Mobile EEG
Mobile EEG

What is Mobile EEG? 

Electroencephalography (EEG) has been a cornerstone technique in neuroscience for nearly a century, offering invaluable insights into brain function and behaviour. EEG is a non-invasive neuroimaging technique used to measure the electrical activity of the brain. It involves placing electrodes on the scalp to detect and record the brain's electrical signals. These signals reflect the collective activity of millions of neurons firing in synchrony. During an EEG procedure, electrodes are typically attached to specific locations on the scalp using a conductive gel or paste. The electrodes pick up electrical signals generated by the brain and amplify them for recording. Researchers use EEG in various research settings – for example, EEG can be used to diagnose and monitor various neurological disorders such as epilepsy, sleep disorders and brain injuries. EEG can also be used to study a wide range of cognitive and neural processes, from basic sensory perception to higher-order cognitive functions such as memory, language, and emotion. 

Traditional EEG systems require participants to be tethered to stationary equipment, confining researchers’ investigations to controlled laboratory environments. Yet, with the advent of mobile EEG technology, the horizon of neuroimaging has expanded dramatically, empowering researchers to delve into the complexities of brain activity in real-world settings like never before. Mobile EEG signifies a monumental shift in EEG technology with a completely wireless setup, liberating researchers from the constraints of traditional electroencephalography studies. Unlike stationary EEG systems, which demand participants to remain immobile, mobile EEG devices withstand motion to varying extents, boasting portability, wearability, and transparency. Portable EEG denotes mere mobility, whereas mobile EEG implies motion tolerance during signal acquisition (Bleichner and Debener 2017). 

Applications of Mobile EEG

Advantages of Mobile EEG

The transition from wired to wireless EEG devices heralds numerous advantages. Wireless connectivity eradicates lengthy cables attached to stationary equipment, streamlining data collection with unparalleled ease.
This breakthrough empowers researchers to conduct studies across diverse settings and populations, fostering interdisciplinary collaboration and broadening the horizons of EEG research.
 

Portable EEG

Compact and lightweight designs facilitate easy transport and usage across diverse environments, enhancing research flexibility. Mobile EEG technology promotes research outside of traditional laboratory settings, enabling the collection of more naturalistic data during activities like sports or exercise performance studies, sleep research, and rehabilitation. 

mBrainTrain PRO X Product Image

Flexible 

Wireless connectivity enables data collection in real-world environments, facilitating longitudinal monitoring and naturalistic data acquisition. 

Accessible 

Simplified setup and operation democratise EEG research, making it more accessible to a wider range of researchers and practitioners.  

Scalable 

Versatile architectures cater to various research needs, from individual studies to large-scale investigations that involve hyperscanning, fostering collaboration and knowledge dissemination. Hyperscanning is a sophisticated research method that synchronises data from multiple EEG streams and other sensors into a single file structure. Mobile EEG enables conducting experiments completely wirelessly, providing freedom of movement during social experiments. 

Disciplinaries enhanced with Mobile EEG recordings  

  • Perception and visual processing  
  • Auditory processing and speech detection  
  • Memory retrieval  
  • Sleep scoring and polysomnography (PSG) 
  • Cognitive load and creativity  
  • Neural correlates of attention  
  • Chronic neuropathic pain  
  • Attention refocusing in attention-deficit/hyperactivity disorder (ADHD) 
  • Gait performance  
  • Epilepsy  
  • Psychedelics  
  • Post-traumatic stress disorder (PTSD) 
  • Cognitive and neural correlates of emotion  

What are the applications of mobile-EEG? 

