SIMPLE, RELIABLE, MOBILE

Smarting MOBI

Choose SMARTING mobi to bring
convenience and simplicity to your
research experiments and join the
league of pioneers in mobile EEG.

  • Signal Created with Sketch.
    High signal
    quality
  • satic Created with Sketch.
    Submillisecond
    time precision
  • telefon Created with Sketch.
    Easy to use
    mobile app
LET'S TALK
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    smarting

    Smarting MOBI

    Choose SMARTING mobi to bring convenience and simplicity to your research experiments and join the league of pioneers in mobile EEG.

    • Signal Created with Sketch.
      High signal
      quality
    • satic Created with Sketch.
      Submillisecond
      time precision
    • telefon Created with Sketch.
      Easy to use
      mobile application
    LET'S TALK

    FULLY MOBILE EEG

    Small light-weight EEG device for high quality recordings with accompanying mobile app for real-time brain activity monitoring, out of the lab, in real life.

    Whether paired with a PC or smartphone, SMARTING mobi provides superior data quality and high time-precision.

    LET'S TALK
    smarting android application mobile eeg device
    smarting mobile eeg device
    fully mobile

    WHY SMARTING MOBI?

    SMARTING mobi is small, simple and mobile EEG device, with no need for any additional equipment, which makes it a powerful research tool that records EEG on the go:

    • Psychology studies
    • Sport studies
    • Drowsiness/fatigue studies
    • Serious gaming/VR studies

    SMARTING mobi supports synchronization with other sensors and simultaneous multi-amplifier streaming via labstreaming layer, so it can be used for cognitive group studies:

    • In musical groups
    • Among quiz players
    • For sport psychology
    • Interaction in multiplayer games

    SMARTING mobi is wearable device that features motion sensors, which means that you can detect body and head movements. It makes our device perfectly suitable for:

    • Pairing behavioural & cognitive metrics
    • Health and safety at work research
    • Complementing neurological image
    • Brain recordings in sport studies
    smarting tablet

    KEY FEATURES

    Lighter
    than 60g

    81x52x12mm
    Light and Compact

    250-500Hz
    sampling

    0-133Hz flat frequency response
    High Signal quality

    24ch
    Recording cap

    Customizable and Comfortable

    3D built-in
    gyroscope

    For recording head motion

    Bluetooth
    10m range

    Wireless recordings

    up to 5 hours
    recordings

    Long battery life

    Lighter
    than 60g

    81x52x12mm
    Light and Compact

    250-500Hz
    sampling

    0-133Hz flat frequency response
    High Signal quality

    24ch
    Recording cap

    Customizable and Comfortable

    3D built-in
    gyroscope

    For recording head motion

    Bluetooth
    10m range

    Wireless recordings

    up to 5 hours
    recordings

    Long battery life

    General characteristics
    Name Smarting
    Number of channels 24
    Channel Type / Reference referential channels / recording with one electrode
    Input impedance 1
    Input Referred Noise <1 µV
    Input Range (-100)mV - 100 mV
    CMMR > 140 dB*
    Gain 24
    Gyroscope 3D Built-in
    *measured at 50Hz common mode
    Connectors
    Electrode Connectors IDC
    EEG Cap Layouts
    Standard
    Motor
    Dimensions
    Physical box size 82x51x12 mm
    Weight <60 grams
    AD conversion
    Sampling frequency 250 or 500 Hz
    Sampling Parallel sampling
    Resolution 24-bits
    Bandwidth 0-250 Hz
    Flat Frequency Response 0-133 Hz
    (3dB attenuation at 133Hz),
    true DC performance
    Anti-aliasing Filter Yes
    Active Ground Yes
    Communication type
    Wireless Communications Bluetooth range v2.1 + EDR
    Bluetooth range ~10 meters
    Power
    Power Supply USB Type-C
    Battery Type Internal
    Operation time ~ 5 hours

    HOW IT WORKS

    play

    Mounting the EEG cap

    play

    SMARTING
    Android App

    play

    Checkerboard task

    play

    Connecting to PC
    and streamer

    CONNECTED SOLUTIONS

    EasyCap

    EasyCap

    EasyCap is the official partner of mBrainTrain LLC, providing the EEG caps with standardized or custom electrode layout configuration. The caps are based on the Ag/AgCl sintered ring electrodes and they are comfortable for the long term EEG recordings.

    mindfield

    Mindfield biosystems

    SMARTING mobi is integrated with the eSense Skin Response and Temperature sensors. This allows synchronous recording of the EEG data, Galvanic Skin Response (GSR) and body temperature solely on the smartphone, which allows full mobility of the subjects.

