Development of a Low-cost Real-time Bioelectrical Signal Acquisition Module

Abstract

Human Machine Interface (HMI) is gaining attention in the healthcare field and the acquisition of different bioelectrical signals simultaneously through one portable system remains still under active investigations, which can help further advancement of HMI. In this paper, we developed a system that can capture different respiratory signals (e.g. Electrocardiogram (ECG), Electromyogram (EMG) and Electrooculogram (EOG)) by utilizing low-cost hardware facilities in developing countries. The designed system was tested by capturing signals from human skin surfaces using electrodes. While developing such a system, we procured these signals by placing disposable skin surface electrodes on the desired positions of the body, employing customized electronic hardware. For computer interfacing and signal analysis, Arduino Uno was used in terms of Analog to Digital Conversion (ADC), whereas, a model developed in MATLAB Simulink for envisioning and saving the data in actual time. Our Simulink model designed using low-pass filters through the filter design toolbox selected different cut-off frequencies considering various bio-signals. Furthermore, a program is developed to store the signal data in MATLAB workspace for performing specific analyses. The developed prototype tested on human subjects proved to be efficient to integrate into assistive technologies.