Relationship of Knee Abduction Moment to Trunk and Lower Extremity Segment Acceleration during Sport-specific Movements

Fortiton Caroline^*
*Correspondence: Fortiton Caroline, Department of Health Science and Psychology, Federation University Australia, SMB Campus, Australia, Email:

Keywords

Knee abduction moment • Trunk acceleration • Lower extremity segment acceleration • Injury prevention

Introduction

In the realm of sports biomechanics, understanding the intricate interplay between different segments of the body during movement is crucial for optimizing performance and preventing injuries. One such parameter of interest is the Knee Abduction Moment (KAM), which reflects the load distribution across the knee joint during dynamic movements. Particularly in sport-specific activities, the relationship between KAM and acceleration of trunk and lower extremity segments holds significance in delineating movement patterns and potential injury risks. This article delves into the complexities of this relationship, exploring its implications for athletes and sports practitioners. The KAM is a biomechanical measure that describes the tendency of the knee to adduct or move inward during activities such as walking, running, and jumping. It is often associated with increased stress on the medial compartment of the knee joint and is a known risk factor for various lower limb injuries, including Anterior Cruciate Ligament (ACL) injuries and Patellofemoral Pain Syndrome (PFPS). Monitoring KAM provides valuable insights into the biomechanical factors influencing knee joint integrity and function during movement [1].

Acceleration of trunk and lower extremity segments reflects the dynamic interactions between various body segments during motion. It encompasses the rate of change in velocity and direction of these segments, offering a comprehensive perspective on movement patterns and coordination. Trunk and lower extremity segment acceleration is influenced by factors such as muscle activation, joint angles, and external forces acting on the body, making it a multifaceted parameter to study in sports biomechanics. Research indicates a significant relationship between KAM and segment acceleration during sport-specific movements. Increased KAM is often associated with alterations in lower extremity kinematics and kinetics, leading to aberrant movement patterns and elevated injury risk. Specifically, higher KAM values have been linked to greater trunk and lower extremity segment acceleration, suggesting compromised biomechanical efficiency and control during dynamic tasks [2].

Literature Review

Sport-specific movements place unique demands on the musculoskeletal system, requiring coordinated activation of multiple muscle groups and precise control of joint kinematics to achieve optimal performance. However, these movements also expose athletes to increased risk of musculoskeletal injuries, particularly at the knee joint. Knee Abduction Moment (KAM), a measure of frontal plane knee joint loading, has been identified as a significant predictor of knee injury risk, particularly in activities involving cutting, pivoting, and landing maneuvers. Recent research has focused on understanding the biomechanical factors contributing to elevated KAM during sport-specific movements. One key aspect of this investigation is the relationship between KAM and trunk and lower extremity segment acceleration. Trunk and lower extremity segment acceleration patterns are indicative of movement strategy and neuromuscular control, which play critical roles in modulating joint loading and injury risk. Studies have demonstrated associations between increased KAM and specific movement patterns characterized by excessive trunk sway, hip adduction, and internal rotation during dynamic tasks such as cutting, jumping, and deceleration. These movement patterns are often observed in athletes with a history of knee injuries and are thought to contribute to abnormal loading of the knee joint, leading to increased injury risk [3].

Discussion

As we progress further into the realm of sports biomechanics, the integration of advanced technologies plays a pivotal role in enhancing our understanding of the relationship between Knee Abduction Moment (KAM) and segment acceleration. Here are some key advancements and their potential impact:

Wearable sensors: Wearable sensors, such as Inertial Measurement Units (IMUs) and pressure-sensing insoles, provide real-time data on movement patterns and loading distribution during sports activities. By incorporating these sensors into athletes' training regimens, coaches and sports scientists can monitor KAM and segment acceleration, identify movement deficiencies, and deliver immediate feedback for performance optimization and injury prevention [4].

Motion capture systems: Three-dimensional motion capture systems offer precise kinematic measurements of joint angles and segmental motion during dynamic tasks. Coupled with force plates and Electromyography (EMG), these systems enable comprehensive biomechanical analysis, allowing researchers to examine the relationship between KAM and segment acceleration with unparalleled accuracy. Integrating motion capture technology into sports performance centers and rehabilitation facilities facilitates personalized training programs tailored to athletes' biomechanical profiles.

Computational modeling: Computational modeling techniques, such as Finite Element Analysis (FEA) and musculoskeletal modeling, enable virtual simulations of complex biomechanical interactions within the body. By simulating different movement scenarios and loading conditions, researchers can elucidate the underlying mechanisms governing KAM and segment acceleration and optimize intervention strategies accordingly. Computational modeling also offers a platform for exploring the effects of external factors, such as footwear design and playing surface, on biomechanical outcomes, informing equipment development and injury prevention guidelines.

