Basketball Activity Recognition using Wearable Inertial Measurement Units

TLDR

Human movement analysis is a growing research area that can enhance athlete performance, predict injuries, and optimize training, but camera-based methods are limited, making wearable inertial systems a promising alternative. The study introduces a new wearable sensing system using multiple inertial measurement units to monitor basketball players. The system employs multiple inertial measurement units and a designed data collection plan to record basketball movements for activity recognition. Experimental results demonstrate the system’s potential for recognizing basketball activities.

Abstract

The analysis and evaluation of human movement is a growing research area within the field of sports monitoring. This analysis can help support the enhancement of an athlete's performance, the prediction of injuries or the optimization of training programs. Although camera-based techniques are often used to evaluate human movements, not all movements of interest can be analyzed or distinguished effectively with computer vision only. Wearable inertial systems are a promising technology to address this limitation. This paper presents a new wearable sensing system to record human movements for sports monitoring. A new paradigm is presented with the purpose of monitoring basketball players with multiple inertial measurement units. A data collection plan has been designed and implemented, and experimental results show the potential of the system in basketball activity recognition.