Design and Expert-Based Usability Evaluation of a Smart Mobile Application for Aphasia Rehabilitation

This paper aims to develop an artificial intelligence-assisted mobile application using speech recognition and image processing technologies to address language difficulties experienced by individuals with aphasia.

The mobile application was developed in the Android Studio environment using the Java programming language. Google Speech API was used for speech recognition, and Google ML Kit's image labelling APIs were used for image recognition. The development process of the application was conducted using the Scrum methodology. Features developed during the sprints for each module were evaluated through Expectation Tests conducted with expert participation. In these tests, users' pre-application expectations and post-application experiences with the modules were analysed through comparison. At the end of the development process, a System Usability Scale (SUS) Test was conducted to assess the overall integration of all modules.

Based on the results of Expectation Tests, necessary updates were made, and improvements were implemented in the functionality of each module. According to the SUS Test results, the application demonstrated an acceptable level of usability rate, and positive feedback was received in terms of user experience. The expert evaluation indicated that the application has acceptable usability and shows promise as a supportive tool for aphasia rehabilitation.

This prototype application has the potential to support speech skills of individuals with aphasia, especially those who face challenges in accessing a Speech and Language Therapist. The integration of artificial intelligence-supported speech recognition and image processing technologies offers a promising supportive tool for the language rehabilitation of individuals with aphasia. Testing this prototype with a wider group of users and continuously updating it will be crucial in providing further support to individuals with aphasia.