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Rapid patient-specific FEM meshes from 3D smart-phone based scans Physiol. Meas. (IF 3.2) Pub Date : 2024-02-28 Ethan K Murphy, Joel Smith, Michael A Kokko, Seward B Rutkove, Ryan J Halter
Objective. 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)
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Detecting central apneas using multichannel signals in premature infants Physiol. Meas. (IF 3.2) Pub Date : 2024-02-28 Gabriele Varisco, Zheng Peng, Deedee Kommers, Eduardus J E Cottaar, Peter Andriessen, Xi Long, Carola van Pul
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
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Blood flow restriction pressure for narrow cuffs (5 cm) cannot be estimated with precision Physiol. Meas. (IF 3.2) Pub Date : 2024-02-26 Robert W Spitz, Yujiro Yamada, Vickie Wong, Ryo Kataoka, William B Hammert, Jun Seob Song, Anna Kang, Aldo Seffrin, Jeremy P Loenneke
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
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Sampling rate requirement for accurate calculation of heart rate and its variability based on the electrocardiogram Physiol. Meas. (IF 3.2) Pub Date : 2024-02-21 Yuanyuan Zhou, Bryndan Lindsey, Samantha Snyder, Elizabeth Bell, Lucy Reider, Michael Vignos, Eyal Bar-Kochba, Azin Mousavi, Jesse Parreira, Casey Hanley, Jae Kun Shim, Jin-Oh Hahn
Objective. To develop analytical formulas which can serve as quantitative guidelines for the selection of the sampling rate for the electrocardiogram (ECG) required to calculate heart rate (HR) and heart rate variability (HRV) with a desired level of accuracy. Approach. We developed analytical formulas which relate the ECG sampling rate to conservative bounds on HR and HRV errors: (i) one relating
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Analysis of electrode arrangements for brain stroke diagnosis via electrical impedance tomography through numerical computational models Physiol. Meas. (IF 3.2) Pub Date : 2024-02-19 Hannah Lee, Jared Culpepper, Emily Porter
Objective. Rapid stroke-type classification is crucial for improved prognosis. However, current methods for classification are time-consuming, require expensive equipment, and can only be used in the hospital. One method that has demonstrated promise in a rapid, low-cost, non-invasive approach to stroke diagnosis is electrical impedance tomography (EIT). While EIT for stroke diagnosis has been the
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Utilization of bioelectrical impedance vector analysis (BIVA) in children and adolescents without diagnosed diseases: a systematic review Physiol. Meas. (IF 3.2) Pub Date : 2024-02-19 Leandro Narciso Santiago, Priscila Custódio Martins, Diego Augusto Santos Silva
Introduction. Bioelectrical impedance vector analysis (BIVA) emerges as a technique that utilizes raw parameters of bioelectrical impedance analysis and assumes the use of a reference population for information analysis. Objective. To summarize the reference values, main studies objectives, approaches, pre-test recommendations and technical characteristics of the devices employed in studies utilizing
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Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system Physiol. Meas. (IF 3.2) Pub Date : 2024-02-15 Lin Yang, Zhijun Gao, Chunchen Wang, Hang Wang, Jing Dai, Yang Liu, Yilong Qin, Meng Dai, Xinsheng Cao, Zhanqi Zhao
Objective. Wearable electrical impedance tomography (EIT) can be used to monitor regional lung ventilation and perfusion at the bedside. Due to its special system architecture, the amplitude of the injected current is usually limited compared to stationary EIT system. This study aims to evaluate the performance of current injection patterns with various low-amplitude currents in healthy volunteers
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The influence of cardiac arrhythmias on the detection of heartbeats in the photoplethysmogram: benchmarking open-source algorithms Physiol. Meas. (IF 3.2) Pub Date : 2024-02-14 Loïc Jeanningros, Mathieu Le Bloa, Cheryl Teres, Claudia Herrera Siklody, Alessandra Porretta, Patrizio Pascale, Adrian Luca, Jorge Solana Muñoz, Giulia Domenichini, Théo A Meister, Rodrigo Soria Maldonado, Hildegard Tanner, Jean-Marc Vesin, Jean-Philippe Thiran, Mathieu Lemay, Emrush Rexhaj, Etienne Pruvot, Fabian Braun
Objective. Cardiac arrhythmias are a leading cause of mortality worldwide. Wearable devices based on photoplethysmography give the opportunity to screen large populations, hence allowing for an earlier detection of pathological rhythms that might reduce the risks of complications and medical costs. While most of beat detection algorithms have been evaluated on normal sinus rhythm or atrial fibrillation
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ECG data enhancement method using generate adversarial networks based on Bi-LSTM and CBAM Physiol. Meas. (IF 3.2) Pub Date : 2024-02-12 Feiyan Zhou, Jiajia Li