    Mangold

    Mangold

    SMARTING mobi is integrated with the Mangold DataView and Interact software, which allows synchroneous recording of the EEG and video data. Mangold International is a world class leader in observational lab systems for behavioral research.



    neuro behavioral systems

    Neurobs Presentation

    One and only solution for reliable ERP experiments on a smartphone that enables recording the ERPs in free environment. SMARTING mobi and Neurobs Presentation software enable wireless stimulus triggering protocol, both on smartphone and/ or PC.

    Pupil

    Pupil labs

    Pupil labs is an open source platform for eye tracking and egocentric vision research. SMARTING mobi and Pupil labs eye tracker can synchronously record the data using smartphone, which allows full mobility for both neuromaketing and neuroergonomics research.

    OpenVibe

    OpenVibe

    SMARTING mobi device is supported by OpenViBE. OpenViBE is an open source platform for the brain computer interface (BCI) and real-time neurofeedback experiments. OpenViBE supports both Windows and Linux OS.

    USE CASES

    Cycling

    Darts

    Snowboarding

    Riding

    REFERENCE WORK

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    Hölle D. , Meekes J. , Bleichner M. G. Mobile ear-EEG to study auditory attention in everyday life, preprint


    Winneke H. A. , Schulte M. , Vormann M. , Matthias Latzel M. Effect of Directional Microphone Technology in Hearing Aids on Neural Correlates of Listening and Memory Effort: An Electroencephalographic Study , Volume 24 (2020)


    Jakovljević T. , Janković M. , Savić A. , Soldatović I. , Todorović P. , Jakulin T. J. , Papa G. , Ković V. The sensor hub for detecting the developmental characteristics in reading in children on a white vs. coloured background/coloured overlays, preprint


    Lee Y. , Lee M. , Lee S. Reconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface, arXiv:2005.08430v1.


    Kalafatovich J. , Lee M. , Lee S. Prediction of Memory Retrieval Performance Using Ear-EEG Signals, arXiv:2005.01329v3


    Daeglau M. , Wallhoff F. , Debener S. , Condro I.S. , Kranczioch C. , Zich C. Challenge Accepted? Individual Performance Gains for Motor Imagery Practice with Humanoid Robotic EEG Neurofeedback, Sensors 2020, 20(6), 1620.


    Fjaellingsdal T.G. , Schwenke D. , Ruigendijk E. , Scherbaum S. , Bleichner M.G. Studying brain activity during word-by-word interactions using wireless EEG, PLoS ONE 15(3): e0230280.


    Lee Y. , Lee M. Decoding Visual Responses based on Deep Neural Networks with Ear-EEG Signals, arXiv:2002.01085.


    Spychala N. , Debener S. , Bongartz E. , Möller HHO. , Thorne JD. , Philipsen A Braun N. Exploring Self-Paced Embodiable Neurofeedback for Post-stroke Motor Rehabilitation, Front. Hum. Neurosci. 13:461.


    Topalović I. , Graovac S. , Popović D. B. EMG map image processing for recognition of fingers movement, Journal of Electromyography and Kinesiology, Volume 49, December 2019, 102364.


    Farmaki C. , Sakkalis V. , Loesche F. , Nisiforou E. A. Assessing Field Dependence-Independence Cognitive Abilities Through EEG-Based Bistable Perception Processing, Front. Hum. Neurosci. 13:345.


    Cretot-Richert G. , De Vos M. , Debener S. , Emkes R. , Voix J. Assessing concentration levels through ear-EEG: a comparative study between conventional and mobile EEG systems, Frontiers.


    Cao L. , Händel B. Walking enhances peripheral visual processing in humans, PLoS Biol 17(10): e3000511.


