Bachelorarbeit, 2014
54 Seiten
This thesis aims to develop a low-cost, real-time eye-tracking system, called Eye-Reaction, to facilitate communication between patients with disabilities and their doctors. The system utilizes color-based object detection, allowing patients to answer questions by gazing at the desired answer, which is then highlighted. The primary focus is on assisting patients with Amyotrophic Lateral Sclerosis (ALS), who experience full body paralysis and rely heavily on eye movements for interaction.
Chapter One provides an introduction to eye-tracking technology, its applications in various fields, and the challenges faced by individuals with physical disabilities. It outlines the research problem, objectives, and scope, emphasizing the need for an accessible communication system for patients with ALS. Chapter Two presents a literature review on existing eye-tracking systems, highlighting their strengths and limitations. It explores various techniques and approaches used in eye detection and tracking, including color-based methods. Chapter Three discusses the methodology employed in this study, focusing on the participants, environment, tools, and instruments used. It delves into the technical details of the chosen image processing framework (AForge.NET) and explains the development process of the Eye-Reaction system. Chapter Four explores the software system's features and functionalities, describing the design principles and functionalities of the login form, configuration form, questions form, help and sleep form, and about form. Chapter Five presents the results of the research, including both theoretical and experimental findings. It analyzes the system's performance, emphasizing its ability to accurately track eye movements and provide reliable feedback. Chapter Six concludes the thesis by summarizing the findings, discussing the system's strengths and limitations, and exploring potential future directions for research and development.
This research focuses on developing an eye-tracking system for patients with disabilities, particularly ALS. Key concepts include color-based object detection, real-time video processing, AForge.NET framework, and accessible communication technology. The research explores the use of eye movements as a means of interaction and aims to improve the quality of life for individuals with limited mobility.
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