OWSD PhD Fellowship
OWSD Early Career
2023
Sanam Tahsina
About the project
This project will use machine learning to detect multi-stroke gestures and recognize Bangla Sign Languages in children with autism spectrum disorder using radio frequency (RF)-based wi-fi channel state information (CSI) signals. Autism Spectrum Disorders (ASD) can impact an individual's communication, social skills, or behavior, leading to repetitive motor movements or unusual behaviors. Communication and speech disorders are common among those diagnosed with ASD, and they may use augmentative and alternative communication (AAC) methods such as sign language, picture exchange communication, or flashcards. Despite a significant number of children in Bangladesh being affected by ASD, there is a limited number of healthcare professionals available to support them. Additionally, conventional ways of analyzing and evaluating the behavior and movements of children with ASD rely on intrusive and/or time-consuming methods such as wearable devices and manual observation of video footage. This project aims to improve the quality of life and social services for those with ASD by developing effective algorithms that utilize advanced techniques such as statistical learning, deep learning, and big data analytics. Additionally this system can establish a non-intrusive surveillance system to help clinicians diagnose ASD.
Field of Specialization
Position
Assistant Professor