Results 91 to 100 of about 169,837 (295)
ECG Signal Processing and Automatic Classification Algorithms
International Journal of Crowd ScienceWith heart health issues attracting much attention, wearable electrocardiogram (ECG) monitoring devices show a broad market prospect. This paper develops a generic ECG pre-processing algorithm and proposes a method for the single-lead ECG classification ...
Xiaonuo Yang, Yueting Chai
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Electrocardiographic localization of infarct related coronary artery in acute ST elevation myocardial infarction [PDF]
Journal of Clinical and Scientific Research, 2013 The electrocardiogram (ECG) remains a crucial tool in the identification and management of acute myocardial infarction (MI). A detailed analysis of patterns of ST-segment elevation may influence decisions regarding the use of reperfusion therapy.
C.S. Thejanandan Reddy +2 more
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ECG-SL: Electrocardiogram(ECG) Segment Learning, a deep learning method for ECG signal
, 2023 Electrocardiogram (ECG) is an essential signal in monitoring human heart activities. Researchers have achieved promising results in leveraging ECGs in clinical applications with deep learning models. However, the mainstream deep learning approaches usually neglect the periodic and formative attribute of the ECG heartbeat waveform.
Yu, Han, Yang, Huiyuan, Sano, Akane
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Hydrogel‐Based Functional Materials: Classifications, Properties, and Applications
Advanced Materials Technologies, Volume 11, Issue 7, 6 April 2026.Conductive hydrogels have emerged as promising materials for smart wearable devices due to their outstanding flexibility, multifunctionality, and biocompatibility. This review systematically summarizes recent progress in their design strategies, focusing on monomer systems and conductive components, and highlights key multifunctional properties such as
Zeyu Zhang, Zao Cheng, Patrizio Raffa
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Automatic diagnosis of the 12-lead ECG using a deep neural network
Nature Communications, 2020 The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. In that context, the authors present a Deep Neural Network (DNN) that recognizes different abnormalities in ECG recordings which ...
Antônio H. Ribeiro +11 more
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Adaptive Carbon Nanotube Patches for Versatile Electronic Textiles and Wind‐Harvesting Applications
Advanced Materials Technologies, EarlyView.An adhesion‐tunable electronic textile patch based on a carbon nanotube/paraffin composite is presented, enabling direct, adhesive‐free integration with fabrics. Pressure‐responsive bonding allows reversible or permanent attachment on demand.
Seokwon Joo +4 more
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Trend extraction in functional data of R and T waves amplitudes of exercise electrocardiogram
, 2016 The R and T waves amplitudes of the electrocardiogram recorded during the exercise test undergo strong modifications in response to stress. We analyze the time series of these amplitudes in a group of normal subjects in the framework of functional data ...
Cammarota, Camillo, Curione, Mario
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Fetal electrocardiogram (ECG) for fetal monitoring during labour [PDF]
Cochrane Database of Systematic Reviews, 2003 Hypoxaemia during labour can alter the shape of the fetal electrocardiogram (ECG) waveform, notably the relation of the PR to RR intervals, and elevation or depression of the ST segment. Technical systems have therefore been developed to monitor the fetal ECG during labour as an adjunct to continuous electronic fetal heart rate monitoring with the aim ...
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Advanced Materials Technologies, EarlyView.Combined approach of electromagnetic (Power) and ultrasound (data harvesting) waves is proposed to address the miniaturized ultrasonic implants. Electromagnetic waves trigger the piezoelectric element to generate the acoustic pulse which is modulated by the variations in the sensor's impedance.
Anam Bhatti +6 more
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