School of Physical Education Shanxi University, Taiyuan, Shanxi 030006, China.
Comput Intell Neurosci. 2022 Mar 19;2022:3917415. doi: 10.1155/2022/3917415. eCollection 2022.
. To explore the effect of different training load stimulation on heart rate variability level of Chinese elite female volleyball players. Through two-year follow-up experiment, this paper uses OmegaWave Sport Technology system to track and test the heart rate variability level and central nervous system parameters of 25 elite Chinese women volleyball players who participated in the national adult volleyball training in 2019 and 2020. It is found that the HRV time-domain index of the players under the stimulation of three stages of training load during the winter training in 2020 is determined. Frequency-domain index has significant influence on response stability of central nervous system. In order to further explore the influence of HRV on response stability of central nervous system, a feature classification method based on distance evaluation is proposed for experimental data processing. Through the multimodal human-machine interaction (M-HMI), advanced machine learning is used to promote the cooperative interaction between human and intelligent body. After analysis, SDNN and LF n.u. have a significant impact on the average reaction time. It shows that some indexes tested by the OmegaWave system can reflect the real-time physical function state of athletes sensitively and play an active role in diagnosis of fatigue of athletes' central nervous system. HRV time-domain and frequency-domain indexes, as parameters to evaluate the body functional state of excellent female volleyball players in the preparation process of competition, can sensitively reflect the level of autonomic nerve regulation of athletes in three different load stages.
. 探讨不同训练负荷刺激对中国优秀女排运动员心率变异性水平的影响。通过为期两年的随访实验,本文使用 OmegaWave Sport 技术系统跟踪和测试了 25 名参加 2019 年和 2020 年全国成人排球训练的中国优秀女排运动员的心率变异性水平和中枢神经系统参数。发现 2020 年冬训中三个阶段训练负荷刺激下运动员的 HRV 时域指标,频域指标对中枢神经系统反应稳定性有显著影响。为进一步探讨 HRV 对中枢神经系统反应稳定性的影响,对实验数据进行了基于距离评价的特征分类方法处理。通过多模态人机交互(M-HMI),采用先进的机器学习促进人机与智能体的协同交互。经分析,SDNN 和 LF n.u. 对平均反应时间有显著影响。表明 OmegaWave 系统测试的一些指标能敏感地反映运动员的实时身体机能状态,对运动员中枢神经系统疲劳的诊断具有积极作用。HRV 时域和频域指标作为评价优秀女排运动员比赛准备过程中身体机能状态的参数,能敏感地反映运动员在三个不同负荷阶段的自主神经调节水平。