Artificial Intelligence (AI) and machine learning: AI algorithms and machine learning techniques can analyze vast amounts of biomechanical data to identify patterns, predict injury risk, and optimize training protocols. By leveraging AI-powered biomechanical models, coaches and sports practitioners can tailor intervention strategies based on individual athletes' biomechanical profiles, maximizing performance gains and minimizing injury incidence. Furthermore, AI-driven feedback systems provide real-time insights during training and competition, empowering athletes to make immediate adjustments to their movement mechanics and mitigate injury risk [5].

Understanding the relationship between KAM and segment acceleration holds several implications for athletes and sports practitioners:

Injury prevention: Monitoring KAM and segment acceleration can aid in identifying athletes at higher risk of knee injuries. By addressing biomechanical deficiencies and implementing targeted interventions, such as neuromuscular training and movement retraining, injury prevention strategies can be optimized.

Performance optimization: Optimizing movement patterns and biomechanical efficiency can enhance athletic performance and reduce energy expenditure during sport-specific activities. By focusing on minimizing KAM and segment acceleration through proper technique and strength conditioning, athletes can improve agility, speed, and overall athletic prowess.

Rehabilitation strategies: For athletes recovering from knee injuries or undergoing rehabilitation, assessing KAM and segment acceleration provides valuable feedback on progress and readiness to return to sport. Incorporating biomechanical analysis into rehabilitation programs allows for tailored interventions aimed at restoring optimal movement mechanics and reducing the risk of reinjury [6].

Equipment design: Insights gleaned from studying the relationship between KAM and segment acceleration can inform the design of sports equipment, such as footwear and orthotics. By considering biomechanical factors associated with knee joint loading and segmental acceleration, designers can develop products that promote biomechanical efficiency and reduce injury risk.

Conclusion

The relationship between knee abduction moment and trunk and lower extremity segment acceleration during sport-specific movements provides valuable insights into movement biomechanics and injury risk factors in athletes. By leveraging this knowledge, sports practitioners can develop targeted interventions to optimize performance, prevent injuries, and enhance overall athlete well-being. Continued research and interdisciplinary collaboration are essential for advancing our understanding of these complex relationships and improving sports biomechanics practice. Future directions in this field include longitudinal studies to track biomechanical changes over time, efficacy evaluations of intervention strategies, integration of wearable technology for real-time feedback, and continued multidisciplinary collaboration to bridge the gap between research and practice. By prioritizing athlete-centered approaches and leveraging cutting-edge biomechanical research, the sports community can strive towards a future where injuries are minimized, performance is optimized, and athletes can excel in their respective disciplines with confidence and resilience.

Acknowledgement

None.

Conflict of Interest

There are no conflicts of interest by author.

References

1. Brophy, Robert H., Jeffrey G. Stepan, Holly J. Silvers and Bert R. Mandelbaum. "Defending puts the anterior cruciate ligament at risk during soccer: A gender-based analysis." Sports Health 7 (2015): 244-249.

Google Scholar, Crossref, Indexed at

2. Butler, Lauren S., Eryn K. Milian, Amie DeVerna and Kevin Latz, et al. "Reliability of the Cutting Alignment Scoring Tool (CAST) to assess trunk and limb alignment during a 45-degree side-step cut." Int J Sports Phys Ther 16 (2021): 312.

Google Scholar, Crossref, Indexed at

3. Dos’Santos, Thomas, Alistair McBurnie, Thomas Donelon and Christopher Thomas, et al. "A qualitative screening tool to identify athletes with ‘high-risk’movement mechanics during cutting: The Cutting Movement Assessment Score (CMAS)." Phys Ther Sport 38 (2019): 152-161.

Google Scholar, Crossref, Indexed at

4. Weir, Gillian, Jacqueline Alderson, Natalie Smailes and Bruce Elliott, et al. "A reliable video-based ACL injury screening tool for female team sport athletes." Int J Sports Med 40 (2019): 191-199.

Google Scholar, Crossref, Indexed at

5. Boden, Barry P., Joseph S. Torg, Sarah B. Knowles and Timothy E. Hewett. "Video analysis of anterior cruciate ligament injury: Abnormalities in hip and ankle kinematics." Am J Sports Med 37 (2009): 252-259.

Google Scholar, Crossref, Indexed at

6. Kristianslund, Eirik, Oliver Faul, Roald Bahr and Grethe Myklebust, et al. "Sidestep cutting technique and knee abduction loading: Implications for ACL prevention exercises." Br J Sports Med 48 (2014): 779-783.

Google Scholar, Crossref, Indexed at