AIMC Topic: Heart Rate

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Deep Learning Methods for Remote Heart Rate Measurement: A Review and Future Research Agenda.

Sensors (Basel, Switzerland) Sep 20, 2021
Heart rate (HR) is one of the essential vital signs used to indicate the physiological health of the human body. While traditional HR monitors usually require contact with skin, remote photoplethysmography (rPPG) enables contactless HR monitoring by ...
Monitoring, Physiologic Signal Processing, Computer-Assisted Heart Rate Humans Algorithms Deep Learning Photoplethysmography
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A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals.

Sensors (Basel, Switzerland) Sep 13, 2021
The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents in...
Humans Neural Networks, Computer Artificial Intelligence Cardiotocography Algorithms Heart Rate Pregnancy Heart Rate, Fetal Female
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Personal Resilience Can Be Well Estimated from Heart Rate Variability and Paralinguistic Features during Human-Robot Conversations.

Sensors (Basel, Switzerland) Aug 30, 2021
Mental health is as crucial as physical health, but it is underappreciated by mainstream biomedical research and the public. Compared to the use of AI or robots in physical healthcare, the use of AI or robots in mental healthcare is much more limited...
Speech Robotics Heart Rate Humans Communication Social Interaction
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Interpretation of Electrocardiogram Heartbeat by CNN and GRU.

Computational and mathematical methods in medicine Aug 29, 2021
The diagnosis of electrocardiogram (ECG) is extremely onerous and inefficient, so it is necessary to use a computer-aided diagnosis of ECG signals. However, it is still a challenging problem to design high-accuracy ECG algorithms suitable for the med...
Heart Rate Deep Learning Algorithms Humans Monitoring, Ambulatory Wavelet Analysis Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Neural Networks, Computer Wearable Electronic Devices Computational Biology Databases, Factual Diagnosis, Computer-Assisted
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LwF-ECG: Learning-without-forgetting approach for electrocardiogram heartbeat classification based on memory with task selector.

Computers in biology and medicine Aug 27, 2021
Most existing Electrocardiogram (ECG) classification methods assume that all arrhythmia classes are known during the training phase. In this paper, the problem of learning several successive tasks is addressed, where, in each new task, there are new ...
Machine Learning Electrocardiography Arrhythmias, Cardiac Humans Neural Networks, Computer Heart Rate
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The effect of principal component analysis in the diagnosis of congestive heart failure via heart rate variability analysis.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine Aug 7, 2021
In this study, we investigated the effect of principal component analysis (PCA) in congestive heart failure (CHF) diagnosis using various machine learning algorithms from 5-min HRV data. The extracted 59 heart rate variability (HRV) features consist ...
Heart Failure Heart Rate Support Vector Machine Principal Component Analysis Bayes Theorem Humans Algorithms
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Heart rate estimation from ballistocardiographic signals using deep learning.

Physiological measurement Jul 28, 2021
Ballistocardiography (BCG) is an unobtrusive approach for cost-effective and patient-friendly health monitoring. In this work, deep learning methods are used for heart rate estimation from BCG signals and are compared against five digital signal proc...
Ballistocardiography Humans Neural Networks, Computer Algorithms Deep Learning Heart Rate
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Artificial Intelligence-Enabled ECG to Identify Silent Atrial Fibrillation in Embolic Stroke of Unknown Source.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jul 22, 2021
OBJECTIVES: Embolic strokes of unknown source (ESUS) are common and often suspected to be caused by unrecognized paroxysmal atrial fibrillation (AF). An AI-enabled ECG (AI-ECG) during sinus rhythm has been shown to identify patients with unrecognized...
Time Factors Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Registries Electrocardiography, Ambulatory Male Middle Aged Risk Assessment Hospitalization Aged Aged, 80 and over Artificial Intelligence Atrial Fibrillation Female Heart Rate Humans Risk Factors Embolic Stroke
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Cross-Gram matrices and their use in transfer learning: Application to automatic REM detection using heart rate.

Computer methods and programs in biomedicine Jul 21, 2021
BACKGROUND AND OBJECTIVES: while traditional sleep staging is achieved through the visual - expert-based - annotation of a polysomnography, it has the disadvantages of being unpractical and expensive. Alternatives have been developed over the years t...
Humans Machine Learning Heart Rate Polysomnography Sleep Stages
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Prediction model for thyrotoxic atrial fibrillation: a retrospective study.

BMC endocrine disorders Jul 11, 2021
BACKGROUND: Thyrotoxic atrial fibrillation (TAF) is a recognized significant complication of hyperthyroidism. Early identification of the individuals predisposed to TAF would improve thyrotoxic patients' management. However, to our knowledge, an inst...
Heart Rate Models, Statistical Atrial Fibrillation Hyperthyroidism Case-Control Studies Follow-Up Studies Retrospective Studies Female Risk Factors Male Middle Aged Risk Assessment Humans Machine Learning Prognosis
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