Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/23093
Title: A solution to overcome speech disorder of patients using Brain Neuron EEG Signals
Authors: Jayawickrama, J.A.D.T.
Thelijjagoda, Samantha
Keywords: Automated interface, Brain neuron waves, Self-learning video therapies, Speech disorders, Voice analysis algorithm
Issue Date: 2020
Publisher: Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka
Citation: Jayawickrama, J.A.D.T., Thelijjagoda, Samantha (2020). A solution to overcome speech disorder of patients using Brain Neuron EEG Signals. In : International Research Conference on Smart Computing and Systems Engineering, 2020. Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, p.182.
Abstract: Speech disorders are neurodevelopmental disorders such as Stuttering, Dysarthria, Dysphonia and Aphasia associated with left inferior frontal structural anomalies that involve repeating or prolonging a word, syllable or phrase, or stopping during speech and making no sound for certain syllables. Most of the people who are suffering from speech disorders encounter difficulties in professional communication. Since people are busy with their day to day life, it is not practical to spend more time in consulting a doctor or do speech therapies for their medical issues. The speech therapist generally charges a significantly much higher rate for a single speech therapy practice, which the patient needs to practice at least twice or more for a week to get a better result. In an economy like Sri Lanka, people with average income cannot afford such an amount of money. Therefore, an innovative desktop application for speech disorder patients to overcome this problem has arisen. The main aim of this application is to reduce the speech imperative percentage of speech disorder patients via capturing the electroencephalogram feed of speech motor (Broca's area) using brain neuron O1, O2, C3, C4, F3, F4, F7, F8 electrodes and analyzing it to identify speech imperative issues. This system identifies the current impact on the left hemisphere of the brain (Broca’s area) using EEG neurofeedback. Using speech voice analysis, the system provides the user to measure the articulation interference of the speech process. Self-Learning video tutorials are available for the clinical practices and treatments are available as prolong, relaxing, and humming exercises. Patients can track down the improvements daily or monthly by the rating system which makes the system unique among all other systems and the result can be directly sent to the desired consultant/neurophysiologist by the system itself. Patients can save time and the total cost of a therapy fee by using this system.
URI: http://repository.kln.ac.lk/handle/123456789/23093
Appears in Collections:Smart Computing and Systems Engineering - 2020 (SCSE 2020)

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