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Khaled Arbateni and Amir Benzaoui
Electrocardiography (ECG) is a simple and safe tool for detecting heart conditions. Despite the diaspora of existing heartbeat classifiers, improvements such as real-time heartbeat identification and patient-independent classification persist. Reservoir ...
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Yi Zhao and Song-Kyoo Kim
This paper addresses the enhancement of modern security through the integration of electrocardiograms (ECGs) into biometric authentication systems. As technology advances, the demand for reliable identity authentication systems has grown, given the rise ...
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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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Jin Su Kim, Cheol Ho Song, Jae Myung Kim, Jimin Lee, Yeong-Hyeon Byeon, Jaehyo Jung, Hyun-Sik Choi, Keun-Chang Kwak, Youn Tae Kim, EunSang Bak and Sungbum Pan
Current advancements in biosignal-based user recognition technology are paving the way for a next-generation solution that addresses the limitations of face- and fingerprint-based user recognition methods. However, existing biosignal benchmark databases ...
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Maria Louro da Silva, Carolina Gouveia, Daniel Filipe Albuquerque and Hugo Plácido da Silva
Bio-Radar (BR) systems have shown great promise for biometric applications. Conventional methods can be forged, or fooled. Even alternative methods intrinsic to the user, such as the Electrocardiogram (ECG), present drawbacks as they require contact with...
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Abrar Alamr and Abdelmonim Artoli
Anomaly detection is one of the basic issues in data processing that addresses different problems in healthcare sensory data. Technology has made it easier to collect large and highly variant time series data; however, complex predictive analysis models ...
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Agostino Giorgio, Cataldo Guaragnella and Maria Rizzi
The high mortality rate associated with cardiac abnormalities highlights the need of accurately detecting heart disorders in the early stage so to avoid severe health consequence for patients. Health trackers have become popular in the form of wearable d...
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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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Nafisa Anjum, Khaleda Akhter Sathi, Md. Azad Hossain and M. Ali Akber Dewan
By using computer-aided arrhythmia diagnosis tools, electrocardiogram (ECG) signal plays a vital role in lowering the fatality rate associated with cardiovascular diseases (CVDs) and providing information about the patient?s cardiac health to the special...
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Khaled M. Abdelgaber, Mostafa Salah, Osama A. Omer, Ahmed E. A. Farghal and Ahmed S. Mubarak
In this paper, a beat-based autoencoder is proposed for mapping photoplethysmography (PPG) to a single-lead electrocardiogram (single-lead ECG) signal. The main limiting factors represented in uncleaned data, subject dependency, and erroneous beat segmen...
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