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Background: This field experiment investigated the acute effects of brief mindfulness-based intervention (MBI) coupled with carbohydrate (CHO) intake on players’ recovery from half-time break in a simulated soccer competition. Methods: In a single-blinded randomized crossover experiment, 14 male players received 3 treatments (Control: non-carbohydrate solution + travelling introduction audio; CHO: CHO–electrolyte solution + travelling introduction audio; and CHO_M: CHO–electrolyte solution + MBI) during simulated half-time breaks. Vertical jump, sprint performance, mindfulness level, rate of perceived exertion, muscle pain, mental fatigue, blood glucose, and lactate were measured immediately before, during, and after the exercise. Results: (1) MBI significantly increased participants’ mindfulness level (Control vs. CHO_M, p < 0.01; CHO vs. CHO_M, p < 0.01) and decreased mental fatigue for CHO_M condition (pre vs. post, p < 0.01); (2) participants in the CHO_M condition performed better in the repeated sprint tests than in the Control and CHO condition (Control vs. CHO_M, p = 0.02; CHO vs. CHO_M, p = 0.02). Conclusion: Findings of this study provide preliminary evidence of the positive effect of MBI coupled with CHO ingestion on athletes’ recovery from fatigue in the early stage of the second half of a game.

Wearable sensors facilitate running kinematics analysis of joint kinematics in real running environments. The use of a few sensors or, ideally, a single inertial measurement unit (IMU) is preferable for accurate gait analysis. This study aimed to use a convolutional neural network (CNN) to predict level-ground running kinematics (measured by four IMUs on the lower extremities) by using treadmill running kinematics training data measured using a single IMU on the anteromedial side of the right tibia and to compare the performance of level-ground running kinematics predictions between raw accelerometer and gyroscope data. The CNN model performed regression for intraparticipant and interparticipant scenarios and predicted running kinematics. Ten recreational runners were recruited. Accelerometer and gyroscope data were collected. Intraparticipant and interparticipant R2 values of actual and predicted running kinematics ranged from 0.85 to 0.96 and from 0.7 to 0.92, respectively. Normalized root mean squared error values of actual and predicted running kinematics ranged from 3.6% to 10.8% and from 7.4% to 10.8% in intraparticipant and interparticipant tests, respectively. Kinematics predictions in the sagittal plane were found to be better for the knee joint than for the hip joint, and predictions using the gyroscope as the regressor were demonstrated to be significantly better than those using the accelerometer as the regressor.

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