Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
40000206
During long-term electrocardiogram (ECG) monitoring, various types of noise inevitably become mixed with the signal, potentially hindering doctors' ability to accurately assess and interpret patient data. Therefore, evaluating the quality of ECG sign...
Monitoring nociception under general anesthesia remains challenging due to the complexity of pain pathways and the limitations of single-parameter methods. In this study, we introduce a multimodal approach that integrates electroencephalogram (EEG), ...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
40000175
Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia feature...
Electrocardiogram (ECG) is widely used to provide early warning signals for cardiovascular diseases. However, traditional twelve-lead ECG monitoring methods and smartwatch-based home solutions are unable to achieve daily long-term monitoring. Therefo...
IEEE transactions on bio-medical engineering
40030245
This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) methods. Our objective is to enhance the accuracy and robustness of ECGI reconstructions. We reshape the ...
Data fusion, involving the simultaneous integration of signals from multiple sensors, is an emerging field that facilitates more accurate inferences in instrumentation applications. This paper presents a novel fusion methodology for multi-sensor mult...
BACKGROUND: Females are typically underserved in cardiovascular medicine. The use of sex as a dichotomous variable for risk stratification fails to capture the heterogeneity of risk within each sex. We aimed to develop an artificial intelligence-enha...
IEEE transactions on biomedical circuits and systems
40031210
Many electrocardiogram (ECG) processors have been widely used for cardiac monitoring. However, most of them have relatively low energy efficiency, and lack configurability in classification leads number and inference algorithm models. A multi-lead EC...
IEEE journal of biomedical and health informatics
40030784
Noninvasive fetal ECG (FECG) monitoring holds significant importance in ensuring the normal development of the fetus. Since FECG is usually submerged by maternal ECG (MECG) and background noise in abdominal ECG (AECG), it is challenging to exactly re...
IEEE journal of biomedical and health informatics
40030493
This paper conducts an extensive review of flexible cardiac sensing devices designed for electrocardiogram (ECG) acquisitions, with emphasis on their application in cardiac health monitoring. This study focuses on characteristics crucial to these dev...