Objective. The classification performance of electrocardiogram (ECG) classification algorithms is easily affected by data imbalance, which often leads to poor model prediction performance for a few classes and a consequent decrease in the overall performance of the model. Approach. To address this problem, this paper proposed an ECG data augmentation method based on a generative adversarial network
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Conventional and deep learning methods in heart rate estimation from RGB face videos Physiol. Meas. (IF 3.2) Pub Date : 2024-02-09 Abdulkader Helwan, Danielle Azar, Mohamad Khaleel Sallam Ma’aitah
Contactless vital signs monitoring is a fast-advancing scientific field that aims to employ monitoring methods that do not necessitate the use of leads or physical attachments to the patient in order to overcome the shortcomings and limits of traditional monitoring systems. Several traditional methods have been applied to extract the heart rate (HR) signal from the face. Moreover, machine learning
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Sleep apnea detection from single-lead electrocardiogram signals using effective deep-shallow fusion network Physiol. Meas. (IF 3.2) Pub Date : 2024-02-09 Pan Li, Wenjun Ma, Huijun Yue, Wenbin Lei, Xiaomao Fan, Ye Li
Objective. Explore a network architecture that can efficiently perform single-lead electrocardiogram (ECG) sleep apnea (SA) detection by utilizing the beneficial information of extended ECG segments and reducing the impact of their noisy information. Approach. We propose an effective deep-shallow fusion network (EDSFnet). The deeper residual network is used to extract high-level features with stronger
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Assessment of bioimpedance spectroscopy devices: a comparative study and error analysis of gold-plated copper electrodes Physiol. Meas. (IF 3.2) Pub Date : 2024-02-05 Sebastian Mussnig, Simon Krenn, Manfred Hecking, Peter Wabel
Objective. Bioimpedance spectroscopy (BIS) is a non-invasive diagnostic tool to derive fluid volume compartments from frequency dependent voltage drops in alternating currents by extrapolating to the extracellular resistance (R 0) and intracellular resistance (R i). Here we tested whether a novel BIS device with reusable and adhesive single-use electrodes produces results which are (in various body
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Regional ventilation distribution before and after laparoscopic lung parenchymal resection Physiol. Meas. (IF 3.2) Pub Date : 2024-01-31 Zhibin Xiao, Lin Yang, Meng Dai, Wenjun Lu, Feng Liu, Inéz Frerichs, Changjun Gao, Xude Sun, Zhanqi Zhao
Objective. The aim of the present study was to evaluate the influence of one-sided pulmonary nodule and tumour on ventilation distribution pre- and post- partial lung resection. Approach. A total of 40 consecutive patients scheduled for laparoscopic lung parenchymal resection were included. Ventilation distribution was measured with electrical impedance tomography (EIT) in supine and surgery lateral
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Investigating the impact of smoking habits through photoplethysmography analysis Physiol. Meas. (IF 3.2) Pub Date : 2024-01-22 Qasem Qananwah, Ateka Khader, Munder Al-Hashem, Ahmad Mumani, Ahmad Dagamseh
Smoking is widely recognized as a significant risk factor in the progression of arterial stiffness and cardiovascular diseases. Valuable information related to cardiac arrhythmias and heart function can be obtained by analyzing biosignals such as the electrocardiogram (ECG) and the photoplethysmogram (PPG). The PPG signal is a non-invasive optical technique that can be used to evaluate the changes
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The hemodynamic cardiac profiler volume-time curves and related parameters: an MRI validation study Physiol. Meas. (IF 3.2) Pub Date : 2024-01-10 Maurits K Konings, Manuella Al Sharkawy, Sjoerd M Verwijs, Adrianus J Bakermans, Martijn Visscher, Charles L Hollenkamp, Denise P Veelo, Harald T Jørstad
Background. The hemodynamic cardiac profiler (HCP) is a new, non-invasive, operator-independent screening tool that uses six independent electrode pairs on the frontal thoracic skin, and a low-intensity, patient-safe, high-frequency applied alternating current to measure ventricular volume dynamics during the cardiac cycle for producing ventricular volume-time curves (VTCs). Objective. To validate
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Distribution of regional lung function in upright healthy subjects determined by electrical impedance tomography in two chest examination planes Physiol. Meas. (IF 3.2) Pub Date : 2024-01-10 I Frerichs, B Vogt, K Deuss, V Hennig, D Schädler, C Händel
Objective. The variation in pulmonary gas content induced by ventilation is not uniformly distributed in the lungs. The aim of our study was to characterize the differences in spatial distribution of ventilation in two transverse sections of the chest using electrical impedance tomography (EIT). Approach. Twenty adult never-smokers, 10 women and 10 men (mean age ± SD, 31 ± 9 years), were examined in
