An Advanced Human-Machine Interface Utilizing Eye Tracking For Enhanced Written Communication Among Locked-In Syndrome Patients By Using Haar Cascade Algorithm

Abstract

The purpose of this research is to provide an intelligent human-machine interface based on eye tracking technology to help patients with Locked-in Syndrome (LIS) communicate better in writing. Patients with LIS are completely paralyzed in their voluntary muscles; as a result, they are conscious but unable to move or talk. With the help of eye tracking, patients will be able to compose messages with the suggested interface by just focusing their gaze on a virtual keyboard that is shown on a computer screen. The user's gaze is efficiently tracked by the system, which interprets it as input and maps it to the appropriate letters or phrases. For LIS patients, this novel method offers a substantial improvement over current assistive communication technology becaus[1]e it does not involve physical movements or tools that require fine motor control. The interface's efficacy is demonstrated by the experimental findings, which show that writing messages may be done quickly and accurately. The system also includes clever features that improve user experience and overall communication efficiency, like word prediction and error correction. This study's technology offers LIS patients a dependable and effective way to communicate in writing, which could significantly improve their quality of life. eye tracking, textual communication, assistive technology, human-machine interface, and locked-in syndrome.