Physiological Measurement

Papers
(The H4-Index of Physiological Measurement is 21. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-05-01 to 2025-05-01.)
ArticleCitations
Interbeat interval-based sleep staging: work in progress toward real-time implementation79
Pilot study of contactless sleep apnea detection based on snore signals with hardware implementation52
Exploring novel algorithms for atrial fibrillation detection by driving graduate level education in medical machine learning50
Spatial–temporal features-based EEG emotion recognition using graph convolution network and long short-term memory49
A wireless physiological parameter monitoring system with a treatment feedback function during neonatal phototherapy45
Video based non-contact monitoring of respiratory rate and chest indrawing in children with pneumonia44
Bio-potential noise of dry printed electrodes: physiology versus the skin-electrode impedance43
Lung area estimation using functional tidal electrical impedance variation images and active contouring40
One-week test–retest stability of heart rate variability during rest and deep breathing36
LumEDA: image luminance based contactless correlates of electrodermal responses35
Determinants of the dynamic cerebral critical closing pressure response to changes in mean arterial pressure33
MLP-RL-CRD: diagnosis of cardiovascular risk in athletes using a reinforcement learning-based multilayer perceptron32
Electrical-tomographic imaging of physiological-induced conductive response in calf muscle compartments during voltage intensity change of electrical muscle stimulation (vic-EMS)29
Accessibility and use of novel methods for predicting physical activity and energy expenditure using accelerometry: a scoping review28
Predicting seizure episodes and high-risk events in autism through adverse behavioral patterns28
End-to-end sensor fusion and classification of atrial fibrillation using deep neural networks and smartphone mechanocardiography27
LDSG-Net: an efficient lightweight convolutional neural network for acute hypotensive episode prediction during ICU hospitalization26
Automatic identifying OSAHS patients and simple snorers based on Gaussian mixture models25
A low-cost PPG sensor-based empirical study on healthy aging based on changes in PPG morphology25
Analysis of relative changes in pulse shapes of intracranial pressure and cerebral blood flow velocity24
Accuracy and applicability of non-invasive evaluation of aortic wave intensity using only pressure waveforms in humans24
ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization21
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