Experimental characterization and analysis of the BITalino platforms against a reference device

Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul:2017:2418-2421. doi: 10.1109/EMBC.2017.8037344.

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.

MeSH terms

  • Accelerometry
  • Biomedical Engineering*
  • Electrocardiography
  • Electroencephalography
  • Electromyography