Visualization deep learning model for automatic arrhythmias classification
Objective. With the improvement of living standards, heart disease has become one of the common diseases that threaten human health. Electrocardiography (ECG) is an effective way of diagnosing cardiovascular diseases. With the rapid growth of ECG examinations and the shortage of cardiologists, accurate and automatic arrhythmias classification has become a research hotspot. The main purpose of this paper is to improve accuracy in detecting abnormal ECG patterns. Approach. A hybrid 1D Resnet-GRU method, consisting of the Resnet and gated recurrent unit (GRU) modules, is proposed to implement classification of arrhythmias fro...
Source: Physiological Measurement - August 11, 2022 Category: Physiology Authors: Mingfeng Jiang, Yujie Qiu, Wei Zhang, Jucheng Zhang, Zhefeng Wang, Wei Ke, Yongquan Wu and Zhikang Wang Source Type: research
A systematic review of deep learning methods for modeling electrocardiograms during sleep
Sleep is one of the most important human physiological activities, and plays an essential role in human health. Polysomnography (PSG) is the gold standard for measuring sleep quality and disorders, but it is time-consuming, labor-intensive, and prone to errors. Current research has confirmed the correlations between sleep and the respiratory/circulatory system. Electrocardiography (ECG) is convenient to perform, and ECG data are rich in breathing information. Therefore, sleep research based on ECG data has become popular. Currently, deep learning (DL) methods have achieved promising results on predictive health care tasks ...
Source: Physiological Measurement - August 11, 2022 Category: Physiology Authors: Chenxi Sun, Shenda Hong, Jingyu Wang, Xiaosong Dong, Fang Han and Hongyan Li Source Type: research
Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular control
Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H...
Source: Physiological Measurement - August 11, 2022 Category: Physiology Authors: H élder Pinto, Riccardo Pernice, Maria Eduarda Silva, Michal Javorka, Luca Faes and Ana Paula Rocha Source Type: research
Monitoring residual kidney function in haemodialysis patients using timed urine collections: validation of the use of estimated blood results to calculate GFR
Objective. With growing recognition of the benefits of preserving residual kidney function (RKF) and use of incremental treatment regimes, the incentive to measure residual clearance in haemodialysis patients is increasing. Interdialytic urine collections used to monitor RKF in research studies are considered impractical in routine care, partly due to the requirement for blood samples before and after the collection. Plasma solute levels can be estimated if patients are in ‘steady state’, where urea and creatinine concentrations increase at a constant rate between dialysis sessions and are reduced by a constant ratio a...
Source: Physiological Measurement - August 2, 2022 Category: Physiology Authors: Elizabeth Lindley, David Keane, John Belcher, Nancy Fernandes Da Silva Jeffcoat, Simon Davies and BISTRO trial investigators Source Type: research
Modified photoplethysmography signal processing and analysis procedure for obtaining reliable stiffness index reflecting arteriosclerosis severity
This study aimed to describe a modified photoplethysmography (PPG) signal processing and analysis procedure to obtain a more reliable arterial stiffness index (SI). Approach. Three parameters were used to assess the PPG signal quality without prominent diastolic waves, which are similar to a sinusoidal waveform shape. The first parameter, sinusoidal ratio (S-value), was based on frequency-domain analysis: a higher S-value indicated the presence of PPG pulse wave with unapparent diastolic peak. The second parameter was the time difference between systolic peak-to-diastolic peak and the systolic peak-to-dicrotic notch. The t...
