窗口T期间第i导联θ波振幅的评分数据

在脑电信号采集过程中，θ波振幅的评分可以实时反映信号的质量。通过监测θ波振幅的波动和稳定性，可以及时发现并提示信号中的噪声或干扰，从而帮助研究人员或医生调整采集设备，提高信号采集的效率和准确性。除了实时分析外，θ波振幅的评分数据还可以用于离线分析。通过对大量采集到的脑电信号进行回顾性评估，可以进一步验证和优化信号质量评估方法，提高后续数据分析的可靠性和准确性。1.数据采集：统计窗口T期间θ波振幅的评分，该评分是根据第i导联的θ波的振幅来计算；检查导联中不超过阈值Thrθ振幅(Thrθ＝30μv)占比，超过Thrθ的采样点数越多，认为信号中的噪声就越多；θ波振幅分数Pθ记作为信号窗口T中不超过Thrθ的采样点数占总采样点数的百分比。2.数据处理：对采集到数据进行分类、合并、累加，便于分析使用。3.算法加工：将处理后的数据进行分析： Pθ＝(T1+T2+T3)*采样率/(T*采样率)。4、数据分类分级：根据导联和信号表现的关系，判断数据得出综合评分。4-8为合格，反之不合格。对高质量的脑电数据进行分析运算，忽略低质量的信号，提高BCI应用运行效率。本发明在不同噪声水平下具有较好的鲁棒性，评估信号质量的准确性较高。

During electroencephalogram (EEG) signal acquisition, the theta wave amplitude score can reflect signal quality in real time. By monitoring the fluctuations and stability of theta wave amplitude, noise or interference in the signal can be detected and alerted timely, helping researchers or clinicians adjust the acquisition equipment to improve the efficiency and accuracy of signal collection. Besides real-time analysis, the theta wave amplitude score data can also be used for offline analysis. Through retrospective evaluation of a large number of collected EEG signals, the signal quality assessment method can be further verified and optimized, enhancing the reliability and accuracy of subsequent data analysis.
1. Data Acquisition: Calculate the theta wave amplitude score during statistical window T, which is derived from the amplitude of theta wave in the i-th lead. Check the proportion of sampled points whose amplitude does not exceed the threshold Thrθ (Thrθ = 30 μV) in the lead: the more sampled points exceeding Thrθ, the more noise is considered to exist in the signal. The theta wave amplitude score Pθ is defined as the percentage of sampled points with amplitude not exceeding Thrθ in the signal window T relative to the total number of sampled points.
2. Data Processing: Classify, merge and accumulate the collected data to facilitate subsequent analysis.
3. Algorithm Processing: Analyze the processed data using the formula: Pθ = (T1 + T2 + T3) * sampling rate / (T * sampling rate).
4. Data Classification and Grading: Determine the comprehensive score of the data by judging the relationship between leads and signal performance. Scores ranging from 4 to 8 are qualified, while others are unqualified. Analyze and process high-quality EEG data while ignoring low-quality signals, so as to improve the operating efficiency of BCI (Brain-Computer Interface) applications. This invention exhibits good robustness under different noise levels and has high accuracy in signal quality assessment.

搜集汇总

数据集介绍

特点

该数据集包含700条脑电信号采集过程中θ波振幅的评分数据，用于实时和离线分析信号质量。数据通过特定算法处理，评估信号质量并提高脑机接口应用的效率，适用于科学研究和技术服务业。