Physiological Measurement

Sleep staging based on full polysomnography is the gold standard in the diagnosis of many sleep disorders. It is however costly, complex, and obtrusive due to the use of multiple electrodes. Automatic sleep staging based on single-channel electro-oculography (EOG) is a promising alternative, requiring fewer electrodes which could be self-applied below the hairline. EOG sleep staging algorithms are however yet to be validated in clinical populations with sleep disorders.
Approach. We utilized the SOMNIA dataset, comprising 774 recordings from subjects with various sleep disorders, including insomnia, sleep-disordered breathing, hypersomnolence, circadian rhythm disorders, parasomnias, and movement disorders...


Bioimpedance spectroscopy (BIS) is a popular technique for the assessment of body composition in children and adults but has not found extensive use in babies and infants. This due primarily to technical difficulties of measurement in these groups. Although improvements in data modelling have, in part, mitigated this issue, the problem continues to yield unacceptably high rates of poor quality data. This study investigated an alternative data modelling procedure obviating issues associated with BIS measurements in babies and infants...

UNLABELLED: Monitoring changes in human HRV (Heart Rate Variability) holds significant importance for protecting life and health.. Studies have shown that Imaging Photoplethysmography (IPPG) based on ordinary color cameras can detect the color change of the skin pixel caused by cardiopulmonary system. Most researchers employed deep learning IPPG algorithms to extract the Blood Volume Pulse (BVP) signal, analyzing it predominantly through the Heart Rate (HR). However, this approach often overlooks the inherent intricate time-frequency domain characteristics in the BVP signal, which cannot be comprehensively deduced solely from HR...

OBJECTIVE: Significant aortic regurgitation is a common complication following left ventricular assist device (LVAD) intervention, and existing studies have not attempted to monitor regurgitation signals and undertake preventive measures during full support. Regurgitation is an adverse event that can lead to inadequate left ventricular unloading, insufficient peripheral perfusion, and repeated episodes of heart failure. Moreover, regurgitation occurring during full support due to pump position displacement cannot be directly controlled through control algorithms...

OBJECTIVE: In cardiovascular magnetic resonance (MR) imaging, synchronization of image acquisition with heart motion (called gating) is performed by detecting R-peaks in electrocardiogram (ECG) signals. Effective gating is challenging with 3T and 7T scanners, due to severe distortion of ECG signals caused by magnetohydrodynamic effects associated with intense magnetic fields. This work proposes an efficient retrospective gating strategy that requires no prior training outside the scanner and investigates the optimal number of leads in the ECG acquisition set...

OBJECTIVE: Making up one of the largest shares of diagnosed cancers worldwide, skin cancer is also one of the most treatable. However, this is contingent upon early diagnosis and correct skin cancer-type differentiation. Currently, methods for early detection that are accurate, rapid, and non-invasive are limited. However, literature demonstrating the impedance differences between benign and malignant skin cancers, as well as between different types of skin cancer, show that methods based on impedance differentiation may be promising...

This study aims to automate the segmentation of retinal arterioles and venules (A/V) from digital fundus images (DFI), as changes in the spatial distribution of retinal microvasculature are indicative of cardiovascular diseases, positioning the eyes as windows to cardiovascular health.

Approach: We utilized active learning to create a new DFI dataset with 240 crowd-sourced manual A/V segmentations performed by 15 medical students and reviewed by an ophthalmologist. We then developed LUNet, a novel deep learning architecture optimized for high-resolution A/V segmentation...

OBJECTIVE: 
Myocardial infarction (MI) is a serious cardiovascular disease that can cause irreversible damage to the heart, making early identification and treatment crucial. However, automatic MI detection and localization from an electrocardiogram (ECG) remain challenging. In this study, we propose two models, MFB-SENET and MFB-DMIL, for MI detection and localization, respectively. APPROACH: The MFB-SENET model is designed to detect MI, while the MFB-DMIL model is designed to localize MI...

Diagnosing chronic obstructive pulmonary disease (COPD) using Impulse Oscillometry (IOS) is challenging due to the high level of clinical expertise it demands from doctors , which limits the clinical application of IOS in screening. The primary aim of this study is to develop a COPD diagnostic model based on machine learning algorithms using IOS test results. 
Approach:Feature selection was conducted to identify the optimal subset of features from the original feature set, which significantly enhanced the classifier's performance...

The respiratory rate (RR) is considered one of the most informative vital signals. A well-validated standard for RR measurement in mechanically ventilated patient is capnography; a noninvasive technique for expiratory CO2 measurements. Reliable RR measurements in spontaneously breathing patients remains a challenge as continuous mainstream capnography measurements are not available. This study aimed to assess the accuracy of RR measurement using electrical impedance tomography (EIT) in healthy volunteers and intensive care unit (ICU) patients on mechanical ventilation and spontaneously breathing post-extubation...

