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Keywords

Clinical Practice in Athletic Training

Abstract

Athletic training is entering a transformative period driven by the convergence of wearable technologies, artificial intelligence (AI), and advanced biomechanical modeling. Historically, wearable technology in sport was primarily used for performance tracking, including workload monitoring, heart rate assessment, and movement quantification. However, advances in sensor accuracy and data analytics have expanded the clinical relevance of wearable systems, allowing athletic trainers to monitor fatigue markers, movement asymmetry, and neuromuscular control patterns that inform injury risk and rehabilitation progression. Wearable sensor technologies provide objective data that can support clinical decision-making when integrated with traditional evaluation methods.¹Despite these advancements, wearable technologies present persistent barriers to widespread clinical adoption. Athlete compliance remains inconsistent because of device discomfort, behavioral resistance, and workflow disruption. Additionally, financial and infrastructure requirements limit accessibility across secondary schools, community athletic programs, and historically under-resourced institutions. Consumer wearable reviews have demonstrated variability in measurement accuracy and practical implementation challenges in physically active populations.¹,³ These barriers highlight the need for scalable monitoring solutions that maintain clinical value while minimizing athlete burden. Sensorless monitoring systems represent a promising evolution in athlete care. Using AI-driven computer vision, video-based motion analysis, and simulated datasets, sensorless technologies can evaluate movement patterns without requiring athlete-worn devices.² This approach improves compliance, reduces cost barriers, and expands access to advanced biomechanical analysis. For athletic trainers, sensorless monitoring offers an opportunity to integrate objective data collection into clinical workflows without increasing operational complexity while maintaining ecological validity during sport participation. The emergence of digital twin modeling further expands the potential of technology-assisted athletic training. Digital twins create virtual representations of athletes using historical, real-time, and simulated data inputs. These models allow clinicians to test rehabilitation progressions, training load adjustments, and return-to-play scenarios without exposing athletes to unnecessary physical risk. When paired with predictive modeling frameworks, digital twins may help identify early injury risk signals and optimize rehabilitation timelines while supporting clinician-driven decision-making. Complex systems approaches to sport injury demonstrate that injuries rarely occur from isolated variables and instead emerge from multiple interacting risk factors.⁴ In parallel, tensegrity-based biomechanical frameworks provide a system-level understanding of musculoskeletal function. Traditional rehabilitation models often focus on isolated joints or muscle groups. In contrast, tensegrity models conceptualize the body as a continuous tension network, emphasizing global load distribution and neuromuscular coordination.⁶ Integrating tensegrity principles with wearable or sensorless data may enhance rehabilitation precision and improve long-term injury resilience. Athletic trainers must play a central leadership role in technology implementation. Athletic trainers possess unique expertise in movement analysis, injury management, and patient-centered care. Their involvement in technology design and adoption ensures that emerging tools remain clinically relevant, ethically sound, and aligned with athlete safety. Failure to involve athletic trainers early in technology integration risks the development of systems that prioritize data collection over clinical applicability. Sensorless monitoring and simulated data modeling also offer pathways to reduce disparities in access to advanced athlete monitoring technologies. By lowering hardware costs and infrastructure demands, these systems can support equitable care delivery across youth sport, scholastic athletics, and resource-limited environments. Athletic trainers are uniquely positioned to lead this evolution and ensure that technological progress translates into meaningful improvements in athlete health outcomes.

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