Developing an electronic device for the acquisition and processing of ECG signals: a Soft Computing approach

Future healthcare needs accurate results when using specific sensors that produce exponentially attenuated signals. Due to their applicability in various applications, these sensors are of great interest, including those of a biomedical nature. This paper illustrates a biomedical device capable of analysing and capturing exponentially amortised signals in the biomedical field. The device is intended to capture and study ECG signals and consists of an analogue-digital converter (ADC), a programable connection transistor (PUT), two Thomas Tow square cells, a PGA (programable gain amplifier), and a bi-stable multivibrator with a 555 timer. The device, connected to 10 electrodes, integrates an on-board analysis system to assess the qualitative trend of the signal. ECG signal analysis is performed using a soft computing approach based on the Hybrid ResNet algorithm merged with LSTM (HRL). Finally, as in the results, the soft computing analysis of the implemented system produced encouraging results for both performance and information quality.