A unified framework for multi-lead ECG characterization using Laplacian Eigenmaps
Background. The analysis of multi-lead electrocardiographic (ECG) signals requires integrating the information derived from each lead to reach clinically relevant conclusions. This analysis could benefit from data-driven methods compacting the information in those leads into lower-dimensional representations (i.e. 2 or 3 dimensions instead of 12). Objective. We propose Laplacian Eigenmaps (LE) to create a unified framework where ECGs from different subjects can be compared and their abnormalities are enhanced. Approach. We conceive a normal reference ECG space based on LE, calculated using signals of healthy subjects in si...
Source: Physiological Measurement - July 23, 2023 Category: Physiology Authors: Amalia Villa, Sebastian Ingelaere, Ben Jacobs, Bert Vandenberk, Sabine Van Huffel, Rik Willems and Carolina Varon Source Type: research
ETucker: a constrained tensor decomposition for single trial ERP extraction
Objective. In this paper, we propose a new tensor decomposition to extract event-related potentials (ERP) by adding a physiologically meaningful constraint to the Tucker decomposition. Approach. We analyze the performance of the proposed model and compare it with Tucker decomposition by synthesizing a dataset. The simulated dataset is generated using a 12th-order autoregressive model in combination with independent component analysis (ICA) on real no-task electroencephalogram (EEG) recordings. The dataset is manipulated to contain the P300 ERP component and to cover different SNR conditions, ranging from 0 to −30 dB, to ...
Source: Physiological Measurement - July 20, 2023 Category: Physiology Authors: Behrad TaghiBeyglou and Mohammad Bagher Shamsollahi Source Type: research
Secondary electrocardiographic stratification of NSTEMI to identify an acutely occluded culprit artery
In the United States, approximately 720 000 adults will experience a myocardial infarction (MI) every year. The 12-lead electrocardiogram (ECG) is quintessential for the classification of a MI. About 30% of all MIs exhibit ST-segment elevation on the 12-lead ECG and is therefore classified as an ST-Elevation Myocardial Infarction (STEMI), which is treated emergently with percutaneous coronary intervention to restore blood flow. However, in the remaining 70% of MIs, the 12-lead ECG lacks ST-segment elevation and instead exhibits a motley of changes, including ST-segment depression, T-wave inversion, or, in up to 20% of pati...
Source: Physiological Measurement - July 16, 2023 Category: Physiology Authors: Dillon J Dzikowicz and Mary G Carey Source Type: research
Validity of ActivPAL CREA software detection of sitting and lying during free-living conditions
Objective. Approaches to differentiate sitting and lying are available within the default activPAL software from a single thigh-worn monitor. Dual-monitor methods use multiple monitors positioned on the thigh and torso to characterize sitting versus lying. We evaluated the validity between these two methods to measure waking, sitting, and lying time in free-living conditions. We also examined if the degree-threshold distinguishing sitting/lying for the dual-monitor (<30 ° and<45 °) impacted results. Approach. Thirty-five young adults (24 ± 3 years, 16 females) wore an activPAL 24 h per day on their thigh and torso...
Source: Physiological Measurement - July 12, 2023 Category: Physiology Authors: Madeline E Shivgulam, Ryan J Frayne, Beverly D Schwartz, Yanlin Wu, W Seth Daley, Derek S Kimmerly and Myles W O'Brien Source Type: research
BTCRSleep: a boundary temporal context refinement-based fully convolutional network for sleep staging with single-channel EEG
This study attempts to capture the boundary context, which contains the characteristics of brain waves during sleep stage transition, to improve the performance of sleep staging. Approach. In this paper we propose a fully convolutional network with boundary temporal context refinement, called BTCRSleep (Boundary Temporal Context Refinement Sleep). The boundary temporal context refinement module refines the boundary information on sleep stages on the basis of extracting multi-scale temporal dependences between epochs and enhances the abstract capability of the boundary temporal context. In addition, we design a class-aware ...
