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An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
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Experimental characterization and analysis of the BITalino platforms against a reference device

Diana Batista, Hugo Silva, Ana Fred

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 25, 2017
    PubMed

    Abstract:

    Low-cost hardware platforms for biomedical engineering are becoming increasingly available, which empower the research community in the development of new projects in a wide range of areas related with physiological data acquisition. Building upon previous work by our group, this work compares the quality of the data acquired by means of two different versions of the multimodal physiological computing platform BITalino, with a device that can be considered a reference. We acquired data from 5 sensors, namely Accelerometry (ACC), Electrocardiography (ECG), Electroencephalography (EEG), Electrodermal Activity (EDA) and Electromyography (EMG). Experimental evaluation shows that ACC, ECG and EDA data are highly correlated with the reference in what concerns the raw waveforms. When compared by means of their commonly used features, EEG and EMG data are also quite similar across the different devices.

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