Cerebral asymmetry representation learning-based deep subdomain adaptation network for electroencephalogram-based emotion recognition
Objective. Extracting discriminative spatial information from multiple electrodes is a crucial and challenging problem for electroencephalogram (EEG)-based emotion recognition. Additionally, the domain shift caused by the individual differences degrades the performance of cross-subject EEG classification. Approach. To deal with the above problems, we propose the cerebral asymmetry representation learning-based deep subdomain adaptation network (CARL-DSAN) to enhance cross-subject EEG-based emotion recognition. Specifically, the CARL module is inspired by the neuroscience findings that asymmetrical activations of the left a...
Source: Physiological Measurement - March 26, 2024 Category: Physiology Authors: Zhe Wang, Yongxiong Wang, Xin Wan and Yiheng Tang Source Type: research

Maximum a posteriori detection of heartbeats from a chest-worn accelerometer
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 aposterior...
Source: Physiological Measurement - March 21, 2024 Category: Physiology Authors: Fons Schipper, Ruud J G van Sloun, Angela Grassi, Jan Brouwer, Fokke van Meulen, Sebastiaan Overeem and Pedro Fonseca Source Type: research

Validation of three-dimensional thoracic electrical impedance tomography of horses during normal and increased tidal volumes
Objective. Data from two-plane electrical impedance tomography (EIT) can be reconstructed into various slices of functional lung images, allowing for more complete visualisation and assessment of lung physiology in health and disease. The aim of this study was to confirm the ability of 3D EIT to visualise normal lung anatomy and physiology at rest and during increased ventilation (represented by rebreathing). Approach. Two-plane EIT data, using two electrode planes 20 cm apart, were collected in 20 standing sedate horses at baseline (resting) conditions, and during rebreathing. EIT data were reconstructed into 3D EIT where...
Source: Physiological Measurement - March 21, 2024 Category: Physiology Authors: David P Byrne, Nicole Studer, Cristy Secombe, Alexander Cieslewicz, Giselle Hosgood, Anthea Raisis, Andy Adler and Martina Mosing Source Type: research

Algorithmic detection of sleep-disordered breathing using respiratory signals: a systematic review
Conclusions. Multiple detection algorithms have been widely applied for SDB detection, and their accuracy is c losely related to factors such as signal source, signal processing, feature selection, and model selection. (Source: Physiological Measurement)
Source: Physiological Measurement - March 21, 2024 Category: Physiology Authors: Liqing Yang, Zhimei Ding, Jiangjie Zhou, Siyuan Zhang, Qi Wang, Kaige Zheng, Xing Wang and Lin Chen Source Type: research

Remote photoplethysmography based on reflected light angle estimation
Objective. In previous studies, the factors affecting the accuracy of imaging photoplethysmography (iPPG) heart rate (HR) measurement have been focused on the light intensity, facial reflection angle, and motion artifacts. However, the factor of specularly reflected light has not been studied in detail. We explored the effect of specularly reflected light on the accuracy of HR estimation and proposed an estimation method for the direction of specularly radiated light. Approach. To study the HR measurement accuracy influenced by specularly reflected light, we control the component of specularly reflected light by controllin...
Source: Physiological Measurement - March 20, 2024 Category: Physiology Authors: Xuanhe Fan, Fangwu Liu, Jinjin Zhang, Tong Gao, Ziyang Fan, Zhijie Huang, Wei Xue and JingJing Zhang Source Type: research

Quantitative assessment of carotid ultrasound diameter measurements in the operating room: a comparable analysis of long-axis versus rotated and tilted orientation
This study aimed to quantitatively assess common carotid diameter estimates obtained in a clinical setting from an RT view and compare those to corresponding estimates obtained using other views. Approach. Carotid US measurements were performed in 30 adult cardiac-surgery patients (26 males, 4 females) with short-axis (SA), LA, and RT probe orientations, the first being used as a reference for measuring the true vessel diameter. Per 30 s acquisition, the median and spread in diameter values were computed, the latter representing a measure of robustness, and were statistically compared between views. Main results. The media...
Source: Physiological Measurement - March 20, 2024 Category: Physiology Authors: Esm ée C de Boer, Catarina Dinis Fernandes, Danihel van Neerven, Christoph Pennings, Rohan Joshi, Sabina Manzari, Sergei Shulepov, Luuk van Knippenberg, John van Rooij, R Arthur Bouwman and Massimo Mischi Source Type: research

