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An Open Access Database for Evaluating the Algorithms of Electrocardiogram Rhythm and Morphology Abnormality Detection
Signal Quality Assessment and Lightweight QRS Detection for Wearable ECG SmartVest System
It is demonstrated that the developed IoT-driven ECG SmartVest system can be applied for widely monitoring the population during daily life and has a promising application future.
Rule-Based Method for Morphological Classification of ST Segment in ECG Signals
A simple rule-based ST morphology classification method is proposed that identifies ST segments with the normal morphology type and five abnormal morphology sub-types: concave or convex elevation, up-sloping, down-Sloping, or horizontal depression.
Electrocardiogram Reconstruction Based on Compressed Sensing
This paper proposed novel CS algorithms for reconstructing under-sampled and compressed electrocardiogram (ECG) signal and found that the proposed CS scheme was capable of faithfully reconstructing ECG signals with only 30% acquisition.
Noise reduction in ECG signals using wavelet transform and dynamic thresholding
- Diptangshu Pandit, Li Zhang, C. Liu, N. Aslam, Samiran Chattopadhyay, C. Lim
- Computer Science, Engineering
A noise reduction algorithm which can be applied to noisy ECG (electrocardiogram) signals to obtain a higher signal-to-noise ratio (SNR) for further processing and is able to produce a higher SNR in the output signal than that in the raw test signals.
The Accuracy on the Common Pan-Tompkins Based QRS Detection Methods Through Low-Quality Electrocardiogram Database
Joint transform correlator based on CIELAB model with encoding technique for color pattern recognition
- Tiengsheng Lin, Chulung Chen, C. Liu, Yuming Chen
- Physics, Computer ScienceInternational Symposium on Advanced Optical…
- 13 May 2010
From the numerical results, it is found that the recognition ability based on CIELAB color specification system is accepted and the minimum average correlation energy approach to yield sharp correlation peak is used.
Classification of congestive heart failure with different New York Heart Association functional classes based on heart rate variability indices and machine learning
The SVM classifier performed better in classification than the CART classifier using the same HRV indices and the area under the curve of receiver operating characteristic for the two classifiers was 86.4% and 84.7%, respectively.
Signal processing and feature selection preprocessing for classification in noisy healthcare data
Pattern recognition by Mach-Zehnder joint transform correlator with binary power spectrum
A construction of the optoelectronic system with binary power spectrum is presented for target recognition. In the beginning, the minimum average correlation energy method is used to yield the…