In the last two decades new non-invasive mobile EEG solutions have been developed to overcome limitations of conventional clinical EEG and improve monitoring of patients with long-term conditions. Despite their availability, the adoption of mobile innovations is still very limited. The aim of this study is to review the current state-of-the-art and highlight the main advantages of adopting non-invasive mobile EEG solutions in clinical trials and research studies of people with epilepsy or suspected seizures. Device characteristics are described, and their evaluation, is presented.
Two authors performed independently a literature review in accordance with PRISMA guidelines. A combination of different digital libraries was used (Embase, MEDLINE, Global Health and PsycINFO and https://clinicaltrials.gov/).
Twenty-three full-text, six conference abstracts and eight webpages were included while a total of fourteen non-invasive mobile solutions were identified. Published studies demonstrated at different levels how EEG recorded via mobile EEG can be used for visual detection of EEG abnormalities and for the application of automatic detection algorithms with acceptable specificity and sensitivity. When quality of the signal was compared with scalp-EEG, many similarities were found in the background activities and power spectrum. Several studies indicated that the experience of patients and health care providers using mobile EEG was positive in different settings. Ongoing trials are mostly focused on improving seizure detection accuracy but also on testing and assessing feasibility and acceptability of non-invasive devices in the hospital and at home.
This review supports the potential clinical value of non-invasive mobile EEG systems and their advantages in terms of time, technical support, cost, usability, and reliability when applied to seizure detection and management. On the other hand, the limitations of the studies confirmed that future research is needed to provide more evidence regarding feasibility and acceptability in different settings, as well as data quality and detection accuracy of new non-invasive mobile EEG solutions.