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Esophageal balloon catheter system identification to improve respiratory effort time features and amplitude determination Physiol. Meas. (IF 3.2) Pub Date : 2024-01-10 Yu Hao Wang Xia, Marcus Henrique Victor Jr, Caio César Araújo Morais, Eduardo Leite Vieira Costa, Marcelo Britto Passos Amato
Objective. Understanding a patient’s respiratory effort and mechanics is essential for the provision of individualized care during mechanical ventilation. However, measurement of transpulmonary pressure (the difference between airway and pleural pressures) is not easily performed in practice. While airway pressures are available on most mechanical ventilators, pleural pressures are measured indirectly
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A comparative analysis of mathematical methods for detecting lactate thresholds using muscle oxygenation data during a graded cycling test Physiol. Meas. (IF 3.2) Pub Date : 2023-12-29 Carlos Sendra-Pérez, Alberto Encarnación-Martínez, Fran Oficial-Casado, Rosario Salvador-Palmer, Jose I Priego-Quesada
Objective. Threshold determination for improving training and sports performance is important for researchers and trainers, who currently use different methods for determining lactate, ventilatory or muscle oxygenation (SmO2) thresholds. Our study aimed to compare the identification of the intensity at the first and second thresholds using lactate and SmO2 data by different mathematical methods in
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Effective DBS treatment improves neural information transmission of patients with disorders of consciousness: an fNIRS study Physiol. Meas. (IF 3.2) Pub Date : 2023-12-29 Zhilin Shu, Jingchao Wu, Jiewei Lu, Haitao Li, Jinrui Liu, Jianeng Lin, Siquan Liang, Jialing Wu, Jianda Han, Ningbo Yu
Objective. Deep brain stimulation (DBS) is a potential treatment that promotes the recovery of patients with disorders of consciousness (DOC). This study quantified the changes in consciousness and the neuromodulation effect of DBS on patients with DOC. Approach. Eleven patients were recruited for this study which consists of three conditions: ‘Pre’ (two days before DBS surgery), ‘Post-On’ (one month
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MLP-RL-CRD: diagnosis of cardiovascular risk in athletes using a reinforcement learning-based multilayer perceptron Physiol. Meas. (IF 3.2) Pub Date : 2023-12-29 Arsam Bostani, Marzieh Mirzaeibonehkhater, Hamidreza Najafi, Mohammad Mehrtash, Roohallah Alizadehsani, Ru-San Tan, U Rajendra Acharya
Objective. Pre-participation medical screening of athletes is necessary to pinpoint individuals susceptible to cardiovascular events. Approach. The article presents a reinforcement learning (RL)-based multilayer perceptron, termed MLP-RL-CRD, designed to detect cardiovascular risk among athletes. The model underwent training using a publicized dataset that included the anthropological measurements
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In vivo characterization of the optical and hemodynamic properties of the human sternocleidomastoid muscle through ultrasound-guided hybrid near-infrared spectroscopies Physiol. Meas. (IF 3.2) Pub Date : 2023-12-26 Lorenzo Cortese, Pablo Fernández Esteberena, Marta Zanoletti, Giuseppe Lo Presti, Gloria Aranda Velazquez, Sabina Ruiz Janer, Mauro Buttafava, Marco Renna, Laura Di Sieno, Alberto Tosi, Alberto Dalla Mora, Stanislaw Wojtkiewicz, Hamid Dehghani, Sixte de Fraguier, An Nguyen-Dinh, Bogdan Rosinski, Udo M Weigel, Jaume Mesquida, Mattia Squarcia, Felicia A Hanzu, Davide Contini, Mireia Mora Porta, Turgut
Objective. In this paper, we present a detailed in vivo characterization of the optical and hemodynamic properties of the human sternocleidomastoid muscle (SCM), obtained through ultrasound-guided near-infrared time-domain and diffuse correlation spectroscopies. Approach. A total of sixty-five subjects (forty-nine females, sixteen males) among healthy volunteers and thyroid nodule patients have been
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Machine learning to detect, stage and classify diseases and their symptoms based on inertial sensor data: a mapping review Physiol. Meas. (IF 3.2) Pub Date : 2023-12-26 Daniele Bibbo, Cristiano De Marchis, Maurizio Schmid, Simone Ranaldi
This article presents a systematic review aimed at mapping the literature published in the last decade on the use of machine learning (ML) for clinical decision-making through wearable inertial sensors. The review aims to analyze the trends, perspectives, strengths, and limitations of current literature in integrating ML and inertial measurements for clinical applications. The review process involved
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Mechanocardiography detects improvement of systolic function caused by resynchronization pacing Physiol. Meas. (IF 3.2) Pub Date : 2023-12-20 Fadime Tokmak, Tero Koivisto, Olli Lahdenoja, Tuija Vasankari, Samuli Jaakkola, K E Juhani Airaksinen
