
FULLY MOBILE EEG
A portable EEG device for high-quality recordings and monitoring brain activity in real-time, outside the lab.
When paired with PC, SMARTING mobi provides superior data quality with an excellent time precision.
Choose SMARTING to bring
convenience and simplicity to your
research experiments and join the
league of pioneers in mobile EEG.
A portable EEG device for high-quality recordings and monitoring brain activity in real-time, outside the lab.
When paired with PC, SMARTING mobi provides superior data quality with an excellent time precision.
SMARTING 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 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 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
81x52x12mm
Light and Compact
0-133Hz flat frequency response High Signal quality
Customizable and Comfortable
for recording Head motion
Wireless recordings
Long battery life
Smarting mobi
Number of channels
24
Channel Type / Reference
referential channels / recording with one electrode
Input impedance
1 GΩ
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
Electrode Connectors
IDC
Standard
Motor
Physical box size
82x51x12 mm
Weight
<60 grams
Sampling frequency
250 or 500 Hz
Sampling
Parallel sampling
Resolution
24-bits
Bandwidth
0-250 Hz
Flat Frequency Response
Anti-aliasing Filter
Yes
Active Ground
Yes
Wireless Communications
Bluetooth range v2.1 + EDR
Bluetooth range
~10 meters
Power Supply
USB Type-C
Battery Type
Internal
Operation time
~ 5 hours
The box also fits: Smarting EEG amplifier,
Smarting USB charger, Bluesoleil dongle.
81x52x12mm
Light and Compact
0-133Hz flat frequency response for a high-quality signal
Customizable and Comfortable
Wireless recordings
Vibrant battery life
SMARTING mobi incorporates eSense Skin Response and Temperature sensors. Hence, it allows synchronous EEG data recording, Galvanic Skin Response (GSR), and body temperature monitoring solely on a smartphone - allows full mobility of the subjects.
SMARTING mobi is integrated with the Mangold DataView and Interact software, which allows synchronous recording of EEG and video data. Mangold International is the leading observational lab system for behavioral research.
Provides a solution for reliable ERP experiments on smartphones as it can record the ERPs in a free environment. SMARTING mobi and Neurobs Presentation software enable wireless stimulus triggering protocol on smartphones and PC.
Pupil labs is an open-source platform for eye tracking and egocentric vision research. SMARTING mobi and Pupil labs eye tracker can synchronously record data using smartphones, allowing full mobility for both neuromarketing and neuroergonomics research.
Heremans ERM, Phan H, Borzée P, Buyse B, Testelmans D, De Vos M. From unsupervised to semi-supervised adversarial domain adaptation in electroencephalography-based sleep staging. J Neural Eng. 2022 Jun 24;19(3). doi: 10.1088/1741-2552/ac6ca8. PMID: 35508121.
Annika Wiebe, Kyra Kannen, Mengtong Li, Behrem Aslan, David Anders, Benjamin Selaskowski, Ulrich Ettinger, Silke Lux, Alexandra Philipsen, and Niclas Braun. Multimodal Virtual Reality-Based Assessment of Adult ADHD: A Feasibility Study in Healthy Subjects, Assessment 0 10.1177/10731911221089193
Yang, Q., & Kalantari, S. (2022). Real-time Continuous Uncertainty Annotation (RCUA) for Spatial Navigation Studies. arXiv. https://doi.org/10.48550/arXiv.2207.14651
Meiser, A., Tadel, F., Debener, S. et al. The Sensitivity of Ear-EEG: Evaluating the Source-Sensor Relationship Using Forward Modeling. Brain Topogr 33, 665–676 (2020). https://doi.org/10.1007/s10548-020-00793-2
Hölle, D., Meekes, J. & Bleichner, M.G. Mobile ear-EEG to study auditory attention in everyday life. Behav Res 53, 2025–2036 (2021). https://doi.org/10.3758/s13428-021-01538-0
Li Q, Coulson Theodorsen M, Konvalinka I, Eskelund K, Karstoft KI, Bo Andersen S, Andersen TS. Resting-state EEG functional connectivity predicts post-traumatic stress disorder subtypes in veterans. J Neural Eng. 2022 Nov 9;19(6). doi: 10.1088/1741-2552/ac9aaf. PMID: 36250685.
Longo, Luca Modeling cognitive load as a self-supervised brain rate with electroencephalography and deep learning (2022). https://doi.org/10.48550/arxiv.2209.10992
Hölle D, Blum S, Kissner S, Debener S and Bleichner MG (2022) Real-Time Audio Processing of Real-Life Soundscapes for EEG Analysis: ERPs Based on Natural Sound Onsets. Front. Neuroergon. 3:793061. doi: 10.3389/fnrgo.2022.793061
Mavros, P., J Wälti, M., Nazemi, M. et al. A mobile EEG study on the psychophysiological effects of walking and crowding in indoor and outdoor urban environments. Sci Rep 12, 18476 (2022). https://doi.org/10.1038/s41598-022-20649-y
Mitsuhiko Ishikawa & Shoji Itakura (2022) Social reward anticipation in infants as revealed by event-related potentials, Social Neuroscience, 17:5, 480-489, DOI: 10.1080/17470919.2022.2138535
Martin Orf, Malte Wöstmann, Ronny Hannemann, Jonas Obleser Auditory neural tracking reflects target enhancement but not distractor suppression in a psychophysically augmented continuous-speech paradigm, bioRxiv 2022.06.18.496558; doi: https://doi.org/10.1101/2022.06.18.496558
Elisabeth R.M. Heremans, Huy Phan, Amir H. Ansari, Pascal Borzée, Bertien Buyse, Dries Testelmans, Maarten De Vos, Feature matching as improved transfer learning technique for wearable EEG, Biomedical Signal Processing and Control, Volume 78, 2022,104009, ISSN 1746-8094,https://doi.org/10.1016/j.bspc.2022.104009.
Dasenbrock S, Blum S, Maanen P, Debener S, Hohmann V and Kayser H (2022) Synchronization of ear-EEG and audio streams in a portable research hearing device. Front. Neurosci. 16:904003. doi: 10.3389/fnins.2022.904003
Cavanna, F., Muller, S., de la Fuente, L.A. et al. Microdosing with psilocybin mushrooms: a double-blind placebo-controlled study. Transl Psychiatry 12, 307 (2022). https://doi.org/10.1038/s41398-022-02039-0
Zeena Britt Sanders, Melanie K Fleming, Tom Smejka, Marilien C Marzolla, Catharina Zich, Sebastian W Rieger, Michael Lührs, Rainer Goebel, Cassandra Sampaio-Baptista, Heidi Johansen-Berg, Self-modulation of motor cortex activity after stroke: a randomized controlled trial, Brain, 2022;, awac239, https://doi.org/10.1093/brain/awac239
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)
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.