| 摘要: |
| 针对人体疲劳程度检测问题，采集被测试者的脑电图（EEG）信号，利用阈值小波变换对EEG信号进行消噪处理，提取脑电波中的特征值，分析疲劳程度与特征值的相关性，建立脑电波信号与疲劳程度的数学模型，并用十折交叉验证法来验证该模型的准确率.结果表明：该模型检测人体疲劳程度的准确率可以达到96%以上. |
| 关键词: 脑电图(EEG)信号 疲劳程度 小波变换 数学模型 十折交叉验证法 |
| DOI：10.3969/J.ISSN.1000-5137.2019.01.018 |
| 分类号: |
| 基金项目: |
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| Analysis of human body's fatigue testing model based on EEG signals |
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GU Xuanxuan, LI Luqun, DU Rudong
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College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
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| Abstract: |
| For the detection of degree of human body's fatigue,we collected electroencephalographic(EEG) signals from the tested people.We eliminated the noise in the EEG signals by threshold wavelet transform technology,and extracted the eigenvalues in EEG signals.We analyzed the relationship between the fatigue and the eigenvalues,and built the mathematical model between EEG signals and the degree of fatigue.We verified the model by 10-fold cross-validation.The experimental results showed that the testing accuracy of the model reached up to 96%. |
| Key words: electroencephalographic (EEG) signals degree of fatigue wavelet transform mathematical model 10-fold cross-validation method |
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