IoT based approach for detection of dominating emotions in persons who stutter

Speech therapy sessions can be successful if therapists able to explore what kinds of emotions dominate the brain activities of persons who stutter (PWS). This study attempts to present a framework that would deliver a BCI system to measure and recognize dominating emotions in PWS. In this study, objective emotions of PWS were captured using an EEG-based
_Mindwave
sensor. Later, emotions' EEG data were analyzed to detect prevailing feelings in the mind of the targeted audience. Results suggest EEG-based sensors are cost-effective and convincing to read the brain activities of the targeted clients. PWS's brainwave data revealed that they are having emotional complications. This study implies that its outcomes would assist speech therapists to understand the insides of objective emotions of PWS.