Sun Chia-Chun, Tai Shen-Chuan
National Cheng Kung University, Tainan, Taiwan, ROC.
IEEE Trans Biomed Eng. 2005 Nov;52(11):1882-8. doi: 10.1109/TBME.2005.856270.
An electrocardiogram (ECG) data compression scheme is presented using the gain-shape vector quantization. The proposed approach utilizes the fact that ECG signals generally show redundancy among adjacent heartbeats and adjacent samples. An ECG signal is QRS detected and segmented according to the detected fiducial points. The segmented heartbeats are vector quantized, and the residual signals are calculated and encoded using the AREA algorithm. The experimental results show that with the proposed method both visual quality and the objective quality are excellent even in low bit rates. An average PRD of 5.97% at 127 b/s is obtained for the entire 48 records in the MIT-BIH database. The proposed method also outperforms others for the same test dataset.
提出了一种使用增益形状矢量量化的心电图（ECG）数据压缩方案。该方法利用了ECG信号在相邻心跳和相邻样本之间通常存在冗余这一事实。对ECG信号进行QRS检测，并根据检测到的基准点进行分段。对分段后的心跳进行矢量量化，并使用AREA算法计算和编码残差信号。实验结果表明，即使在低比特率下，该方法的视觉质量和客观质量都非常出色。对于MIT-BIH数据库中的全部48条记录，在127比特/秒时平均百分比根方差（PRD）为5.97%。对于相同的测试数据集，该方法也优于其他方法。