Source: Physiological Measurement - August 2, 2022 Category: Physiology Authors: Meng-Ting Wu, I-Fan Liu, Yun-Hsuan Tzeng and Lei Wang Source Type: research
An attention-based temporal convolutional network for rodent sleep stage classification across species, mutants and experimental environments with single-channel electroencephalogram
This study aims to promote well-standardized cross-laboratory sleep studies to improve our understanding of sleep. Our source codes and supplementary materials will be disclosed later. (Source: Physiological Measurement)
Source: Physiological Measurement - August 2, 2022 Category: Physiology Authors: Yuzheng Liu, Zhihong Yang, Yuyang You, Wenjing Shan and WeiKang Ban Source Type: research
Monitoring residual kidney function in haemodialysis patients using timed urine collections:
validation of the use of estimated blood results to calculate GFR
Objective . With growing recognition of the benefits of preserving residual kidney function (RKF)
and use of incremental treatment regimes, the incentive to measure residual clearance in
haemodialysis patients is increasing. Interdialytic urine collections used to monitor RKF in
research studies are considered impractical in routine care, partly due to the requirement for blood
samples before and after the collection. Plasma solute levels can be estimated if patients are in
'steady state', where urea and creatinine concentrations increase at a constant rate between
dialysis sessions and are reduced by a constant rati...
Source: Physiological Measurement - August 2, 2022 Category: Physiology Authors: Elizabeth Lindley, David Keane, John Belcher, Nancy Fernandes Da Silva Jeffcoat, Simon Davies and BISTRO trial investigators Source Type: research
Application of artificial intelligence techniques for automated detection of myocardial infarction:
a review
Objective. Myocardial infarction (MI) results in heart muscle injury due to receiving insufficient
blood flow. MI is the most common cause of mortality in middle-aged and elderly individuals
worldwide. To diagnose MI, clinicians need to interpret electrocardiography (ECG) signals, which
requires expertise and is subject to observer bias. Artificial intelligence-based methods can be
utilized to screen for or diagnose MI automatically using ECG signals. Approach. In this work, we
conducted a comprehensive assessment of artificial intelligence-based approaches for MI detection
based on ECG and some other biophysical sig...
Source: Physiological Measurement - August 2, 2022 Category: Physiology Authors: Javad Hassannataj Joloudari, Sanaz Mojrian, Issa Nodehi, Amir Mashmool, Zeynab Kiani Zadegan, Sahar Khanjani Shirkharkolaie, Roohallah Alizadehsani, Tahereh Tamadon, Samiyeh Khosravi, Mitra Akbari Kohnehshari, Edris Hassannatajjeloudari, Danial Sharifrazi Source Type: research
Modified photoplethysmography signal processing and analysis procedure for obtaining reliable
stiffness index reflecting arteriosclerosis severity
This study aimed to describe a modified photoplethysmography (PPG) signal processing and
analysis procedure to obtain a more reliable arterial stiffness index (SI). Approach. Three
parameters were used to assess the PPG signal quality without prominent diastolic waves, which are
similar to a sinusoidal waveform shape. The first parameter, sinusoidal ratio (S-value), was based
on frequency-domain analysis: a higher S-value indicated the presence of PPG pulse wave with
unapparent diastolic peak. The second parameter was the time difference between systolic
peak-to-diastolic peak and the systolic peak-to-dicrotic notch....
Source: Physiological Measurement - August 2, 2022 Category: Physiology Authors: Meng-Ting Wu, I-Fan Liu, Yun-Hsuan Tzeng and Lei Wang Source Type: research
An attention-based temporal convolutional network for rodent sleep stage classification across
species, mutants and experimental environments with single-channel electroencephalogram
This study aims to promote well-standardized
cross-laboratory sleep studies to improve our understanding of sleep. Our source codes and
supplementary materials will be disclosed later. (Source: Physiological Measurement)
Source: Physiological Measurement - August 2, 2022 Category: Physiology Authors: Yuzheng Liu, Zhihong Yang, Yuyang You, Wenjing Shan and WeiKang Ban Source Type: research
Automatic sleep stage classification based on a two-channel electrooculogram and one-channel electromyogram
Objective. Sleep monitoring by polysomnography (PSG) severely degrades sleep quality. In order to reduce the load of sleep monitoring, an approach to automatic sleep stage classification without an electroencephalogram (EEG) was proposed. Approach. A total of 124 records from the public dataset ISRUC-Sleep incorporating American Academy of Sleep Medicine (AASM) standards were used: 10 records were from the healthy group while the others were from sleep disorder groups. The 124 records were collected from 116 subjects (eight subjects had two records each, the others had one record each) with ages ranging from 20 to 85 years...