The continuous delivery of oxygen is critical to sustain brain function, and therefore, measuring brain oxygen consumption can provide vital physiological insight. In this work, we examine the impact of calibration and CBF measurements on the computation of the relative changes in the cerebral metabolic rate of oxygen consumption (rCMRO2) from hemoglobin-sensitive intrinsic optical imaging data. Using these data, we calculate rCMRO2, and calibrate the model using an isometabolic stimulus.

Approach...


In this study, we test the hypothesis that if, as demonstrated in a previous study, brachial arteries exhibit hysteresis as the occluding cuff is deflated and fail to open until cuff pressure (CP) is well below true intra-arterial blood pressure (IAPB), estimating systolic (SBP) and diastolic blood pressure (DBP) from the presence of Korotkoff sounds as CP increases may eliminate these errors and give more accurate estimates of SBP and DBP relative to IABP readings. 
Approach. In 62 subjects of varying ages (45...

In this paper, we present a novel data-driven approach for solving ill-posed inverse problems, such as Electrical Impedance Tomography (EIT). Our approach introduces a new layer architecture composed of three paths: spatial, spectral, and truncated spectral paths. The spatial path processes information locally, while the spectral and truncated spectral paths provide the network with a global receptive field. Such architecture helps eliminate the ill-posedness and nonlinearity of the inverse problem. The three paths are interconnected, allowing for information exchange on different receptive fields with different learning abilities...

UNLABELLED: Increasing interest in measuring key components of the 24-Hour Activity Cycle (24-HAC) [Sleep, Sedentary Behavior (SED), Light Physical Activity (LPA), and Moderate to Vigorous Physical Activity (MVPA)] has led to a need for better methods. Single wrist-worn accelerometers and different self-report instruments can assess the 24-HAC but may not accurately classify time spent in the different components or be subject to recall errors. OBJECTIVE: To overcome these limitations, the current study harmonized output from multiple complimentary research grade accelerometers and assessed the feasibility and logistical challenges of this approach...

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with significant health ramifications, including an elevated susceptibility to ischemic stroke, heart disease, and heightened mortality. Photoplethysmography (PPG) has emerged as a promising technology for continuous AF monitoring for its cost-effectiveness and widespread integration into wearable devices. Our team previously conducted an exhaustive review on PPG-based AF detection before June 2019. However, since then, more advanced technologies have emerged in this field...

OBJECTIVE: Surface mechanomyography (sMMG) can measure oscillations of the activated muscle fibers in three axes (i.e., X-, Y-, and Z-axes) and has been used to describe motor unit activation patterns (X-axis). The application of blood flow restriction (BFR) is common in exercise studies, but the cuff may restrict muscle fiber oscillations. Therefore, the purpose of this investigation was to examine the acute effects of submaximal, fatiguing exercise with and without BFR on sMMG amplitude in the X-, Y-, and Z-axes among female participants...


This study aims to explore the possibility of using electrical impedance tomography (EIT) to assess PLB performance of patients with COPD.
Methods:
32 patients with COPD were assigned equally to either the conventional group or the EIT guided group. All patients were taught to perform PLB by a physiotherapist without EIT in the conventional group or with EIT in the EIT guided group for 10 min. The ventilation of all patients in the final test were continuously monitored using EIT and the PLB performances were rated by another physiotherapist before and after reviewing EIT...

Photoplethysmography is a non-invasive optical technique that measures changes in blood volume within tissues. It is commonly and being increasingly used for a variety of research and clinical applications to assess vascular dynamics and physiological parameters. Yet, contrary to heart rate variability measures, a field which has seen the development of stable standards and advanced toolboxes and software, no such standards and limited open tools exist for continuous photoplethysmogram (PPG) analysis. Consequently, the primary objective of this research was to identify, standardize, implement and validate key digital PPG biomarkers...

Efficient non-contact heart rate detection has received much attention in the field of health testing. In previous studies on factors affecting the accuracy of remote photoplethysmography
(rPPG) detection, light intensity, facial reflection angle, and motion artifacts have been investigated, but interference from specularly reflected light has not been studied. In this paper, a total of 84 videos were first acquired from four different angles and used to study the effect of specularly reflected light on the accuracy of heart rate estimation...

Objective - Unobtrusive long-term monitoring of cardiac parameters is important in a wide variety of clinical applications, such as the assesment of acute-illness severity and unobtrusive sleep monitoring. Here we determined the accuracy and robustness of heartbeat detection by an accelerometer worn on the chest.

Approach - We performed overnight recordings in 147 individuals (69 female, 78 male) referred to two sleep centers. Two methods for heartbeat detection in the acceleration signal were compared: one previously described approach, based on local periodicity, and a novel extended method incorporating maximum a-posterior estimation and a Markov decision process to approach an optimal solution...