Alternative TitleMotion Capture Based Measurement Technology for Mental Fatigue under Body Weight Support Situation.
马倩颖; 吴瑞林; 王亚猛; 刘晓倩; 朱廷劭; 王伟强
First Author马倩颖
Source Publication航天医学与医学工程
Contribution Rank2
Other AbstractTo test the reliability of measuring the mental fatigue with joint motion characteris tics by motion capture and computer technology in the body weight support situation. Methods Mental fatigue was induced by prolonged cognitive tasks and then was evaluated using a series of psychological questionnaires. Kinect was used to identify and track 25 joint points during the 2-minute running exercise in the body weight support situation for each subject to get data acquisition. The Uaussian process regression algorithm was used to establish a model between the psychological scale and the motion capture data. Pearson correlation and root mean square error (RMSE) were applied for testing models. Results Based on the time-space characteristics of joint motion,the individual’s mental fatigue could be measured under body weight support situation. The mean correlation coefficient between the predicted value and the real scores of the fatigue was 0.44,the RMSE was 2.94,meanwhile,the mean correlation in mood states was 0.45,and the RMSE was 5.49. Conclusion The joint motion information can be used as an effective biometric to predict the mental fatigue. When the space or resources are limited,the psychological index prediction model based on the motion capture and machine learning methods can provide a new perspective in the future space missions.
Keyword心理疲劳状态 动作捕捉 时间-空间特征 高斯过程回归模型
Project Intro.载人航天领域预先研究项目(17440207)
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Document Type期刊论文
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GB/T 7714
马倩颖,吴瑞林,王亚猛,等. 基于动作捕捉的减重条件下心理疲劳状态测量技术[J]. 航天医学与医学工程,2019,32(04):291-298.
APA 马倩颖,吴瑞林,王亚猛,刘晓倩,朱廷劭,&王伟强.(2019).基于动作捕捉的减重条件下心理疲劳状态测量技术.航天医学与医学工程,32(04),291-298.
MLA 马倩颖,et al."基于动作捕捉的减重条件下心理疲劳状态测量技术".航天医学与医学工程 32.04(2019):291-298.
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