Objective. Cardiac resynchronization therapy (CRT) is commonly used to manage heart failure with dyssynchronous ventricular contraction. CRT pacing resynchronizes the ventricular contraction, while AAI (single-chamber atrial) pacing does not affect the dyssynchronous function. This study compared waveform characteristics during CRT and AAI pacing at similar pacing rates using seismocardiogram (SCG)
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Domain independent post-processing with graph U-nets: applications to electrical impedance tomographic imaging⋆ ⋆ SH and BH were supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R21EB028064. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Physiol. Meas. (IF 3.2) Pub Date : 2023-12-18 William Herzberg, Andreas Hauptmann, Sarah J Hamilton
Objective. To extend the highly successful U-Net Convolutional Neural Network architecture, which is limited to rectangular pixel/voxel domains, to a graph-based equivalent that works flexibly on irregular meshes; and demonstrate the effectiveness on electrical impedance tomography (EIT). Approach. By interpreting the irregular mesh as a graph, we develop a graph U-Net with new cluster pooling and
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Is muscle localized phase angle an indicator of muscle power and strength in young women? Physiol. Meas. (IF 3.2) Pub Date : 2023-12-18 Núbia Maria Oliveira, Aryanne Hydeko Fukuoka, Catarina Nunes Matias, Gil Guerra-Júnior, Ezequiel Moreira Gonçalves
Objective. This study aimed to investigate the capacity of the bioelectrical muscle localized phase angle (ML-PhA) as an indicator of muscle power and strength compared to whole body PhA (WB-PhA). Approach. This study assessed 30 young women (22.1 ± 3.2 years) for muscle power and strength using the Wingate test and isokinetic dynamometer, respectively. Bioimpedance analysis at 50 kHz was employed
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Cross-subject emotion recognition using hierarchical feature optimization and support vector machine with multi-kernel collaboration Physiol. Meas. (IF 3.2) Pub Date : 2023-12-18 Lizheng Pan, Ziqin Tang, Shunchao Wang, Aiguo Song
Objective. Due to individual differences, it is greatly challenging to realize the multiple types of emotion identification across subjects. Approach. In this research, a hierarchical feature optimization method is proposed in order to represent emotional states effectively based on peripheral physiological signals. Firstly, sparse learning combined with binary search is employed to achieve feature
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Photoplethysmography-based cuffless blood pressure estimation: an image encoding and fusion approach Physiol. Meas. (IF 3.2) Pub Date : 2023-12-15 Yinsong Liu, Junsheng Yu, Hanlin Mou
Objective. Photoplethysmography (PPG) is a promising wearable technology that detects volumetric changes in microcirculation using a light source and a sensor on the skin’s surface. PPG has been shown to be useful for non-invasive blood pressure (BP) measurement. Deep learning-based BP measurements are now gaining popularity. However, almost all methods focus on 1D PPG. We aimed to design an end-to-end
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Physiological sensor data cleaning with autoencoders Physiol. Meas. (IF 3.2) Pub Date : 2023-12-15 Lito Kriara, Mattia Zanon, Florian Lipsmeier, Michael Lindemann
Objective. Physiological sensor data (e.g. photoplethysmograph) is important for remotely monitoring patients’ vital signals, but is often affected by measurement noise. Existing feature-based models for signal cleaning can be limited as they might not capture the full signal characteristics. Approach. In this work we present a deep learning framework for sensor signal cleaning based on dilated convolutions
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SEResUTer: a deep learning approach for accurate ECG signal delineation and atrial fibrillation detection Physiol. Meas. (IF 3.2) Pub Date : 2023-12-15 Xinyue Li, Wenjie Cai, Bolin Xu, Yupeng Jiang, Mengdi Qi, Mingjie Wang
Objective. Accurate detection of electrocardiogram (ECG) waveforms is crucial for computer-aided diagnosis of cardiac abnormalities. This study introduces SEResUTer, an enhanced deep learning model designed for ECG delineation and atrial fibrillation (AF) detection. Approach. Built upon a U-Net architecture, SEResUTer incorporates ResNet modules and Transformer encoders to replace convolution blocks
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Magnetocardiography-based coronary artery disease severity assessment and localization using spatiotemporal features Physiol. Meas. (IF 3.2) Pub Date : 2023-12-11 Xiaole Han, Jiaojiao Pang, Dong Xu, Ruizhe Wang, Fei Xie, Yanfei Yang, Jiguang Sun, Yu Li, Ruochuan Li, Xiaofei Yin, Yansong Xu, Jiaxin Fan, Yiming Dong, Xiaohui Wu, Xiaoyun Yang, Dexin Yu, Dawei Wang, Yang Gao, Min Xiang, Feng Xu, Jinji Sun, Yuguo Chen, Xiaolin Ning
