A SYSTEMATIC REVIEW OF THE APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN THE DEVELOPMENT OF SMART WEARABLE DEVICE APPLICATIONS

The convergence of artificial intelligence (AI) and wearables is ushering in a new paradigm of software development - AI- powered app creation - where AI is not just a feature but a software creation tool. This paper combines bibliometric analysis and systematic review (PRISMA) to explore research trends, contrast challenges and solutions, and identify academic gaps for 2020-2025. Results from 51 papers show a surge in research after 2021, with a shift in focus to healthcare personalization, edge machine learning (TinyML), and data privacy. However, there are still limitations in data normalization, automated UI/UX testing, and model transparency. The paper identifies some unaddressed research gaps by synthesizing existing challenges and solutions. It suggests potential directions to promote the application of AI in the development of smart wearable devices in practice, especially in the context of personal healthcare. Keywords: AI-powered wearable apps; TinyML; systematic review; PRISMA guidelines; software development for wearables