Autonomous Human Movement Analyzer System

Human activity recognition is a crucial task in healthcare and exercise sciences, with wide-ranging applications for monitoring human health and well-being, disease detection, and prevention. With a multitude of devices that record human activity proliferating people's daily lives in the form of smartwatches, various wearable devices, and cameras, the abundance of data collected has made it possible to apply neural architectures to the problem. This study considers human activity data collected as time series. Recent advancements in deep learning architectures, specifically the Transformer model, have made it possible to classify sequential data with excellent accuracy. This paper presents a human activity recognition system utilizing a combination of the OptiTrack PrimeX 22 motion capture camera and a Transformer-based classifier model.