Neurological Disorders  

Mobile EEG devices offer a promising avenue for enhancing our understanding and management of neurological disorders, providing valuable insights into brain activity outside traditional clinical settings. These portable systems extend the reach of EEG technology beyond the confines of hospitals and clinics, potentially revolutionising diagnostic and monitoring approaches. One significant application lies in the realm of epilepsy, where routine EEG recordings often fall short in detecting interictal epileptiform discharges (IEDs). As highlighted by Nous et al. (2024), subclinical epileptiform activity (SEA) plays a role in conditions like Alzheimer’s disease (AD), potentially impacting cognitive decline. Mobile EEG devices offer a solution to the limitations of conventional EEG setups, enabling continuous monitoring in real-world environments. This flexibility enhances the likelihood of capturing elusive epileptic events, aiding in both diagnosis and treatment optimisation. Moreover, the accessibility and convenience of mobile EEG hold promise for early detection and personalised treatment strategies across various neurological conditions. By facilitating long-term monitoring in naturalistic settings, these devices provide a more comprehensive view of brain dynamics, shedding light on patterns of activity that may be missed during brief clinical assessments. This proactive approach enables clinicians to intervene earlier, potentially mitigating disease progression and optimising therapeutic outcomes. 

Additionally, the advent of advanced algorithms, as briefly discussed by Askamp and van Putten (2014), further enhances the utility of mobile EEG data. These algorithms assist in the interpretation of EEG recordings, addressing concerns about signal quality and the complexity of data analysis. By automating aspects of the review process, they streamline workflow and improve diagnostic accuracy, ultimately empowering healthcare professionals to make informed decisions based on robust neurophysiological data. 

 Auditory Processing  

Investigating auditory processes in real-world settings enriches our comprehension of everyday brain functions, particularly in contexts where individuals, such as musicians, experience a state of flow. Mobile EEG technology facilitates this exploration without the constraints of clinical laboratory environments and cumbersome wires scattered everywhere. Zamm et al. (2021) explored interpersonal synchrony in music duet partners using wireless EEG technology. By measuring brain activity in real-time during spontaneous music performance, they uncovered the neural dynamics underlying interpersonal coordination. Their findings demonstrated that mobile EEG enabled the assessment of coupled cortical dynamics at the performance frequency, shedding light on the neural mechanisms supporting synchronised musical joint action. Bridwell et al. (2017) investigated cortical responses to structured and random musical sequences using a portable EEG system. By examining event-related potentials (ERPs) to guitar notes presented with and without musical patterns, they revealed cortical sensitivity to complex acoustic patterns. This study highlighted the utility of mobile EEG in capturing neural responses to musical structure in naturalistic listening conditions, enhancing our understanding of how the brain processes complex auditory stimuli. Chabin et al. (2020) evaluated the reliability of wireless EEG devices for detecting musical emotions during naturalistic listening experiences. By comparing mobile EEG recordings with a gold standard EEG device, they demonstrated the feasibility of using portable EEG technology in studying emotional responses to music in real-world settings. This study showcased the potential of mobile EEG for investigating auditory emotional processing outside of the laboratory environment. Zamm et al. (2019) validated a mobile wireless EEG system for capturing neural dynamics during piano performance. Through synchronised recording of music performance and EEG data, they demonstrated the precise temporal accuracy of mobile EEG in capturing the neural signatures of musicians' performances. This research exemplified how mobile EEG technology can overcome technical challenges associated with measuring brain activity during naturalistic tasks, paving the way for studying the neural mechanisms underlying music performance. 

mBrainTrain Smartfones Product Image

Movement  

Mobile EEG technology offers unprecedented opportunities to advance our understanding of neural mechanisms underlying human movement and to develop innovative solutions for improving mobility and quality of life in various populations. Its wireless and portable nature makes it a superior tool compared to stationary EEG, enabling researchers to study brain activity in diverse real-world scenarios. 

Reiser et al. (2019) demonstrate the feasibility of studying cognitive and motor functioning in outdoor environments using mobile EEG. Their findings reveal how increasing movement complexity imposes a higher workload on the cognitive system, affecting cognitive task performance. Jacobsen et al. (2020) address challenges in mobile EEG recordings during gait, proposing a comprehensive framework to quantify and mitigate gait-related artifacts. Their study showcases the specificity and effectiveness of artifact reduction strategies, enabling more accurate interpretation of brain activity patterns during walking. Mavros et al. (2022) explore the psychophysiological effects of different environmental settings using mobile EEG and electrodermal activity measurements during walking. Their research underscores the importance of urban design on human psychological experience and validates the efficacy of mobile EEG in capturing emotional responses in ambulatory settings. Petrini et al. (2019) present a ground-breaking study on integrating sensory feedback into leg neuroprostheses using mobile EEG. Their research demonstrates how real-time tactile and proprioceptive feedback can improve mobility, prevent falls, and enhance embodiment of the prosthesis, highlighting the potential of mobile EEG in developing sensory-enhanced neuroprostheses for people with disabilities. 

