Empowering Communication for Paralyzed Individuals and Spinal Cord Injury Patients: An Intelligent System With Eye Gaze Tracking, Voice Assistance, and Chat-Bot Integration

J. M. Chan Sri Manukalpa and H. P. Dissanayake
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J. M. Chan Sri Manukalpa: Department of Industrial Management, University of Kelaniya, Sri Lanka
H. P. Dissanayake: Department of Physical Science, Rajarata University of Sri Lanka

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 3, 81-89

Abstract: Advancements in artificial intelligence (AI) and machine learning (ML) have paved the way for transformative solutions in healthcare, particularly for individuals with severe physical disabilities. This research presents an innovative assistive communication platform tailored to Sinhala-speaking patients in Sri Lanka, addressing the unique challenges faced by individuals with Amyotrophic Lateral Sclerosis (ALS) and spinal cord injuries (SCI). These conditions severely restrict mobility and communication, leading to social isolation and diminished quality of life. The proposed system integrates eye-gaze tracking, speech recognition, and natural language processing (NLP) technologies to provide inclusive and effective communication solutions. For ALS patients, real-time eye-gaze tracking powered by MediaPipe interprets gaze movements as inputs, processed by a dense neural network (DNN)-based chatbot that generates responses in both English and Sinhala text and voice outputs. For SCI patients, who often retain speech abilities but face physical limitations, the system leverages speech recognition and NLP to interpret spoken commands, translating them into Sinhala text and synthesized speech. The dual-system approach ensures inclusivity, catering to the larger SCI-affected population while remaining adaptable to the needs of ALS patients. Despite challenges such as precision in gaze tracking, complexities in Sinhala speech recognition, and cultural nuances in NLP, the system demonstrates significant potential to enhance independence, social inclusion, and overall quality of life for patients. Empirical validation highlights the system's effectiveness, with high accuracy in intent identification and response generation. This research underscores the importance of culturally adapted, scalable assistive technologies, offering a foundation for future innovations in underserved regions. By bridging communication barriers, this platform represents a transformative step toward empowering individuals with disabilities.

Date: 2025
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