SwinUNet: a multiscale feature learning approach to cardiovascular magnetic resonance parametric mapping for myocardial tissue characterization
This study aims to accelerate CMR parametric mapping with deep learning. Approach. A deep-learning model, SwinUNet, was developed to accelerate T1/T2 mapping. SwinUNet used a convolutional UNet and a Swin transformer to form a hierarchical 3D computation structure, allowing for analyzing CMR images spatially and temporally with multiscale feature learning. A comparative study was conducted between SwinUNet and an existing deep-learning model, MyoMapNet, which only used temporal analysis for parametric mapping. The T1/T2 mapping performance was evaluated globally using mean absolute error (MAE) and structural similarity ind...
Source: Physiological Measurement - March 20, 2024 Category: Physiology Authors: Yifan Qi, Fusheng Wang, Jun Kong, J Jane Cao and Yu Y Li Source Type: research

Increasing accuracy of pulse arrival time estimation in low frequency recordings
Objective. Wearable devices that measure vital signals using photoplethysmography are becoming more commonplace. To reduce battery consumption, computational complexity, memory footprint or transmission bandwidth, companies of commercial wearable technologies are often looking to minimize the sampling frequency of the measured vital signals. One such vital signal of interest is the pulse arrival time (PAT), which is an indicator of blood pressure. To leverage this non-invasive and non-intrusive measurement data for use in clinical decision making, the accuracy of obtained PAT-parameters needs to increase in lower sampling ...
Source: Physiological Measurement - March 12, 2024 Category: Physiology Authors: Roel J H Montree, Elisabetta Peri, Reinder Haakma, Lukas R C Dekker and Rik Vullings Source Type: research

Quantifying the accuracy of inter-beat intervals acquired from consumer-grade photoplethysmography wristbands using an electrocardiogram-aided information-based similarity approach
In this study, 30 healthy participants concurrently wore two wristbands (E4 and Honor 5) and a gold-standard electrocardiogram (ECG) device under four conditions: resting, deep breathing with a frequency of 0.17 Hz and 0.1 Hz, and mental stress tasks. To quantitatively validate the accuracy of IBI acquired from PPG wristbands, this study proposed to apply an information-based similarity (IBS) approach to quantify the pattern similarity of the underlying dynamical temporal structures embedded in IBI time series simultaneously recorded using PPG wristbands and the ECG system. The occurrence frequency of basic patterns and th...
Source: Physiological Measurement - March 11, 2024 Category: Physiology Authors: Xingran Cui, Jing Wang, Shan Xue, Zeguang Qin and Chung-Kang Peng Source Type: research

SST: a snore shifted-window transformer method for potential obstructive sleep apnea patient diagnosis
The objective of this study was to develop a noncontact sleep audio signal-based method for diagnosing potential OSA patients, aiming to provide a more convenient diagnostic approach compared to the traditional polysomnography (PSG) testing. Approach. The study employed a shifted window transformer model to detect snoring audio signals from whole-night sleep audio. First, a snoring detection model was trained on large-scale audio datasets. Subsequently, the deep feature statistical metrics of the detected snore audio were used to train a random forest classifier for OSA patient diagnosis. Main results. Using a self-collect...
Source: Physiological Measurement - March 11, 2024 Category: Physiology Authors: Jing Luo, Yinuo Zhao, Haiqin Liu, Yitong Zhang, Zhenghao Shi, Rui Li, Xinhong Hei and Xiaorong Ren Source Type: research

