Development of a Multichannel Bioinstrumentation System for Human-Computer Interface Applications

Year 2022, Volume: 12 Issue: 1, 182 - 193, 01.03.2022

Poyraz Alper Öner , Serkan Gürkan , Mustafa Karapınar , Seydi Doğan

https://doi.org/10.21597/jist.998055

Abstract

A multi-channel measurement system used to measure electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG) and electrooculogram (EOG) biosignals has been designed and prototyped. The designed system has 16 configurable measurement channels. Of the 16 channels the developed system has, 8 have been designed for EEG, 2 for EMG, 2 for EOG, 1 for ECG measurements, the remaining 3 have been reserved as backup channels. In circuit design, biosignal amplifier design principles have been applied by taking into account the characteristics of the biosignal to be measured for each channel, such as bandwidth, frequency, amplitude, noise level. Modules such as instrumentation amplifier, filter, DC suppression unit, amplifier, DC level determination unit, analog-digital converter, optical isolation unit, power supply have been designed to perform biosignal measurements through these channels. Biosignals measured by the developed system can be shifted to the desired threshold level with the help of the analog output reference voltage, converted to digital data 10-bit resolution and transferred to the computer environment in real time. The data transferred to the computer can be used in C#, Excel, MATLAB, and LabVIEW platforms. The novelty of the developed system is that any of the four desired biosignal types can be measured from any channel. In addition, another feature of the system is that it can work with real-time data without being dependent on the databases serving for human-computer interface applications. In experimental studies with some researchers for the performance tests of the system, ECG, EEG, EMG and EOG signals have been recorded with different module configurations, and signal processing stages were carried out to be used for human-computer applications.

Keywords

Biomedical engineering, biosignal measurement, biomedical instrumentation, human-computer interfaces, human-machine interfaces, embedded system

Supporting Institution

BALIKESİR UNİVERSİTESİ BAP

Project Number

2017/169

Thanks

This study was supported by the Balıkesir University Research Fund (project number 2017/169). Authors would like to thank to Turkish Academy of Sciences (TUBA) for partial support.

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