Source: Physiological Measurement - July 12, 2023 Category: Physiology Authors: Caihong Zhao, Jinbao Li and Yahong Guo Source Type: research
Automatic ECG-based detection of left ventricular hypertrophy and its predictive value in haemodialysis patients
This study provides evidence that automatic algorithms can be as reliable in LVH parameter assessment and risk predict ion as manual measurements in ESKD patients undergoing haemodialysis. (Source: Physiological Measurement)
Source: Physiological Measurement - July 9, 2023 Category: Physiology Authors: Theresa Letz, Carina H örandtner, Matthias C Braunisch, Peter Gundel, Julia Matschkal, Martin Bachler, Georg Lorenz, Andrea Körner, Carolin Schaller, Moritz Lattermann, Andreas Holzinger, Uwe Heemann, Siegfried Wassertheurer, Christoph Schmaderer and Ch Source Type: research
Using the ear photoplethysmographic waveform as an early indicator of central hypovolemia in healthy volunteers utilizing LBNP induced hypovolemia model
Objective. To study the photoplethysmographic (PPG) waveforms of different locations (ear and finger) during lower body negative pressure (LBNP) induced hypovolemia. Then, to determine whether the PPG waveform can be used to detect hypovolemia during the early stage of LBNP. Approach. 36 healthy volunteers were recruited for progressive LBNP induced hypovolemia, with an endpoint of −60 mmHg or development of hypoperfusion symptoms, whichever comes first. Subjects tolerating the entire protocol without symptoms were designated as high tolerance (HT), while symptomatic subjects were designated as low tolerance (LT). Subjec...
Source: Physiological Measurement - July 9, 2023 Category: Physiology Authors: Anna-Maria Eid, Mohamed Elgamal, Antonio Gonzalez-Fiol, Kirk H Shelley, Hau-Tieng Wu and Aymen Awad Alian Source Type: research
CS-based multi-task learning network for arrhythmia reconstruction and classification using ECG signals
Objective. Although deep learning-based current methods have achieved impressive results in electrocardiograph (ECG) arrhythmia classification issues, they rely on using the original data to identify arrhythmia categories. However, a large amount of data generated by long-term ECG monitoring pose a significant challenge to the limited-bandwidth and real-time systems, which limits the application of deep learning in ECG monitoring. Approach. This paper, therefore, proposed a novel multi-task network that combined compressed sensing and convolutional neural networks, namely CSML-Net. According to the proposed model, the ECG ...
Source: Physiological Measurement - July 4, 2023 Category: Physiology Authors: Suigu Tang and Zicong Deng Source Type: research
Automatic identification of intracranial pressure waveform during external ventricular drainage clamping: segmentation via wavelet analysis
Conclusion. The proposed algorithm automates the identification of valid ICP waveform segments of waveform in EVD data and thus enables the inclusion in real-time data analysis for decision support. It also standardizes and makes research data management more efficient. (Source: Physiological Measurement)
Source: Physiological Measurement - July 3, 2023 Category: Physiology Authors: Murad Megjhani, Kalijah Terilli, Soon Bin Kwon, Daniel Nametz, Bennett Weinerman, Angela Velazquez, Shivani Ghoshal, David Roh, Sachin Agarwal, E Sander Connolly, Jan Claassen and Soojin Park Source Type: research
Calibration of a three-state cell death model for cardiomyocytes and its application in radiofrequency ablation
Objective. Thermal cellular injury follows complex dynamics and subcellular processes can heal the inflicted damage if insufficient heat is administered during the procedure. This work aims to the identification of irreversible cardiac tissue damage for predicting the success of thermal treatments. Approach. Several approaches exist in the literature, but they are unable to capture the healing process and the variable energy absorption rate that several cells display. Moreover, none of the existing models is calibrated for cardiomyocytes. We consider a three-state cell death model capable of capturing the reversible damage...
