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dc.contributor.advisorNoor, Jannatun
dc.contributor.authorChisty, Sharfuddin Khan
dc.contributor.authorAbbasi, Khaled Imtiaz
dc.contributor.authorAfsana, Fairana
dc.contributor.authorShefa, Sanjida Afroz
dc.date.accessioned2024-05-08T03:47:32Z
dc.date.available2024-05-08T03:47:32Z
dc.date.copyright©2024
dc.date.issued2024-01
dc.identifier.otherID: 21341043
dc.identifier.otherID: 23241060
dc.identifier.otherID: 22241172
dc.identifier.otherID: 19101056
dc.identifier.urihttp://hdl.handle.net/10361/22769
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 61-67).
dc.description.abstractElderly users face physical, behavioral, and cognitive constraints as they age. As a considerable portion of the world’s population comprises elderly people, the graphical user interfaces (GUI) of commercial technology applications should be simplified to mobilize this age bracket’s soft skills and technology consumption. Yet, the comfort of this age range is often overlooked while designing smart technology interfaces. Several studies indicate potential design strategies for different technologies. The paper, subsequently, tests an e-health application designed using UCD strategies, consisting of chatbots using AI, to meet the cognitive needs of the elderly and to make their interactions with the application easy, intuitive, and comfortable. The paper introduces the use of AI, specifically the Large Language Model (LLM) of the Natural Language Processing (NLP) system, to create a friendly and humanlike chatbot that will assist elderly individuals or their caretakers in determining the nature of the illness, suggest the type of specialist to refer to, and list down hospitals that provide the required care. This research aims to build an e-health application to study the design methodologies that might assist elderly people with intuitive instructions across all interfaces, explore new possibilities by incorporating User-Centric Designs (UCD) and Artificial Intelligence (AI) in the application, and propose findings to conclude a model design for conventional applications to exhibit an elderly-friendly framework. After testing out this application on elderly people (N = 18), the findings from the data gathered suggest design strategies that can be implemented or have further research done on them to empower the elderly population to use applications on smartphones and other smart devices independently. To conclude, this research seeks to suggest ways to optimize smartphones and smart devices for the cognitive needs of the elderly. This research will address the specific needs and preferences of elderly users and assist them with medical trepidations. By addressing this gap in design, this research seeks to effectively design e-health interfaces that can be altered and used in other such interface designs to make them elderly-friendly.en_US
dc.description.statementofresponsibilitySharfuddin Khan Chisty
dc.description.statementofresponsibilityKhaled Imtiaz Abbasi
dc.description.statementofresponsibilityFairana Afsana
dc.description.statementofresponsibilitySanjida Afroz Shefa
dc.format.extent83 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectHCIen_US
dc.subjecteHealthen_US
dc.subjectUI designen_US
dc.subjectLLMen_US
dc.subject.lcshArtificial intelligence--Medical applications
dc.subject.lcshHealth--Data processing
dc.titleSmart sheba: an investigation on the effectiveness of integrating LLM enabled chatbots and using a user-centred design strategy to enhance user experience of older adultsen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB.Sc. in Computer Science


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