Sensory Profile for Autistic Children by Using EEG Biosignal

The neural activities in a brain can be measured in terms of voltages by Electroencephalography (EEG). The neurological problems are diagnosed by EEG because it is capable of being recorded over longer period of time and it is non-invasive. The children suffering from ASD are unable to express their emotions because of lack of proper processing of information in brain. This work is focussed towards building a sensory profile that differentiates among different types of sensory responses by using an EEG biosignal potential. Different states of emotion are identified by EEG signals such as super learning, positive thinking and relaxation of light and lie in between range of 8-12 Hz. This research involved participation of 64 children among which 34 were suffering from ASD whereas 30 were normal. While recoding EEG data, children were provided with visual, vestibular, taste, sound and vestibular sensory simulations. The EEGLAB software and wavelet transform wa used for filtering raw EEG data by using “independent component analysis (ICA)”. Later on, sensory profile was built by approximating entropy, standard deviations and means after extracting it from filtered EEG signals.