Physical Education Department, Hebei Academy of Fine Arts, Shijiazhuang 050700, Hebei, China.
J Healthc Eng. 2022 Feb 17;2022:8114740. doi: 10.1155/2022/8114740. eCollection 2022.
At present, in sports training for volleyball, it still mainly depends on the personal experience of the coach. Training costs are high, and the quality is difficult to maintain stable. Even with the introduction of training assistance software, it is often necessary to manually enter complex data, and the research samples are mostly single individuals. Serving is one of the basic and important technical movements of volleyball, and its standardization is of great significance to the stable performance of the scene. This article proposes an analysis of the volleyball player's arm trajectory based on the background of human posture recognition and analysis, based on the neural network model. The changes in the angles of the shoulders, elbows, and wrist when serving the ball reflect the different trajectories of the arm. Experiments show that the height of the throwing arm from the ground accounts for 98% of the height. The horizontal angle of the throwing arm at the moment the ball leaves the hand is positively correlated with the throwing time and height, and the reasonable trajectory has an impact on the stability of the throwing ball. The closer the trajectory of the tossing arm is to the vertical, the more stable the tossing is.
目前，在排球运动训练中，仍然主要依赖于教练的个人经验。培训成本高，质量难以保持稳定。即使引入了训练辅助软件，通常也需要手动输入复杂的数据，并且研究样本大多是单个个体。发球是排球的基本和重要技术动作之一，其规范化对现场的稳定表现具有重要意义。本文基于人体姿势识别和分析的背景，提出了一种基于神经网络模型的排球运动员手臂轨迹分析方法。发球时肩部、肘部和手腕角度的变化反映了手臂的不同轨迹。实验表明，投掷手臂离地的高度占总高度的 98%。球出手瞬间投掷手臂的水平角度与投掷时间和高度呈正相关，合理的轨迹对投掷球的稳定性有影响。投掷臂的轨迹越接近垂直，投掷就越稳定。