    Phan Petrini F. M. , Valle G. , Bumbasirevic M. Barberi F. , Bortolotti D. , Čvančara P. , Hiairrassary A. , Mijović P. , Sverrisson A. O. , Pedrocchi A. , Divoux J. , Popović I. , Lechler K. , Mijović B. , Guiraud D. , Stieglitz T. , Alexandersson A. , Micera S. , Lešić A. , Raspopović S. Enhancing functional abilities and cognitive integration of the lower limb prosthesis, Science Translational Medicine, Vol. 11, Issue 512.


    Phan Petrini F. M. , Bumbasirevic M. , Valle G. , Ilic V. , Mijović P. , Čvančara P. , Barberi F. , Katic N. , Bortolotti D. , Andreu D. , Lechler K. , Lesic A. , Mazic S. , Mijović B. , Guiraud D. , Stieglitz T. , Alexandersson A. , Micera S. , Raspopovic S. Sensory feedback restoration in leg amputees improves walking speed, metabolic cost and phantom pain, Nature Medicine 25, 1356-1363 (2019).


    Hendrikse M. M. E. , Llorach G. , Hohmann V. , Grimm G. Movement and Gaze Behavior in Virtual Audiovisual Listening Environments Resembling Everyday Life, Trends in Hearing, Volume 23 (2019).


    Phan H. , Chén Y.O. , Koch P. , Lu Z. , McLoughlin I. , Mertins A. , De Vos M. Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning, arXiv:1907.13177.


    Kwak N. , Lee S. Error Correction Regression Framework for Enhancing the Decoding Accuracies of Ear-EEG Brain-Computer Interfaces, IEEE Transactions on Cybernetics.


    Nogueira W. , Dolhopiatenko H. , Schierholz I. , Büchner A. , Mirkovic B. , Bleichner M.G. , Debener S. Decoding Selective Attention in Normal Hearing Listeners and Bilateral Cochlear Implant Users With Concealed Ear EEG, Frontiers in Neuroscience, 13:720, 2019.


    Blum S. , Jacobsen N. , Bleichner M.G. , Debener S. A Riemannian Modification of Artifact Subspace Reconstruction for EEG Artifact Handling, Frontiers in Human Neuroscience, 13:141, 2019.


    Mirković B. , Debener S. , Schmidt J. , Jaegera M. , Neher T. Effects of directional sound processing and listener's motivation on EEG responses to continuous noisy speech: Do normal-hearing and aided hearing-impaired listeners differ?, Hearing Research, 2019.


    Piñeyro Salvidegoitia M. , Jacobsen N. , Bauer A-KR. , Griffiths B. , Hanslmayr S. , Debener S. Out and about: Subsequent memory effect captured in a natural outdoor environment with smartphone EEG, Psychophysiology, 2019;e13331.


    Sterr A. , Ebajemito J. K. , Mikkelsen K. B. , Bonmati-Carrion M. A. , Santhi N. , della Monica C. , Grainger L. , Atzori G. , Revell V. , Debener S. , Dijk D. , DeVos M. Sleep EEG Derived From Behind-the-Ear Electrodes (cEEGrid) Compared to Standard Polysomnography: A Proof of Concept Study, Frontiers in Human Neuroscience, Hearing Research, 2019.


    Mikkelsen K. B. , Ebajemito J. K. , Bonmati-Carrion M. A. , Santhi N. , Revell V. L., Atzori G. , Monica C. , Debener S. , Dijk D. , Sterr A. , De Vos M. Machine-learning-derived sleep-wake staging from around-the-ear electroencephalogram outperforms manual scoring and actigraphy, J Sleep Res. , 2018; e12786.


    Bridwell D. A. , Henderson S. , Sorge M. , Plis S. , Calhoun V.D. , Relationships between alpha oscillations during speech preparation and the listener N400 ERP to the produced speech, Scientific Reports, 2018 ; 12838.


    Cao L. , Haendel B. , Increased influence of periphery on central visual processing in humans during walking, preprint


    Denk F. , Grzybowski M. , Ernst S. M. A. , Kollmeier B. , Debener S. , Bleichner M. G. Event-Related Potentials Measured From In and Around the Ear Electrodes Integrated in a Live Hearing Device for Monitoring Sound Perception, Trends in Hearing, Volume 22 (2018).


    Zamm A. , Debener S. , Bauer A. R., Bleichner M. G. , Alexander P. Demos A. P. , Palmer C. Amplitude envelope correlations measure synchronous cortical oscillations in performing musicians, Annals of the New York Academy of Sciences, 2018.


