Patient-Specific Deep Architectural Model for ECG Classification

Heartbeat classification is a crucial step for arrhythmia diagnosis during electrocardiographic (ECG) analysis. The new scenario of wireless body sensor network- (WBSN-) enabled ECG monitoring puts forward a higher-level demand for this traditional ECG analysis task. Previously reported methods mainly addressed this requirement with the applications of a shallow structured classifier and expert-designed features. In this study, modified frequency slice wavelet transform (MFSWT) was firstly employed to produce the time-frequency image for heartbeat signal. Then the deep learning (DL) method was performed for the heartbeat classification. Here, we proposed a novel model incorporating automatic feature abstraction and a deep neural network (DNN) classifier. Features were automatically abstracted by the stacked denoising auto-encoder (SDA) from the transferred time-frequency image. DNN classifier was constructed by an encoder layer of SDA and a softmax layer. In addition, a deterministic patient-specific heartbeat classifier was achieved by fine-tuning on heartbeat samples, which included a small subset of individual samples. The performance of the proposed model was evaluated on the MIT-BIH arrhythmia database. Results showed that an overall accuracy of 97.5% was achieved using the proposed model, confirming that the proposed DNN model is a powerful tool for heartbeat pattern recognition

Methods and compositions for transgenic plants with enhanced cold tolerance, ability to flower without vernalization requirement and impacted fertility

The present invention provides transgenic plants having increased tolerance to cold and altered flowering characteristics. Also provided are methods and compositions for producing said transgenic plants

Comparative Study on Theory Model and Test Result for Dilute sulfuric Acid to Erode Concrete

AbstractIn order to find the action mechanism for dilute sulfuric acid to erode concrete, immersion test has been carried out to concrete samples for a long time. Under the premise that PH value of immersion solution is kept constant basically, acid-consuming speed of concrete sample is determined according to titer, and according to assumption of reaction boundary layer and dynamic model of chemical reaction, the theory formula that acid-consuming speed changes with time is deduced, and the action rule for sulfuric acid to erode concrete is obtained finally: course of test sample that acid-consuming speed changes with time can be divided into two phases, respectively quick erosion and stable erosion. According to analysis of immersion test data, test result and theory model are of high degree of fitting, and theory model is correct