Real time ECG characteristic point detection with randomly selected signal pair difference (RSSPD) feature and random forest classifier.

Detection of ECG characteristic points serves as a first step in many automated ECG analysis techniques. We propose a novel statistical scheme for ECG recognition. We design an effective feature, i.e. the randomly selected signal pair difference (RSSPD) feature, to effectively represent ECG morphology. The RSSPD generates a feature pool of signal pairs, and then a multi-class random forest is adopted in this work to train a classification model to detect all the ECG characteristic points simultaneously. After the post processing stage, the final output is generated. Our work provides robust and accurate detection performance in ECG datasets. The evaluation results on QT database show better detection accuracy compared with other studies.

Content Determination of Amygdalin in the Lianhua Qingwen Capsule by HPLC / 中国药房

OBJECTIVE:To establish a method for the content determination of amygdalin in Lianhua qingwen capsule. METH-ODS:HPLC was performed on the column of Phenomenex Kinetex XB-C18 with mobile phase of acetonitrile-0.2%Phosphoric acid so-lution(6∶94,V/V)at a flow rate of 1.0 ml/min,the detection wavelength was 207 nm,column temperature was 30℃,and the injec-tion volume was 10μl. RESULTS:The linear range of amygdalin was 43.16-215.80 μg/ml(r=0.999 7);the limit of detection was 0.431 6μg/ml,the limit of quantitation was 1.294 8μg/ml;RSDs of precision,stability and reproducibility tests no more than 0.69%;recovery was 95.16%-100.49%(RSD=1.67%,n=9). CONCLUSIONS:The method is simple and rapid with high accuracy and well reproducibility,and can be used for the content determination of amygdalin in Lianhua qingwen capsule.

High-accuracy stereo matching based on adaptive ground control points.

This paper proposes a novel high-accuracy stereo matching scheme based on adaptive ground control points (AdaptGCP). Different from traditional fixed GCP-based methods, we consider color dissimilarity, spatial relation, and the pixel-matching reliability to select GCP adaptively in each local support window. To minimize the global energy, we propose a practical solution, named as alternating updating scheme of disparity and confidence map, which can effectively eliminate the redundant and interfering information of unreliable pixels. The disparity values of those unreliable pixels are reassigned with the information provided by local plane model, which is fitted with GCPs. Then, the confidence map is updated according to the disparity reassignment and the left-right consistency. Finally, the disparity map is refined by multistep filers. Quantitative evaluations demonstrate the effectiveness of our AdaptGCP scheme for regularizing the ill-posed matching problem. The top ranks on Middlebury benchmark with different error thresholds show that our algorithm achieves the state-of-the-art performance among the latest stereo matching algorithms. This paper provides a new insight toward high-accuracy stereo matching.