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Monica Fira, Hariton-Nicolae Costin and Liviu Goras
We analyzed the possibility of detecting and predicting ventricular fibrillation (VF), a medical emergency that may put people?s lives at risk, as the medical prognosis depends on the time in which medical personnel intervene. Therefore, besides immediat...
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Krittapat Bannajak, Nipon Theera-Umpon and Sansanee Auephanwiriyakul
In this paper, we propose a lossless electrocardiogram (ECG) compression method using a prediction error-based adaptive linear prediction technique. This method combines the adaptive linear prediction, which minimizes the prediction error in the ECG sign...
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Bassam Al-Naami, Hossam Fraihat, Hamza Abu Owida, Khalid Al-Hamad, Roberto De Fazio and Paolo Visconti
Left bundle branch block (LBBB) is a common disorder in the heart?s electrical conduction system that leads to the ventricles? uncoordinated contraction. The complete LBBB is usually associated with underlying heart failure and other cardiac diseases. Th...
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Junbin Zang, Juliang Wang, Zhidong Zhang, Yongqiu Zheng and Chenyang Xue
Cardiovascular disease and its consequences on human health have never stopped and even show a trend of appearing in increasingly younger generations. The establishment of an excellent deep learning algorithm model to assist physicians in identifying and...
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Eko Ihsanto, Kalamullah Ramli, Dodi Sudiana and Teddy Surya Gunawan
The electrocardiogram (ECG) is relatively easy to acquire and has been used for reliable biometric authentication. Despite growing interest in ECG authentication, there are still two main problems that need to be tackled, i.e., the accuracy and processin...
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Jose Francisco Saenz-Cogollo and Maurizio Agelli
Finding an optimal combination of features and classifier is still an open problem in the development of automatic heartbeat classification systems, especially when applications that involve resource-constrained devices are considered. In this paper, a n...
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Yunfei Cheng, Ying Hu, Mengshu Hou, Tongjie Pan, Wenwen He and Yalan Ye
In the wearable health monitoring based on compressed sensing, atrial fibrillation detection directly from the compressed ECG can effectively reduce the time cost of data processing rather than classification after reconstruction. However, the existing m...
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Matteo D?Aloia, Annalisa Longo and Maria Rizzi
Cardiac signal processing is usually a computationally demanding task as signals are heavily contaminated by noise and other artifacts. In this paper, an effective approach for peak point detection and localization in noisy electrocardiogram (ECG) signal...
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Dengyong Zhang, Shanshan Wang, Feng Li, Jin Wang, Arun Kumar Sangaiah, Victor S. Sheng and Xiangling Ding
Electrocardiographic (ECG) signal is essential to diagnose and analyse cardiac disease. However, ECG signals are susceptible to be contaminated with various noises, which affect the application value of ECG signals. In this paper, we propose an ECG signa...
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