Zexi Chen¹ and Bobby Nguyen², ¹USA, ²California State Polytechnic University, USA

Parkinson's disease, a progressive neurological disorder, affects millions globally, presenting challenges in symptom management and medication adherence. Levio is a mobile application developed to address these challenges comprehensively. Levio integrates several key features: a symptom tracker for logging and monitoring symptoms, a medication reminder system, voice and speech therapy exercises, and a movement and exercise coach. It also provides an online forum where users can ask and answer questions. The methodology involved using Flutter for the app development and Firebase for data storage. Key challenges included ensuring user engagement with symptom tracking, customizing speech therapy exercises, and providing accurate exercise guidance. These were addressed by implementing user-friendly interfaces, leveraging machine learning for personalized therapy, and incorporating AI-based motion detection. During testing, Levio demonstrated high reliability in document registration and machine learning accuracy, with mean and median success rates indicating robust performance. The app's holistic approach provides a practical and integrated solution for managing Parkinson's disease. Levio's potential impact lies in its ability to consolidate multiple management aspects into a single platform, offering a significant improvement over existing fragmented tools and resources.

Parkinson, Computer Vision, Machine Learning, AI