Objective. This study aimed to develop an automatic and accurate method for severity assessment and localization of coronary artery disease (CAD) based on an optically pumped magnetometer magnetocardiography (MCG) system. Approach. We proposed spatiotemporal features based on the MCG one-dimensional signals, including amplitude, correlation, local binary pattern, and shape features. To estimate the
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Improved T-wave detection in electrocardiogram signals based non-stationary wavelet transform and QRS complex cancellation with kurtosis analysis Physiol. Meas. (IF 3.2) Pub Date : 2023-12-06 Neenu Sharma, Ramesh Kumar Sunkaria
Objective. The T-wave in electrocardiogram (ECG) signal has the potential to enumerate various cardiac dysfunctions in the cardiovascular system. The primary objective of this research is to develop an efficient method for detecting T-waves in ECG signals, with potential applications in clinical diagnosis and continuous patient monitoring. Approach. In this work, we propose a novel algorithm for T-wave
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The 2023 wearable photoplethysmography roadmap Physiol. Meas. (IF 3.2) Pub Date : 2023-11-29 Peter H Charlton, John Allen, Raquel Bailón, Stephanie Baker, Joachim A Behar, Fei Chen, Gari D Clifford, David A Clifton, Harry J Davies, Cheng Ding, Xiaorong Ding, Jessilyn Dunn, Mohamed Elgendi, Munia Ferdoushi, Daniel Franklin, Eduardo Gil, Md Farhad Hassan, Jussi Hernesniemi, Xiao Hu, Nan Ji, Yasser Khan, Spyridon Kontaxis, Ilkka Korhonen, Panicos A Kyriacou, Pablo Laguna, Jesús Lázaro, Chungkeun
Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing
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Non-invasive imaging of neural activity with magnetic detection electrical impedance tomography (MDEIT): a modelling study Physiol. Meas. (IF 3.2) Pub Date : 2023-11-29 Kai Mason, Kirill Aristovich, David Holder
Objectives. (1) Develop a computational pipeline for three-dimensional fast neural magnetic detection electrical impedance tomography (MDEIT), (2) determine whether constant current or constant voltage is preferable for MDEIT, (3) perform reconstructions of simulated neural activity in a human head model with realistic noise and compare MDEIT to EIT and (4) perform a two-dimensional study in a saline
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MAG-Res2Net: a novel deep learning network for human activity recognition Physiol. Meas. (IF 3.2) Pub Date : 2023-11-28 Hanyu Liu, Boyang Zhao, Chubo Dai, Boxin Sun, Ang Li, Zhiqiong Wang
Objective. Human activity recognition (HAR) has become increasingly important in healthcare, sports, and fitness domains due to its wide range of applications. However, existing deep learning based HAR methods often overlook the challenges posed by the diversity of human activities and data quality, which can make feature extraction difficult. To address these issues, we propose a new neural network
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Deep learning with fetal ECG recognition Physiol. Meas. (IF 3.2) Pub Date : 2023-11-27 Wei Zhong, Jiahui Luo, Wei Du
Objective. Independent component analysis (ICA) is widely used in the extraction of fetal ECG (FECG). However, the amplitude, order, and positive or negative values of the ICA results are uncertain. The main objective is to present a novel approach to FECG recognition by using a deep learning strategy. Approach. A cross-domain consistent convolutional neural network (CDC-Net) is developed for the task
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Predicting CPAP failure after less invasive surfactant administration (LISA) in preterm infants by machine learning model on vital parameter data: a pilot study Physiol. Meas. (IF 3.2) Pub Date : 2023-11-24 R M J S Kloonen, G Varisco, E de Kort, P Andriessen, H J Niemarkt, C van Pul
Objective. Less invasive surfactant administration (LISA) has been introduced to preterm infants with respiratory distress syndrome on continuous positive airway pressure (CPAP) support in order to avoid intubation and mechanical ventilation. However, after this LISA procedure, a significant part of infants fails CPAP treatment (CPAP-F) and requires intubation in the first 72 h of life, which is associated
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The degree of engagement of cardiac and sympathetic arms of the baroreflex does not depend on the absolute value and sign of arterial pressure variations Physiol. Meas. (IF 3.2) Pub Date : 2023-11-24 Beatrice De Maria, Laura Adelaide Dalla Vecchia, Vlasta Bari, Beatrice Cairo, Francesca Gelpi, Francesca Perego, Anielle Christine Medeiros Takahashi, Juliana Cristina Milan-Mattos, Vinicius Minatel, Patrícia Rehder-Santos, Murray Esler, Elisabeth Lambert, Mathias Baumert, Aparecida Maria Catai, Alberto Porta
Objective. The percentages of cardiac and sympathetic baroreflex patterns detected via baroreflex sequence (SEQ) technique from spontaneous variability of heart period (HP) and systolic arterial pressure (SAP) and of muscle nerve sympathetic activity (MSNA) burst rate and diastolic arterial pressure (DAP) are utilized to assess the level of the baroreflex engagement. The cardiac baroreflex patterns