    Woestmann M. , Waschke P. , Obleser J. Prestimulus neural alpha power predicts confidence in discriminating indentical auditory stimuli, Eur J Neurosci, 2019;49:9-105.


    Mijović P. , Milovanović M. , Ković V. , Mijović B. , Gligorijević I. , Minović M. , Mačužić I. Communicating the user state: Introducing cognition-aware computing in industrial settings, Safety Science, 2018.


    Waschke L. , Wöstmann M. , Obleser J. States and traits of neural irregularity in the age-varying human brain, Scientific Reports, 2017; 17381.


    Zink R. , Proesmans S. , Bertrand A. , Van Huffel S. , De Vos M. Online detection of auditory attention with mobile EEG: closing the loop with neurofeedback, preprint


    Blum S. , Debener S. , Emkes R. , Volkening N. , Fudickar S. , Bleichner M. G. EEG recording and online signal processing on Android: A multi-app framework for brain-computer interfaces on smartphone, BioMed Research International, 2017.


    Zich C. , Harty S. , Kranczioch C. , Mansfield L. K. , Sella F. , Debener S. , Kadosh C. R. Modulating hemispheric lateralization by brain stimulation yields gain in mental and physical activity, Scientific Reports, 2017; 7:13430.


    Zamm A. , Palmera C. , Bauerb A. R. , Bleichner M. G. , Demosa A. P. , Debener S. Synchronizing MIDI and wireless EEG measurements during natural piano performance, Brain Research (2017).


    Zich C. , Debener S. , Schweinitz C. , Sterr A. , Meekes J. and Kranczioch C. High-Intensity Chronic Stroke Motor Imagery Neurofeedback Training at Home: Three Case Reports, Clinical EEG and Neuroscience, 2017; 1-10.


    Bleichner M. G. , Debener S. Concealed, unobtrusive ear-centered EEG acquisition: cEEGrids for transparent EEG, Frontiers in human neuroscience, 2017; 11:163.


    Bridwell D. A. , Leslie E. , McCoy D. , Plis S. M. and Calhoun V.D. Cortical sensitivity to guitar note patterns: EEG entrainment to repetition and key, Frontiers in human neuroscience, 2017; 11:90.


    Braun N. , Kranczioch C. , Liepert J. , Dettmers C. , Zich C. , Büsching I. , Debener S. Motor imagery impairment in post-acute stroke patients, Neural Plasticity, Volume 2017 (2017).


    Waschke P. , Woestmann M. , Obleser J. Neural noise in the age-varying human brain predicts perceptual decisions, preprint


    Goregliad Fjaellingsdal T. , Ruigendijk E. , Scherbaum S. , Bleichner M. G. The N400 Effect during Speaker-Switch—Towards a Conversational Approach of Measuring Neural Correlates of Language, Frontiers in Psychology, 2016; 7:1854.


    Bleichner M. G. , Mirković B. , Debener S. Identifying auditory attention with ear-EEG: cEEGrid versus high-density cap-EEG comparison, Journal of Neural Engineering, 13.6 (2016): 066004.


    Zink R. , et al. Mobile EEG on the bike: disentangling attentional and physical contributions to auditory attention tasks., Journal of Neural Engineering 13.4 (2016): 046017.


    Mijović P. , Ković V. , De Vos M. , Mačužić I. , Jeremić B. and Gligorijević I. Benefits of Instructed Responding in Manual Assembly Tasks: An ERP Approach., Frontiers in human neuroscience 10 (2016).


    Mirković B. , Bleichner M. G. , De Vos M. , Debener S. Target Speaker Detection with Concealed EEG around the Ear
    Frontiers in Neuroscience, 2016; 10:349.


    Popović M. L. , et al. Stimulation map for control of functional grasp based on multi-channel EMG recordings.
    Medical Engineering & Physics (2016).


    Debener S. , Emkes R. , De Vos M. , Bleichner M. G. Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear., Scientific reports, 5, 2015.


    Mijović P. , Ković V. , De Vos M. , Mačužić I. , Todorović P. , Jeremić B. and Gligorijević I. Towards continuous and real-time attention monitoring at work: reaction time versus brain response. Ergonomics (2016): 1-14.

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