A systematic review on automatic identification of insomnia
Conclusion. Based on our review of the studies featured in this paper, we have identified a notable research gap in the current methods for identifying insomnia and opportunities for future advancements in the automation of insomnia detection. While the current techniques have shown promising results, there is still room for improvement in terms of accuracy and reliability. Future developments in technology and machine learning algorithms could help address these limitations and enable more effective and efficient identification of insomnia. (Source: Physiological Measurement)
Source: Physiological Measurement - March 5, 2024 Category: Physiology Authors: Manisha Ingle, Manish Sharma, Kamlesh Kumar, Prince Kumar, Ankit Bhurane, Heather Elphick, Deepak Joshi and U Rajendra Acharya Source Type: research

An interpretable shapelets-based method for myocardial infarction detection using dynamic learning and deep learning
Objective. Myocardial infarction (MI) is a prevalent cardiovascular disease that contributes to global mortality rates. Timely diagnosis and treatment of MI are crucial in reducing its fatality rate. Currently, electrocardiography (ECG) serves as the primary tool for clinical diagnosis. However, detecting MI accurately through ECG remains challenging due to the complex and subtle pathological ECG changes it causes. To enhance the accuracy of ECG in detecting MI, a more thorough exploration of ECG signals is necessary to extract significant features. Approach. In this paper, we propose an interpretable shapelet-based approa...
Source: Physiological Measurement - March 1, 2024 Category: Physiology Authors: Jierui Qu, Qinghua Sun, Weiming Wu, Fukai Zhang, Chunmiao Liang, Yuguo Chen and Cong Wang Source Type: research

Rapid patient-specific FEM meshes from 3D smart-phone based scans
The objective of this study was to describe and evaluate a smart-phone based method to rapidly generate subject-specific finite element method (FEM) meshes. More accurate FEM meshes should lead to more accurate thoracic electrical impedance tomography (EIT) images. Approach. The method was evaluated on an iPhone ® that utilized an app called Heges, to obtain 3D scans (colored, surface triangulations), a custom belt, and custom open-source software developed to produce the subject-specific meshes. The approach was quantitatively validated via mannequin and volunteer tests using an infrared tracker as the go ld standard, an...
Source: Physiological Measurement - February 28, 2024 Category: Physiology Authors: Ethan K Murphy, Joel Smith, Michael A Kokko, Seward B Rutkove and Ryan J Halter Source Type: research

Detecting central apneas using multichannel signals in premature infants
Objective. Monitoring of apnea of prematurity, performed in neonatal intensive care units by detecting central apneas (CAs) in the respiratory traces, is characterized by a high number of false alarms. A two-step approach consisting of a threshold-based apneic event detection algorithm followed by a machine learning model was recently presented in literature aiming to improve CA detection. However, since this is characterized by high complexity and low precision, we developed a new direct approach that only consists of a detection model based on machine learning directly working with multichannel signals. Approach. The dat...
Source: Physiological Measurement - February 28, 2024 Category: Physiology Authors: Gabriele Varisco, Zheng Peng, Deedee Kommers, Eduardus J E Cottaar, Peter Andriessen, Xi Long and Carola van Pul Source Type: research

Blood flow restriction pressure for narrow cuffs (5 cm) cannot be estimated with precision
Blood flow restriction pressures are set relative to the lowest pressure needed to occlude blood flow with that specific cuff. Due to pressure limitations of some devices, it is often not possible to occlude blood flow in all subjects and apply a known relative pressure in the lower body with a 5 cm wide cuff. Objective. To use a device capable of generating high pressures (up to 907 mmHg) to create and validate an estimation equation for the 5 cm cuff in the lower body using a 12 cm cuff. Approach. 170 participants had their arterial occlusion pressure (AOP) with a 5 cm and 12 cm cuff and their thigh circumference measure...
Source: Physiological Measurement - February 26, 2024 Category: Physiology Authors: Robert W Spitz, Yujiro Yamada, Vickie Wong, Ryo Kataoka, William B Hammert, Jun Seob Song, Anna Kang, Aldo Seffrin and Jeremy P Loenneke Source Type: research