AIMC Topic: Heart Rate

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Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review.

Sensors (Basel, Switzerland) Dec 6, 2022
Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body's center of mass and on the chest, respectively. Since their inception, their potenti...
Artificial Intelligence Electrocardiography Humans Respiratory Rate Ballistocardiography Signal Processing, Computer-Assisted Heart Rate
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Clipped DeepControl: Deep neural network two-dimensional pulse design with an amplitude constraint layer.

Artificial intelligence in medicine Nov 24, 2022
Advanced radio-frequency pulse design used in magnetic resonance imaging has recently been demonstrated with deep learning of (convolutional) neural networks and reinforcement learning. For two-dimensionally selective radio-frequency pulses, the (con...
Neural Networks, Computer Magnetic Resonance Imaging Phantoms, Imaging Heart Rate Radio Waves
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Machine Learning Techniques Outperform Conventional Statistical Methods in the Prediction of High Risk QTc Prolongation Related to a Drug-Drug Interaction.

Journal of medical systems Nov 23, 2022
In clinical practice, many drug therapies are associated with prolongation of the QT interval. In literature, estimation of the risk of prescribing drug-induced QT prolongation is mainly executed by means of logistic regression; only one paper report...
Heart Rate Female Male Drug Interactions Long QT Syndrome Machine Learning Algorithms Humans
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Generalisable machine learning models trained on heart rate variability data to predict mental fatigue.

Scientific reports Nov 21, 2022
A prolonged period of cognitive performance often leads to mental fatigue, a psychobiological state that increases the risk of injury and accidents. Previous studies have trained machine learning algorithms on Heart Rate Variability (HRV) data to det...
Machine Learning Algorithms Humans Mental Fatigue Heart Rate Rest
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Automated cell-type classification combining dilated convolutional neural networks with label-free acoustic sensing.

Scientific reports Nov 18, 2022
This study aimed to automatically classify live cells based on their cell type by analyzing the patterns of backscattered signals of cells with minimal effect on normal cell physiology and activity. Our previous studies have demonstrated that label-f...
Neural Networks, Computer Acoustics Heart Rate Artificial Intelligence Ultrasonography
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Wearable Devices for Remote Monitoring of Heart Rate and Heart Rate Variability-What We Know and What Is Coming.

Sensors (Basel, Switzerland) Nov 17, 2022
Heart rate at rest and exercise may predict cardiovascular risk. Heart rate variability is a measure of variation in time between each heartbeat, representing the balance between the parasympathetic and sympathetic nervous system and may predict adve...
Humans Heart Rate Artificial Intelligence Monitoring, Physiologic Reproducibility of Results Wearable Electronic Devices Arrhythmias, Cardiac
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Machine-Learning Classification of Pulse Waveform Quality.

Sensors (Basel, Switzerland) Nov 8, 2022
Pulse measurements made using wearable devices can aid the monitoring of human physiological condition. Accurate estimation of waveforms is often difficult for nonexperts; motion artifacts may occur during tonometry measurements when the skin-sensor ...
Radial Artery Machine Learning Reproducibility of Results Humans Blood Pressure Heart Rate
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Deep learning-based remote-photoplethysmography measurement from short-time facial video.

Physiological measurement Nov 3, 2022
. Efficient non-contact heart rate (HR) measurement from facial video has received much attention in health monitoring. Past methods relied on prior knowledge and an unproven hypothesis to extract remote photoplethysmography (rPPG) signals, e.g. manu...
Algorithms Deep Learning Heart Rate Research Design Photoplethysmography
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Classification and regression of stenosis using an in-vitro pulse wave data set: Dependence on heart rate, waveform and location.

Computers in biology and medicine Oct 21, 2022
BACKGROUND: Data-based approaches promise to use the information in cardiovascular signals to diagnose cardiovascular diseases. Considerable effort has been undertaken in the field of pulse-wave analysis to harness this information. However, the inve...
Pulse Wave Analysis Neural Networks, Computer Constriction, Pathologic Heart Rate Humans Blood Pressure Arteries
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Deep Learning-Based Energy Expenditure Estimation in Assisted and Non-Assisted Gait Using Inertial, EMG, and Heart Rate Wearable Sensors.

Sensors (Basel, Switzerland) Oct 18, 2022
Energy expenditure is a key rehabilitation outcome and is starting to be used in robotics-based rehabilitation through human-in-the-loop control to tailor robot assistance towards reducing patients’ energy effort. However, it is usually assessed by i...
Wearable Electronic Devices Walking Humans Energy Metabolism Gait Deep Learning Heart Rate
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