Sleep 

Recent research has highlighted the potential of mobile EEG in advancing our understanding of sleep physiology. Mobile EEG systems provide an opportunity for more extensive and accessible sleep monitoring, promising significant advancements in both basic and clinical sleep research.  

Mikkelsen et al. (2018) focused on automated sleep scoring using a low-cost mobile EEG platform. By comparing machine-learning-based scoring of around-the-ear EEG signals with manual scoring of standard polysomnography (PSG), the research highlighted the efficacy of mobile EEG in accurately assessing sleep parameters. The findings suggested that mobile EEG outperformed traditional methods in detecting sleep onset and total sleep time, indicating its potential for large-scale sleep studies. Ferster et al. (2019) highlighted the development of a mobile system for sleep-biosignal monitoring and real-time intervention in ambulatory sleep research. Their evaluation showed that the mobile EEG system provided comparable signal quality to traditional lab-based systems, with high correlations in key frequency bands. Furthermore, the system demonstrated effectiveness in real-time intervention, particularly in targeting slow wave sleep phases, making it suitable for unobtrusive, multi-night monitoring and intervention in home settings. 

  1. Mobile EEG in epilepsy.. Askamp, J. and van Putten, M.J.A.M. (2014).. International Journal of Psychophysiology.. September 2013.
  2. Concealed, unobtrusive ear-centered EEG acquisition: cEEGrids for transparent EEG. Frontiers in Human Neuroscience 11.. Bleichner, M.G., and Debener, S.. Frontiers in Human Neuroscience.. April 2017.
  3. Cortical sensitivity to guitar note patterns: EEG entrainment to repetition and key.. Bridwell, D.A. et al.. Frontiers in Human Neuroscience.. March 2017.
  4. Are the new mobile wireless EEG headsets reliable for the evaluation of musical pleasure?.. Chabin, T. et al.. PloS ONE.. December 2020.
  5. Configurable mobile system for autonomous high-quality sleep monitoring and closed-loop acoustic stimulation.. Ferster, M.L. et al.. IEEE Sensors Letters.. May 2019.
  6. A walk in the park? Characterising gait-related artifacts in mobile EEG recordings.. Jacobsen, N.S.J. et al.. European Journal of Neuroscience.. September 2020.
  7. A mobile EEG study on the psychophysiological effects of walking and crowding in indoor and outdoor urban environments.. Mavros, P. et al.. Scientific Reports.. November 2022.
  8. Machine-learning-derived sleep-wake staging from around-the-ear electroencephalogram outperforms manual scoring and actigraphy.. Mikkelsen, K.B. et al.. Journal of Sleep Research.. November 2018.
  9. Subclinical epileptiform activity in the Alzheimer continuum: association with disease, cognition and detection method.. Nous, A. et al.. Alzheimer’s Research and Therapy.. January 2024.
  10. Enhancing functional abilities and cognitive integration of the lower limb prosthesis.. Petrini, F.M et al.. Neuroprosthetics.. October 2019.
  11. Recording mobile EEG in an outdoor environment reveals cognitive-motor interference dependent on movement complexity.. Reiser, J.E., Wascher, E. and Arnau, S.. Scientific Reports.. September 2019.
  12. Synchronising MIDI and wireless EEG measurements during natural piano performance.. Zamm, A. et al.. Brain Research.. August 2019.
  13. Behavioural and neural dynamics of interpersonal synchrony between performing musicians: a wireless EEG Hyperscanning study.. Zamm, A. et al.. Frontiers in Human Neuroscience.. September 2021.

Associated Products

The following products from our catalogue are associated with this technique. To find out more about these supported devices, follow the links below or get in touch via email or phone.

Mobile EEG

Join our mailing listJoin our mailing list