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ECGPsychNet: an optimized hybrid ensemble model for automatic detection of psychiatric disorders using ECG signals Physiol. Meas. (IF 3.2) Pub Date : 2023-11-21 Smith K Khare, Vikram M Gadre, U Rajendra Acharya
Background. Psychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BD), and depression (DPR) are some of the leading causes of disability and suicide worldwide. The signs and symptoms of SCZ, BD, and DPR vary dynamically and do not have uniform detection strategies. The main causes of delays in the detection of psychiatric disorders are negligence by immediate caregivers, varying symptoms
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Methods and evaluation of physiological measurements with acoustic stimuli—a systematic review Physiol. Meas. (IF 3.2) Pub Date : 2023-11-13 Christian Laufs, Andreas Herweg, Christoph Hoog Antink
Objective. The detection of psychological loads, such as stress reactions, is receiving greater attention and social interest, as stress can have long-term effects on health O’Connor, Thayer and Vedhara (2021 Ann. Rev. Psychol. 72, 663–688). Acoustic stimuli, especially noise, are investigated as triggering factors. The application of physiological measurements in the detection of psychological loads
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Anti-motion imaging photoplethysmography via self-adaptive multi-ROI tracking and selection Physiol. Meas. (IF 3.2) Pub Date : 2023-11-13 Yaran Duan, Chao He, Mei Zhou
Objective. The imaging photoplethysmography (IPPG) technique allows people to measure heart rate (HR) from face videos. However, motion artifacts caused by rigid head movements and nonrigid facial muscular movements are one of the key challenges. Approach. This paper proposes a self-adaptive region of interest (ROI) pre-tracking and signal selection method to resist motion artifacts. Based on robust
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A three-dimensional adaptive rational interpolation algorithm for removing TMS-EEG pulse artifacts Physiol. Meas. (IF 3.2) Pub Date : 2023-11-06 Hui Xiong, Yajun Di, Jinzhen Liu, Yuqing Han, Yu Zheng
Objective. Transcranial magnetic stimulation in combination with electroencephalography (TMS-EEG) has been widely used to study the reactivity and connectivity of brain regions. In order to efficiently and fast solve the pulse artifacts problem caused by TMS electromagnetic pulses, a three-dimensional adaptive rational quadratic Hermite interpolation algorithm is proposed. Approach. Firstly, a three-dimensional
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Validity and reliability of the DANU sports system for walking and running gait assessment Physiol. Meas. (IF 3.2) Pub Date : 2023-11-06 Rachel Mason, Gillian Barry, Hugh Robinson, Ben O’Callaghan, Oisin Lennon, Alan Godfrey, Samuel Stuart
Objective. Gait assessments have traditionally been analysed in laboratory settings, but this may not reflect natural gait. Wearable technology may offer an alternative due to its versatility. The purpose of the study was to establish the validity and reliability of temporal gait outcomes calculated by the DANU sports system, against a 3D motion capture reference system. Approach. Forty-one healthy
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Influence of sex on the reliability of cerebral blood velocity regulation during lower body negative pressure and supine cycling with considerations of the menstrual cycle Physiol. Meas. (IF 3.2) Pub Date : 2023-11-06 Nathan E Johnson, Joel S Burma, Jina Seok, Lauren N Miutz, Jonathan D Smirl
Objective. To evaluate sex differences in the reliability of absolute and relative cerebral blood velocity (CBv) during concurrent supine cycling with lower body negative pressure (LBNP). Approach. A total of 19 participants (11 females; aged 20–33 years) completed five testing sessions, occurring on 7 d intervals. Visit 1 was a maximal-ramp-cycle test to ascertain peak CBv wattage. During visits 2–5
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Multi-channel EEG-based sleep staging using brain functional connectivity and domain adaptation Physiol. Meas. (IF 3.2) Pub Date : 2023-10-31 Wenhao Yuan, Wentao Xiang, Kaiyue Si, Chunfeng Yang, Lina Zhao, Jianqing Li, Chengyu Liu
Objective. Sleep stage recognition has essential clinical value for evaluating human physical/mental condition and diagnosing sleep-related diseases. To conduct a five-class (wake, N1, N2, N3 and rapid eye movement) sleep staging task, twenty subjects with recorded six-channel electroencephalography (EEG) signals from the ISRUC-SLEEP dataset is used. Approach. Unlike the exist methods ignoring the
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An effective hybrid feature selection using entropy weight method for automatic sleep staging Physiol. Meas. (IF 3.2) Pub Date : 2023-10-31 Weibo Wang, Junwen Li, Yu Fang, Yongkang Zheng, Fang You
