# Emerging Technologies for Injury Identification in Sports Settings: A Systematic Review
## 1 Introduction  
Sport-related injuries are prevalent across all levels of sports, from recreational to professional sports [1]. These injuries carry a considerable public health burden, often leading to decreased participation in sports activities, possible long-term health consequences, and an increased strain on healthcare systems. At professional levels of sports, once a potential injury is observed and the athlete is removed from activity, medical personnel typicallyadminister the appropriate assessments to confirm the presence of injury and the severity of the specific injury [2].  
At the sub-elite levels of sport, injury reporting can be less structured and is often carried out by individuals without formal training, such as coaches, parents, spectators, or the athletes themselves [3]. In many of these settings, traditional injury identification methods, such as athlete self-reporting [4; 5], or observer-based assessments [6], are prone to human error, underreporting [5], and subjective interpretation. Such limitations can delay injury management, or formal diagnosis and appropriate interventions, particularly in field-based settings. The dynamic nature of sports further complicates timely and accurate detection using conventional methods, especially when medical professionals may not be immediately available at sub-elite levels of sport [7].  
One of the many issues with the self-reporting of injury is the lack of education regarding the identification and severity of certain injuries, for example, sport-related concussion (SRC). In a study involving collegiate athletes who had experienced an SRC, less than 50% reported the injury, with 65% not reporting their injury, believing the injury was not serious enough to warrant medical attention [5].  
As injury management modalities advance, emerging technologies are being developed which offer greater accuracy and accessibility in injury detection. These technologies are increasingly capable of identifying and detecting injury events as they occur, even in field-based settings. There is a burgeoning interest in objective tools which aim to detect injuries and reduce human error. Although sports injuries are inherently unpredictable [8], the development of tools to aid in detection and identification may be useful.  
These tools aim to overcome the limitations of traditional detection approaches by providing objective, accessible data that can assist practitioners in making timely decisions.  
The existing reviews focus on injury prevention, rehabilitation, or predictive models, rather than the real-time identification of injury events. This systematic review aims to identify and evaluate peer-reviewed studies published in the last decade which utilise emerging technologies for the detection of sport-related injuries in field or competition environments. By assessing their methodologies, implementation contexts, and practical utility, this review seeks to inform the development, validation, and broader application of injury detection tools at all levels of sport [9; 10; 11]. This paper provides a novel contribution by critically assessing current tools used for the direct detection of sport-related injuries within their real-world contexts, rather than focusing on retrospective analyses or predictive models. This approach aims to inform both current discourse and the direction of future research.