Han Sun, Jiayang Liu, Kelilah L Wolkowicz, Xiong Zhang, B. Gluckman
{"title":"Low-Cost, USB Connected and Multi-Purpose Biopotential Recording System.","authors":"Han Sun, Jiayang Liu, Kelilah L Wolkowicz, Xiong Zhang, B. Gluckman","doi":"10.1109/EMBC.2018.8513301","DOIUrl":null,"url":null,"abstract":"Several research arenas and clinical applications are reliant on biopotential recordings, such as electroencephalography (EEG), electromyography (EMG), electrocardiography (ECG), and neural interfaces including brain computer interface (BCI). Here, we present a low-cost, biopotential, acquisition hardware platform board (PSUEEG platform) suitable for a wide range of recording tasks. Implementations of the hardware include applications requiring 8 or 16 channels of biopotential recordings, and 3-axis accelerometer measurements, among other modalities. The device firmware allows for flexible software configuration through USB. Power and data are transmitted between the device and base computer through an electrically isolated USB. The device is compatible with a range of computer operating systems, including Windows, Linux, and OSX. Additionally, we have crafted data acquisition under a range of programming platforms, including C++, Python, MATLAB Simulink, and LabView. Notably, we have demonstrated the interface with the Matlab PsychToolbox and the popular BCI2000 platform. The acquisition system with can be used in educational and research-based applications, neural interfaces, and clinical interfaces. For education and research, we have utilized this platform in BCI work, as well as demonstrated comparable classification performance for different paradigms.","PeriodicalId":72689,"journal":{"name":"Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference","volume":"42 1","pages":"4359-4362"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EMBC.2018.8513301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Several research arenas and clinical applications are reliant on biopotential recordings, such as electroencephalography (EEG), electromyography (EMG), electrocardiography (ECG), and neural interfaces including brain computer interface (BCI). Here, we present a low-cost, biopotential, acquisition hardware platform board (PSUEEG platform) suitable for a wide range of recording tasks. Implementations of the hardware include applications requiring 8 or 16 channels of biopotential recordings, and 3-axis accelerometer measurements, among other modalities. The device firmware allows for flexible software configuration through USB. Power and data are transmitted between the device and base computer through an electrically isolated USB. The device is compatible with a range of computer operating systems, including Windows, Linux, and OSX. Additionally, we have crafted data acquisition under a range of programming platforms, including C++, Python, MATLAB Simulink, and LabView. Notably, we have demonstrated the interface with the Matlab PsychToolbox and the popular BCI2000 platform. The acquisition system with can be used in educational and research-based applications, neural interfaces, and clinical interfaces. For education and research, we have utilized this platform in BCI work, as well as demonstrated comparable classification performance for different paradigms.