instrumentation amplifier (100x gain), LM358 operational amplifier (10x gain), and bandpass filter (2.2-480 Hz) vs. Theoretical circuit calculations and oscilloscope voltage measurements was evaluated on Signal detection capability and voltage measurement accuracy (MAE, MSE, RMSE, MAPE, Vpp, and Vrms). The Arduino Uno and AD620 prototype detected EMG and ECG signals with 1000x gain, achieving an MAE of 0.66 V, RMSE of 0.662 V, and MAPE of 19.54%.
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