Objective. Sleep staging is the basis for sleep quality assessment and diagnosis of sleep-related disorders. In response to the inadequacy of traditional manual judgement of sleep stages, using machine learning techniques for automatic sleep staging has become a hot topic. To improve the performance of sleep staging, numerous studies have extracted a large number of sleep-related characteristics. However
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Analysis of intracranial pressure pulse waveform in studies on cerebrospinal compliance: a narrative review Physiol. Meas. (IF 3.2) Pub Date : 2023-10-27 Agnieszka Kazimierska, Romain Manet, Alexandra Vallet, Eric Schmidt, Zofia Czosnyka, Marek Czosnyka, Magdalena Kasprowicz
Continuous monitoring of mean intracranial pressure (ICP) has been an essential part of neurocritical care for more than half a century. Cerebrospinal pressure–volume compensation, i.e. the ability of the cerebrospinal system to buffer changes in volume without substantial increases in ICP, is considered an important factor in preventing adverse effects on the patient’s condition that are associated
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Individualized monitoring of heat illness risk: novel adaptive physiological strain index to assess exercise-heat strain from athletes to fully encapsulated workers Physiol. Meas. (IF 3.2) Pub Date : 2023-10-20 Mark J Buller, Emma Atkinson, Kyla Driver, William J Tharion, Brett R Ely, Samuel N Cheuvront, Nisha Charkoudian
Objective. Exercise-heat strain estimation approaches often involve combinations of body core temperature (Tcore), skin temperature (Tsk) and heart rate (HR). A successful existing measure is the ‘Physiological Strain Index’ (PSI), which combines HR and Tcore values to estimate strain. However, depending on variables such as aerobic fitness and clothing, the equation’s ‘maximal/critical’ Tcore must
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Pulse wave analysis as a tool for the evaluation of resuscitation therapy in septic shock Physiol. Meas. (IF 3.2) Pub Date : 2023-10-13 Riccardo Campitelli, Manuela Ferrario, Fuhong Su, Jacques Creteur, Antoine Herpain, Marta Carrara
Objective. Pulse wave analysis (PWA) can provide insights into cardiovascular biomechanical properties. The use of PWA in critically ill patients, such as septic shock patients, is still limited, but it can provide complementary information on the cardiovascular effects of treatment when compared to standard indices outlined in international guidelines. Previous works have highlighted how sepsis induces
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Uncertainty quantification of the effect of cardiac position variability in the inverse problem of electrocardiographic imaging Physiol. Meas. (IF 3.2) Pub Date : 2023-10-13 Jake A Bergquist, Brian Zenger, Lindsay C Rupp, Anna Busatto, Jess Tate, Dana H Brooks, Akil Narayan, Rob S MacLeod
Objective. Electrocardiographic imaging (ECGI) is a functional imaging modality that consists of two related problems, the forward problem of reconstructing body surface electrical signals given cardiac bioelectric activity, and the inverse problem of reconstructing cardiac bioelectric activity given measured body surface signals. ECGI relies on a model for how the heart generates bioelectric signals
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Evaluation of three approaches used for respiratory measurement in healthy subjects Physiol. Meas. (IF 3.2) Pub Date : 2023-10-13 Xiaojuan Duan, Xin Song, Caidie Yang, Yunchi Li, Liang Wei, Yushun Gong, Yongqin Li
Objective. Respiration is one of the critical vital signs of human health status, and accurate respiratory monitoring has important clinical significance. There is substantial evidence that alterations in key respiratory parameters can be used to determine a patient’s health status, aid in the selection of appropriate treatments, predict potentially serious clinical events and control respiratory activity
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Completing the Cabrera Circle: deriving adaptable leads from ECG limb leads by combining constraints with a correction factor Physiol. Meas. (IF 3.2) Pub Date : 2023-10-13 Henning Dathe, Dagmar Krefting, Nicolai Spicher
Objective. We present a concept for processing 6-lead electrocardiography (ECG) signals which can be applied to various use cases in quantitative electrocardiography. Approach. Our work builds upon the mathematics of the well-known Cabrera sequence which is a re-sorting of the six limb leads (I, II, III, aV R, aV L, aV F) into a clockwise and physiologically-interpretable order. By deriving correction
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HIRA: Heart Rate Interval based Rapid Alert score to characterize autonomic dysfunction among patients with sepsis-related acute respiratory failure (ARF) Physiol. Meas. (IF 3.2) Pub Date : 2023-10-13 Preethi Krishnan, Milad G Rad, Palak Agarwal, Curtis Marshall, Philip Yang, Sivasubramanium V Bhavani, Andre L Holder, Annette Esper, Rishikesan Kamaleswaran
