AI-POWERED WEARABLES FOR REAL-TIME ATHLETE PERFORMANCE MONITORING: ENHANCING STAMINA, HEART RATE, AND STRESS LEVEL ANALYSIS

Abstract

The integration of Artificial Intelligence (AI) into wearable technology
presents a transformative opportunity for athletic performance monitoring.
This paper explores the application of AI-powered wearables designed to
track health, movement, and performance metrics in real-time, providing
athletes and coaches with immediate data on stamina, heart rate, and stress
levels during training and matches. Through a review of existing literature
and a proposed research design utilizing Analysis of Covariance (ANCOVA),
this study aims to investigate the effectiveness of these wearables in enhancing
training optimization and performance outcomes. The methodology outlines a
controlled experiment with athletes using AI-powered wearables during their
training regimen. Key variables, including stamina metrics, heart rate
variability, and perceived stress levels, will be measured and analyzed. This
paper concludes by discussing the potential of AI-powered wearables to
revolutionize athlete monitoring, offering data-driven insights for
personalized training and performance enhancement, while also
acknowledging limitations and suggesting future research directions.