Autism Spectrum Disorder is one of the complex conditions where it’s challenging the therapist & researchers to diagnose & predict at the early stage in an infant’s life. Breaking the myth, recent studies have declared that under the interference of Electroencephalogram (EEG) signals, researchers claimed that one can rule out Autism symptoms at an early stage by analyzing the brain’s electrical activities using EEG device.
“ It’s a well-known fact that EEG device is non-invasive & economically low cost which can be incorporated easily during the visits of routine checkups “ quotes Dr. Charles Nelson, Boston Children’s Hospital. The interdependence of this device can help in predicting whether a newly born baby could potentially be diagnosed with autism.
The existing data has been collected from the ‘Infant Sibling Project’ collaboratively run by Boston University & Boston Hospital for children's which aims at identifying & mapping the initial developmental risks of developing autism or difficulties in speech, communication, behavioral disorders among the newly born infant.
The research conducted by William Bosl was involved in the mining of data from the Infant Screening Project from 99 infants who possessed a higher risk of being autistic. The baby’s scalp was connected to a net carrying 128 sensors. The EEG scanned samples were recorded at regular intervals with a gap of 3 months. Based on the experiment, Bosl analyzed the 6 EEG frequency bands gamma, high gamma, alpha, beta, theta and delta for explaining the severity of ASD level. Bosl developed the computational algorithms which analyze 6 different components with the help of different signal measurement complexities where it predicts the sensitivity levels of autism & its symptoms with a 95% accuracy rate. In conclusion, Bosl claims that initial changes in signal complexities, and considering the brain activities can help us detect the disorder at an early stage of the infant’s life.