Decision Support System for Rehabilitation with a Selection of Exercises for Physical and Mental Health
Students Name: Duhina Sophia Olehivna
Qualification Level: magister
Speciality: Systems and Methods of Decision Making
Institute: Institute of Computer Science and Information Technologies
Mode of Study: full
Academic Year: 2024-2025 н.р.
Language of Defence: англійська
Abstract: This thesis presents the concept and implementation of a decision support system for rehabilitation, which includes selecting exercises for physical and mental health through a mobile application. The scientific novelty of the work lies in the development of an integrated platform that combines personalized recommendations and adaptive algorithms, gamification to maintain user motivation, and a comprehensive approach to rehabilitation that considers both physical and mental aspects. The use of adaptive protocols aims to increase the effectiveness of rehabilitation, reducing the need for constant supervision by specialists. Study object is the rehabilitation process, including the restoration of physical and mental health through exercise. The scope of the research is methods and algorithms for decision support in mobile applications aimed at selecting individual rehabilitation exercises. Goal of the research is to create a decision support system for human rehabilitation that provides the selection of individual exercises for physical and mental health via a mobile application. Main tasks of the study: • analyze modern approaches to physical and mental rehabilitation using mobile applications; • study the principles of habit formation and their application in rehabilitation protocols; • develop a model for a mobile application that integrates physical exercises and mental practices, considering individual user needs; • implement a personalized recommendation system based on user health data and progress; • introduce motivational elements (gamification) to increase user engagement in rehabilitation protocols; • evaluate the effectiveness of the developed system through user group testing. Based on scientific research in the field of mental and physical health, there is significant demand for technological solutions that enhance the management of personal tasks and goals. Specifically, James Clear in his book "Atomic Habits" details mechanisms of habit formation, including cues, cravings, responses, and rewards. These principles form the basis for creating motivational mechanisms in mobile applications [1]. It is crucial today to help people access the necessary support and solutions, as many suffer from deteriorating mental and physical health due to high levels of stress, sedentary lifestyles, and more. Existing market solutions are typically focused on a single aspect of life, such as physical or mental health, and rarely offer a personalized approach [2]. Accordingly, a conceptual model for a mobile application was developed that integrates personalized recommendations, adaptive algorithms, motivational mechanisms, and gamification. A goal tree and UML notation diagrams were designed. The methods chosen for implementing recommendations include fuzzy matching, TF-IDF, and rule templates, enabling the system to display the most relevant suggestions to users. The chosen language for the application is Dart, using the Flutter framework, with Firebase selected for database and cloud services. Furthermore, a system was developed to dynamically adjust routines based on user progress. Testing demonstrated high user satisfaction. Keywords – rehabilitation, physical health, mental health, mobile application, personalization, adaptive algorithms, habit formation, gamification, motivation, protocols, progress, healthy lifestyle, adaptive protocols, rehabilitation protocols. References: 1. Clear, James. Atomic Habits. Lifestyle Publishing, 2019. 2. A Survey on New Horizons for Health Through Mobile Technologies. International Journal of Advance Engineering and Research Development. 2017. Т. 4, № 03. URL: https://doi.org/10.21090/ijaerd.34966 (date of access 04.09.2024). 3. Personal Development Market Analysis - US, Canada, China, Japan, Germany - Size and Forecast 2024-2028. Market Research Reports - Industry Analysis Size & Trends - Technavio. URL: https://www.technavio.com/report/personal-development-market-industry-analysis (date of access: 06.09.2024).