Authors:
K Zhang, B Guo, M Yang, Y Jia, K Zhang, L Wang
Publisher:
Nature, Scientific Reports
Abstract:
The assessment of sports performance has great significance for its scientific, targeting, and precision of training and teaching. It can provide a clear profile and real-time feedback for amateurs, athletes, and coaches to understand training results, identify their shortcomings, and adjust training plans1,2,3. Indexes of biomechanics are used to evaluate sport performance, such as 3D optical analysis tools (Vicon), force plates, and electromyography (EMG)4,5. But these evaluation methods are always conducted in laboratory settings and have certain limitations in using test results to guide training in real sport scenarios6,7. Athletes and coaches often rely on their observation to assess sport skills or metrics. However, the subjective judgment can be influenced by biases due to limitations of objective data, which will be an obstacle for precise improvements or corrections8. In other words, the gold standard evaluation methods can provide precise data in the current field of sports performance evaluation, but they lack authentic background conditions and are complex to operate. Therefore, to address these challenges innovative evaluation methods with precise, convenient, and feasible features in real sports settings is a great strategy for sports performance.
