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Electrical signals from the human body are constantly the focus of research, searching for a better understanding of physiological events, discovering early signs of disease, and improving life quality. Developing devices that allow research beyond the usual requirements and allow easy adaptation regarding the system's acquisition, conditioning, and processing parts could be a step toward better understanding some behaviours. Therefore, this work focused on designing a system that goes from the discrete components to a graphical interface, allowing user control of parameters to set the acquisition in a way that favours the specific signal of interest. The resulting system allows the user to change parameters regarding the analogue and digital filtering, sampling frequency and events detection, namely R-peaks, in the electrocardiogram, to estimate heart rate and its frequency fluctuation, and muscle contraction in electromyogram, to analyse contraction strength and muscle fatigue. The system also allows the data to be stored, aiming to generate datasets to further process the data in AI-based algorithms.