Cleaner EEG signals in Mente Autism using Artefact Reduction Algorithms

16 September, 2016

Electroencephalography (EEG) is a proven technique to record brain activities in natural settings.

p>EEG and the acquisition of EEG data forms the basis of the Mente system and therefore it is crucial that all raw EEG signals are as ‘clean’ as possible.

A problem often encountered is that EEG signals may be contaminated by ocular artefacts such as eye blink activities. To achieve satisfactory cleaning of the raw EEG signal from eye-blink artefacts, AAT’s researchers have adapted and applied various algorithms to achieve high levels of removal of eye-blink artefacts from raw EEG signals in Mente Autism, our next generation therapy for children on the autism spectrum.

Using already-established and implemented methods of sampling and filtering, raw EEG data is analysed and cleaned in real time and window-based. The process is also not resource intensive so as not to impinge on other functions running in parallel.

“Artefact reduction or removal from EEG data is very important as it cleans the signals from eye blink artefacts resulting in a higher quality and more accurate data. We have taken well-established methods and tweaked the maths to ensure that Mente Autism’s EEG output is clean yet does not affect the functionality of the device itself. With this new approach to our EEG acquisition and output, our customers benefit from more accurate therapy sessions while medical professionals are provided with clinical-quality EEG data for them to analyse,” Dr Adrian Attard Trevisan, AAT’s founder and chief scientific officer, said.