Mobile Neuroimaging Technologies

Challenges

While the application of several mobile neuroimaging technologies in neurodevelopmental research seems promising, key challenges are identified for their maximal exploitation and application in education settings.

Signal Quality

Despite the advancement of mobile neuroimaging technologies, signal quality cannot be neglected. Today, there is very little information on signal quality in terms of the validity and reliability of mobile data. Data collection and signal quality lack consensus on the most appropriate benchmarking at the moment. In order to achieve the optimal effects on educational neuroscience, teachers are called out to validate the signal quality and ensure data precision.

Selection of Electrode Density

Low-density devices may be more affordable and portable, but not necessarily appropriate for all circumstances. Light-weight mobile neuroimaging devices don't have the full capacity of laboratory devices. Those high-density devices accommodate more flexible applications. Consequently, they come with higher sensitivity to monitoring brain activities. However, mobile neurotechnologies are most likely equipped with lower-density systems which may compromise neuroimaging data quality.

Comfort Issues

It is essential to make sure learners are comfortable using the mobile neurotechnologies, more specifically about head sizes and body shapes without compromising participants' comfortability or compromising the signal quality - validity and reliability. For instance, dry EEG can cause skin irritation. Because dry electrodes give pressure on the scalp or can be tangled by hair. Similar to the idea of user experience, mobile neurotechnologies need to consider comfort issues, on the condition of not compromising signal quality.

Large-scale Data Collection

Low-density mobile EEG systems for large-scale data collection seem promising, but the future still needs to be seen. A key challenge is to create protocols for testing in multiple/non-standardized settings. In real educational settings, we cannot control all variables. The impact of social contexts and environmental variables on mobile EEG data is unknown. Thus, it may not be suitable to apply in all educational contexts, let alone collecting large-scale data. There is still a long way to go with retrieving large-scale data in educational contexts.

Ethical Concerns

As brain imaging is almost like reading someone's mind, on the condition that neuroscientist knows how to interpret neuroscience data. This raises ethical questions because this information could be manipulated and used for vicious purposes. The ethics of the application of scientific findings to education need to be addressed appropriately.

Page updated

Google Sites

Report abuse