Abdelazez Mohamed, Rajan Sreeraman, Chan Adrian D C
IEEE Trans Biomed Eng. 2022 Nov;69(11):3397-3406. doi: 10.1109/TBME.2022.3170047. Epub 2022 Oct 19.
Develop a signal quality index (SQI) to determine the quality of compressively sensed electrocardiogram (ECG) by estimating the signal-to-noise ratio (SNR).
The SQI used random forests, with the ratio of the standard deviations of an ECG segment and a clean ECG and the Wasserstein metric between the amplitude distributions of an ECG segment and a clean ECG, as features. The SQI was tested using the Long-Term Atrial Fibrillation Database (LTAFDB) and the PhysioNet/CinC Challenge 2011 Database Set A (CinCDB). Clean ECG segments from the LTAFDB were corrupted using simulated motion artifact, with preset SNR between -12 dB and 12 dB. The CinCDB was used as-it-is. The databases were compressively sensed using three types of sensing matrices at three compression ratios (50%, 75%, and 95%). For LTAFDB, the RMSE and Spearman correlation between the SQI and the preset SNR were used for evaluation, while for CinCDB, accuracy and F1 score were used.
The average RMSE was 3.18 dB and 3.47 dB in normal and abnormal ECG. The average Spearman correlation was 0.94 and 0.93 in normal and abnormal ECG, respectively. The average accuracy and F1 score were 0.90 and 0.88, respectively.
The SQI determined the quality of compressively sensed ECG and generalized across different databases. There was no consequential effect on the SQI due to abnormal ECG or compression using different sensing matrices and compression ratios.
Without reconstruction, the SQI can inform which ECG should be analyzed to reduce false alarms due to contamination.
通过估计信噪比（SNR）来开发一种信号质量指数（SQI），以确定压缩感知心电图（ECG）的质量。
该SQI使用随机森林，将心电图段与干净心电图的标准差之比以及心电图段与干净心电图的幅度分布之间的Wasserstein度量作为特征。使用长期房颤数据库（LTAFDB）和PhysioNet/CinC挑战2011数据库A组（CinCDB）对该SQI进行测试。来自LTAFDB的干净心电图段使用模拟运动伪影进行损坏，预设SNR在-12 dB至12 dB之间。CinCDB按原样使用。使用三种类型的感知矩阵以三种压缩率（50%、75%和95%）对数据库进行压缩感知。对于LTAFDB，使用SQI与预设SNR之间的均方根误差（RMSE）和Spearman相关性进行评估，而对于CinCDB，则使用准确率和F1分数进行评估。
正常和异常心电图中的平均RMSE分别为3.18 dB和3.47 dB。正常和异常心电图中的平均Spearman相关性分别为0.94和0.93。平均准确率和F1分数分别为0.90和0.88。
该SQI确定了压缩感知心电图的质量，并在不同数据库中具有通用性。由于异常心电图或使用不同感知矩阵和压缩率进行压缩，对SQI没有显著影响。
无需重建，该SQI可以告知应分析哪些心电图以减少由于污染导致的误报。