Source: Physiological Measurement - June 26, 2023 Category: Physiology Authors: Argyrios Petras, Massimiliano Leoni, Jose M Guerra and Luca Gerardo-Giorda Source Type: research
Evaluation of cardiovascular and cerebrovascular control mechanisms in postural orthostatic tachycardia syndrome via conditional transfer entropy: the impact of the respiratory signal type
This study aims at characterizing CV and CBV controls in postural orthostatic tachycardiac syndrome (POTS) subjects experiencing exaggerated sympathetic response during orthostatic challenge via unconditional TE and TE conditioned on respiratory activity (R). Approach. In 18 healthy controls (age: 28 ± 13 yrs; 5 males, 13 females) and 15 POTS individuals (age: 29 ± 11 yrs; 3 males, 12 females) we acquired beat-to-beat variability of HP, SAP, MAP and MCBv and two R signals, namely respiratory chest movement (RCM) and capnogram (CAP). Recordings were made at sitting rest and during active standi ng (STAND). TE was computed...
Source: Physiological Measurement - June 18, 2023 Category: Physiology Authors: Francesca Gelpi, Vlasta Bari, Beatrice Cairo, Beatrice De Maria, Rachel Wells, Mathias Baumert and Alberto Porta Source Type: research
Corrigendum: Analysis of an adaptive lead weighted ResNet for multiclass classification of 12-Lead ECGs (2022 Physiol. Meas.
43 034001)
(Source: Physiological Measurement)
Source: Physiological Measurement - June 18, 2023 Category: Physiology Authors: Z Zhao, D Murphy, H Gifford, S Williams, A Darlington, S Relton, H Fang and D C Wong Source Type: research
Hemodynamic monitoring in the human temporalis muscle using near-infrared spectroscopy
Objective. Altered temporal muscle perfusion is implicated in several painful disorders afflicting orofacial and head regions, including temporomandibular joint dysfunctions, bruxism, and headache. Knowledge about the regulation of blood supply to the temporalis muscle is limited, due to methodological difficulties. The study aimed to test the feasibility of near-infrared spectroscopy (NIRS) monitoring of the human temporal muscle. Approach. Twenty-four healthy subjects were monitored with a 2-channel NIRS: a muscle probe placed over the temporal muscle and a brain probe placed on the forehead. A series of teeth clenching ...
Source: Physiological Measurement - June 12, 2023 Category: Physiology Authors: Anas Rashid and Silvestro Roatta Source Type: research
State-of-the-art mental tasks classification based on electroencephalograms: a review
Electroencephalograms (EEGs) play an important role in analyzing different mental tasks and neurological disorders. Hence, they are a critical component for designing various applications, such as brain –computer interfaces, neurofeedback, etc. Mental task classification (MTC) is one of the research focuses in these applications. Therefore, numerous MTC techniques have been proposed in literary works. Although various literature reviews exist based on EEG signals for different neurological disord ers and behavior analysis, there is a lack of reviews of state-of-the-art MTC techniques. Therefore, this paper presents a det...
Source: Physiological Measurement - June 11, 2023 Category: Physiology Authors: M Saini and U Satija Source Type: research
Spatial –temporal features-based EEG emotion recognition using graph convolution network and long short-term memory
Objective. Emotion recognition on the basis of electroencephalography (EEG) signals has received a significant amount of attention in the areas of cognitive science and human –computer interaction (HCI). However, most existing studies either focus on one-dimensional EEG data, ignoring the relationship between channels, or only extract time–frequency features while not involving spatial features. Approach. We develop spatial–temporal features-based EEG emotion recog nition using a graph convolution network (GCN) and long short-term memory (LSTM), named ERGL. First, the one-dimensional EEG vector is converted into a tw...
Source: Physiological Measurement - June 7, 2023 Category: Physiology Authors: Fa Zheng, Bin Hu, Xiangwei Zheng and Yuang Zhang Source Type: research
