IDENTIFICATION OF FATIGUE-RELATED KINEMATIC CHANGES IN ELITE RUNNERS USING A SUPPORT VECTOR MACHINE APPROACH

Understanding the kinematic changes underlying fatigue is essential in running biomechanics. The aim of this study was to identify fatigue-related kinematic changes in elite runners using a support vector machine approach. Full-body kinematics of thirteen trained runners were recorded in a non-fatigued and a fatigued state during treadmill running at their individual fatigue-speed. A support vector machine was trained and used to identify kinematic differences between the non-fatigued and fatigued state based on principal component scores. Strides during non-fatigued and fatigued running could be separated with 99.4% classification accuracy. Four upper limb (two shoulder and two elbow), four lower limb (one ankle, two knee and one hip) and two trunk (one thoracic and one lumbar spine) principal component scores were identified as most discriminative kinematic features between non-fatigued and fatigued running. The findings of the study suggest the feasibility of a support vector machine approach to identify subtle fatigue-related kinematic changes in elite runners

WHY IS THE LEFT KNEE RATHER PRONE TO INJURY DURING TEAM HANDBALL-SPECIFIC SIDE-CUTTING MANEUVERS TO THE RIGHT?

The purpose of this study was the biomechanical inter-leg evaluation in three team handball-specific side-cutting maneuvers. This should help to gain a better understanding how different movement executions potentially produce harmful demands to one or both knee joints. Therefore, eight competitive handball player performed the three most common side-cutting maneuvers to the right side (side-cutting maneuver was performed with alternating or simultaneous steps) in a game-like setting in a movement laboratory. Movement data were collected with a 3D motion capture system and two linked 3D force plates. The analysis of the side-cutting maneuvers revealed increased vertical and medio-lateral ground reaction force components on the left leg, which initiated the side-cutting maneuver. The peak knee abduction moments in the weight acceptance phase did not differ between the left and the right leg in all three side-cutting maneuvers. However, higher peak knee valgus angles occurred at the left leg, which increased with increasing stance time. The results of this study indicate that during the performance of handball-specific side-cutting maneuvers to the right, the left knee joint has a greater risk to get injured. Consequently, athletes and coaches should place special focus on the movement execution of the cutting initiating leg to reduce the risk of knee injuries. Furthermore, leg explosive strength and core stability should be in major focus in training exercises to prepare the athlete for the demands in such high intensity movements

Rollator usage lets young individuals switch movement strategies in sit-to-stand and stand-to-sit tasks

The transitions between sitting and standing have a high physical and coordination demand, frequently causing falls in older individuals. Rollators, or four-wheeled walkers, are often prescribed to reduce lower-limb load and to improve balance but have been found a fall risk. This study investigated how rollator support affects sit-to-stand and stand-to-sit movements. Twenty young participants stood up and sat down under three handle support conditions (unassisted, light touch, and full support). As increasing task demands may affect coordination, a challenging floor condition (balance pads) was included. Full-body kinematics and ground reaction forces were recorded, reduced in dimensionality by principal component analyses, and clustered by k-means into movement strategies. Rollator support caused the participants to switch strategies, especially when their balance was challenged, but did not lead to support-specific strategies, i.e., clusters that only comprise light touch or full support trials. Three strategies for sit-to-stand were found: forward leaning, hybrid, and vertical rise; two in the challenging condition (exaggerated forward and forward leaning). For stand-to-sit, three strategies were found: backward lowering, hybrid, and vertical lowering; two in the challenging condition (exaggerated forward and forward leaning). Hence, young individuals adjust their strategy selection to different conditions. Future studies may apply this methodology to older individuals to recommend safe strategies and ultimately reduce falls

Estimation of Knee Joint Forces in Sport Movements Using Wearable Sensors and Machine Learning

Knee joint forces (KJF) are biomechanical measures used to infer the load on knee joint structures. The purpose of this study is to develop an artificial neural network (ANN) that estimates KJF during sport movements, based on data obtained by wearable sensors. Thirteen participants were equipped with two inertial measurement units (IMUs) located on the right leg. Participants performed a variety of movements, including linear motions, changes of direction, and jumps. Biomechanical modelling was carried out to determine KJF. An ANN was trained to model the association between the IMU signals and the KJF time series. The ANN-predicted KJF yielded correlation coefficients that ranged from 0.60 to 0.94 (vertical KJF), 0.64 to 0.90 (anterior–posterior KJF) and 0.25 to 0.60 (medial–lateral KJF). The vertical KJF for moderate running showed the highest correlation (0.94 ± 0.33). The summed vertical KJF and peak vertical KJF differed between calculated and predicted KJF across all movements by an average of 5.7% ± 5.9% and 17.0% ± 13.6%, respectively. The vertical and anterior–posterior KJF values showed good agreement between ANN-predicted outcomes and reference KJF across most movements. This study supports the use of wearable sensors in combination with ANN for estimating joint reactions in sports applications