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Heart Rate

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RPnet: A Deep Learning approach for robust R Peak detection in noisy ECG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic detection of R-peaks in an Electrocardiogram signal is crucial in a multitude of applications including Heart Rate Variability (HRV) analysis and Cardio Vascular Disease(CVD) diagnosis. Although there have been numerous approaches that have...

High Accuracy Respiration and Heart Rate Detection Based on Artificial Neural Network Regression.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A 24GHz Doppler radar system for accurate contactless monitoring of heart and respiratory rates is demonstrated here. High accuracy predictions are achieved by employing a CNN+LSTM neural network architecture for regression analysis. Detection accura...

Deep learning for comprehensive ECG annotation.

Heart rhythm
BACKGROUND: Increasing utilization of long-term outpatient ambulatory electrocardiographic (ECG) monitoring continues to drive the need for improved ECG interpretation algorithms.

Novel Imaging Revealing Inner Dynamics for Cardiovascular Waveform Analysis via Unsupervised Manifold Learning.

Anesthesia and analgesia
BACKGROUND: Cardiovascular waveforms contain information for clinical diagnosis. By learning and organizing the subtle change of waveform morphology from large amounts of raw waveform data, unsupervised manifold learning helps delineate a high-dimens...

Prediction of fatal adverse prognosis in patients with fever-related diseases based on machine learning: A retrospective study.

Chinese medical journal
BACKGROUND: Fever is the most common chief complaint of emergency patients. Early identification of patients at an increasing risk of death may avert adverse outcomes. The aim of this study was to establish an early prediction model of fatal adverse ...

Wearable health devices and personal area networks: can they improve outcomes in haemodialysis patients?

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Digitization of healthcare will be a major innovation driver in the coming decade. Also, enabled by technological advancements and electronics miniaturization, wearable health device (WHD) applications are expected to grow exponentially. This, in tur...

Intelligent infusion controller with a physiological information feedback function.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: In hospitals, some problems still exist, such as transfusion reaction that cannot be dealt with in time, medical staff cannot observe the physiological information of the infusion patients in real time, and the infusion speed cannot be co...

[Clinical research of target guided treatment of patients with severe heart failure under the guidance of pulse indicator continuous cardiac output].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To investigate the value of pulse indicator continuous cardiac output (PiCCO) monitoring in the treatment management of patients with severe heart failure.

[Heartbeat-based end-to-end classification of arrhythmias].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: We propose a heartbeat-based end-to-end classification of arrhythmias to improve the classification performance for supraventricular ectopic beat (SVEB) and ventricular ectopic beat (VEB).

Artificial neural networks-based classification of emotions using wristband heart rate monitor data.

Medicine
Heart rate variability (HRV) is an objective measure of emotional regulation. This study aimed to estimate the accuracy with which an artificial neural network (ANN) algorithm could classify emotions using HRV data that were obtained using wristband ...