Source: Physiological Measurement - July 24, 2022 Category: Physiology Authors: Yanjun Li, Zhi Xu, Yu Zhang, Zhongping Cao and Hua Chen Source Type: research
A deep learning approach to estimate pulse rate by remote photoplethysmography
This study proposes a U-net shaped Deep Neural Network (DNN) model to extract remote
photoplethysmography (rPPG) signals from skin color signals to estimate Pulse Rate (PR). Approach.
Three input window sizes are used in the DNN: 256 samples (5.12 s), 512 samples (10.24 s), and 1024
(20.48 s). A data augmentation algorithm based on interpolation is also used here to artificially
increase the number of training samples. Main results. The proposed model outperformed a
prior-knowledge rPPG method by using input signals with window of 256 and 512 samples. Also, it was
found that the data augmentation procedure only incre...
Source: Physiological Measurement - July 24, 2022 Category: Physiology Authors: Lucas C ôgo Lampier, Carlos Torturella Valadão, Leticia Araújo Silva, Denis Delisle-Rodríguez, Eliete Maria de Oliveira Caldeira and Teodiano Freire Bastos-Filho Source Type: research
Automatic sleep stage classification based on a two-channel electrooculogram and one-channel
electromyogram
Objective. Sleep monitoring by polysomnography (PSG) severely degrades sleep quality. In order to
reduce the load of sleep monitoring, an approach to automatic sleep stage classification without an
electroencephalogram (EEG) was proposed. Approach. A total of 124 records from the public dataset
ISRUC-Sleep incorporating American Academy of Sleep Medicine (AASM) standards were used: 10 records
were from the healthy group while the others were from sleep disorder groups. The 124 records were
collected from 116 subjects (eight subjects had two records each, the others had one record each)
with ages ranging from 20 to 85...
Source: Physiological Measurement - July 24, 2022 Category: Physiology Authors: Yanjun Li, Zhi Xu, Yu Zhang, Zhongping Cao and Hua Chen Source Type: research
Lung area estimation using functional tidal electrical impedance variation images and active
contouring
We present two novel methods for estimating the lung area using functional tidal images or
active contouring methods. A convolutional neural network was trained to determine, whether or not
the heart region was visible within tidal images. In addition, the effects of lung area mirroring
were investigated. The performance of the methods and the effects of mirroring were evaluated via a
score based on the impedance magnitudes and their standard deviations in functional tidal images.
Main results. Our analyses showed that the method based on functional tidal images provided the best
estimate of the lung area. Mirroring ...
Source: Physiological Measurement - July 17, 2022 Category: Physiology Authors: Silke Borgmann, Kim Linz, Christian Braun, Patryk Dzierzawski, Sashko Spassov, Christin Wenzel and Stefan Schumann Source Type: research
Repeatability of ventilatory, metabolic and biomechanical responses to an intermittent incremental
swimming protocol
This study aimed to determine the repeatability of ventilatory, metabolic and
biomechanical variables assessed at a large spectrum of front crawl swimming intensities. We
hypothesized a strong agreement (combined with a small range of variation) between a typical step
protocol performed in two experimental moments. Approach . Forty competitive swimmers performed a
7 × (Source: Physiological Measurement)
Source: Physiological Measurement - July 17, 2022 Category: Physiology Authors: Ana Sofia Monteiro, Diogo D Carvalho, Ana El ói, Francisco Silva, João Paulo Vilas-Boas, Cosme F Buzzachera and Ricardo J Fernandes Source Type: research
