Smarting

mBrainTrain's Smarting device offers high-quality wireless EEG recordings and real-time brain activity monitoring, both in and out of the lab. When paired with a PC, it delivers superior data quality and excellent time precision, making it a reliable tool for researchers. Motion tracking, facilitated by a 3D built-in gyroscope, contributes supplementary data, enriching EEG research capabilities. The battery of the Smarting device lasts up to 5 hours for wireless EEG data stream, up to 500Hz sampling rate.

Compatibility

Smarting is compatible with mBrainTrain’s innovative EEG headgear, Smartfones, perfectly suitable for auditory and music studies.

Acquisition Software  

Smarting seamlessly integrates with user-friendly streamer software for PC, facilitating wireless communication within a range of 10 meters. Configured pre-sets allow for possible configuration mistakes and enhance the ease of use. Recordings maintain precision and synchronicity in supported BDF or XDF formats. Smarting is equipped to handle Lab Streaming Layer (LSL) and TTL inputs with millisecond precision, while offering customisable keyboard markers. The software enables impedance measurement for each electrode and provides real-time visualisation of data acquisition.

Channels and Caps

Smarting features 24 channels, 1 ground (DRL) and 1 reference (CMS), with a customisable layout to accommodate additional EOG and ECG electrodes as needed. Smarting is compatible with both gel-based and semi-dry/saline-based EEG caps.

Selected References

Chen, X., Cao, L. and Haendel, B.F. (2022). Human visual processing during walking: dissociable pre- and post- stimulus influences. NeuroImage 264. DOI: https://doi.org/10.1016/j.neuroimage.2022.119757

Jakovlijević, T., Janković, M.M. and Savić, A.M. et al. (2021). The relation between physiological parameters and colour modifications in text background and overlay during reading in children with and without dyslexia. Brain Science 11(5): 539. DOI: https://doi.org/10.3390/brainsci11050539

Orf, M., Wöstmann, M., Hannemann, R. and Obleser, J. (2023). Target enhancement but not distractor suppression in auditory neural tracking during continuous speech. iScience 6. DOI: https://doi.org/10.1016/j.isci.2023.106849

Selaskowski, B., Asché, L.M. and Wiebe, A. et al. (2023). Gaze-based attention refocusing training in virtual reality for adult attention-deficit/hyperactivity disorder. BMC Psychiatry 23(74). DOI: https://doi.org/10.1186/s12888-023-04551-z

Sterr, A., Ebakemito, J.K. and Mikkelsen, K.B. et al. (2018). Sleep EEG derived from behind-the-ear electrodes (cEEGrid) compared to standard polysomnography: a proof of concept study. Frontiers in Human Neuroscience 12. DOI: https://doi.org/10.3389/fnhum.2018.00452

Zolezzim D.M. and Naal-Ruiz, N.E. and Alonso-Valerdi, L.M. and Ibarra-Zarate, D.I. (2023). Chronic neuropathic pain: EEG data in eyes open and eyes closed with painDETECT and brief pain inventory reports. Data in Brief 48. DOI: https://doi.org/10.1016/j.dib.2023.109060

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