Brain Computer Interaction Framework for Speech and Motor Impairment Using Deep Learning
Abhijit T. Somnathe, Iftikhar Aslam Tayubi, Pundru Chandra Shaker Reddy, Nipun Sharma, Vikas Sharma, Mannava Yesubabu
Abstract
Some people may have trouble communicating with others because of motor and speech difficulties brought on by accidents, strokes, or diseases. Paralyzed people often struggle to communicate their demands, which can make even the simplest tasks challenging. People with disorders like dysarthria and amyotrophic lateral sclerosis may have trouble following conversations. The proposed method for automatic detection of everyday basic desires will help those with dysarthria and quadriplegic paralysis has more fulfilling lives. The device accomplishes this by monitoring brain impulses, which it then converts into either perceptible voice commands or messages that can be delivered to a healthcare provider's smart devices, depending on the user's preferences. The suggested method randomly displays an image of one of six basic requirements while using event-related-potentials(ERPs) detected from the Electroencephalogram (EEG) data to determine which need to fulfill. The dataset utilized for train, test, &validation was built using input from 10 participants. The proposed method had a 96.3|% success rate.