Objective. To examine whether heart rate interval based rapid alert (HIRA) score derived from a combination model of heart rate variability (HRV) and modified early warning score (MEWS) is a surrogate for the detection of acute respiratory failure (ARF) in critically ill sepsis patients. Approach. Retrospective HRV analysis of sepsis patients admitted to Emory healthcare intensive care unit (ICU) was
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Uneven terrain affects metabolic cost and gait in simulated complex lunar surfaces Physiol. Meas. (IF 3.2) Pub Date : 2023-10-06 Kyoung Jae Kim, Alexander Baughman, Patrick Estep, Eric Rivas, Millennia Young, Karina Marshall-Goebel, Andrew Abercromby, Jeffrey Somers
Objective. Upcoming missions of the National Aeronautics and Space Administration (NASA) to the Moon will include extensive human exploration of the lunar surface. Walking will be essential for many exploration tasks, and metabolic cost during ambulation on simulated complex lunar surfaces requires further characterization. In this study, ten healthy subjects (6 male and 4 female) participated in three
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Atrial fibrillation detection with signal decomposition and dilated residual neural network Physiol. Meas. (IF 3.2) Pub Date : 2023-10-05 Yicheng Li, Yong Xia
Objective. Detecting atrial fibrillation (AF) using electrocardiogram (ECG) recordings from wearable devices has been challenging due to factors such as low signal-to-noise ratio and the use of only one lead. The use of deep learning has become a popular approach to tackle this task. However, it has been observed that current methods based on deep neural networks tend to favor raw signals as input
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Characterization of cardiovascular and cerebrovascular controls via spectral causality analysis in patients undergoing surgical aortic valve replacement during a three-month follow-up Physiol. Meas. (IF 3.2) Pub Date : 2023-09-29 Vlasta Bari, Francesca Gelpi, Beatrice Cairo, Martina Anguissola, Sara Pugliese, Beatrice De Maria, Enrico Giuseppe Bertoldo, Valentina Fiolo, Edward Callus, Carlo De Vincentiis, Marianna Volpe, Raffaella Molfetta, Marco Ranucci, Alberto Porta
Objective. Aortic valve stenosis (AVS) induces left ventricular function adaptations and surgical aortic valve replacement (SAVR) restores blood flow profile across aortic valve. Modifications of cardiac hemodynamics induced by AVS and SAVR might alter cardiovascular (CV) and cerebrovascular (CBV) controls. The study aims at characterizing CV and CBV regulations one day before SAVR (PRE), within one
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B3X: a novel efficient algorithm for accurate automated auscultatory blood pressure estimation Physiol. Meas. (IF 3.2) Pub Date : 2023-09-28 Jessica Centracchio, Davide De Caro, Paolo Bifulco, Emilio Andreozzi
Objective. The auscultatory technique is still considered the most accurate method for non-invasive blood pressure (NIBP) measurement, although its reliability depends on operator’s skills. Various methods for automated Korotkoff sounds analysis have been proposed for reliable estimation of systolic (SBP) and diastolic (DBP) blood pressures. To this aim, very complex methodologies have been presented
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Bio-potential noise of dry printed electrodes: physiology versus the skin-electrode impedance Physiol. Meas. (IF 3.2) Pub Date : 2023-09-26 Ana Arché-Núñez, Peter Krebsbach, Bara Levit, Daniel Possti, Aaron Gerston, Thorsten Knoll, Thomas Velten, Chen Bar-Haim, Shani Oz, Shira Klorfeld-Auslender, Gerardo Hernandez-Sosa, Anat Mirelman, Yael Hanein
Objective. To explore noise characteristics and the effect physiological activity has on the link between impedance and noise. Approach. Dry-printed electrodes are emerging as a new and exciting technology for skin electro-physiology. Such electrode arrays offer many advantages including user convenience, quick placement, and high resolution. Here we analyze extensive electro-physiological data recorded
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Threshold distribution of equal states for quantitative amplitude fluctuations Physiol. Meas. (IF 3.2) Pub Date : 2023-09-22 Wenpo Yao, Wenli Yao, Jun Wang
Objective. The distribution of equal states (DES) quantifies amplitude fluctuations in biomedical signals. However, under certain conditions, such as a high resolution of data collection or special signal processing techniques, equal states may be very rare, whereupon the DES fails to measure the amplitude fluctuations. Approach. To address this problem, we develop a novel threshold DES (tDES) that
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Regurgitation during the fully supported condition of the percutaneous left ventricular assist device Physiol. Meas. (IF 3.2) Pub Date : 2023-09-22 Anyun Yin, Biyang Wen, Zijian Cao, Qilian Xie, Ming Dai
Objective. A percutaneous left ventricular assist device (PLVAD) can be used as a bridge to heart transplantation or as a temporary support for end-stage heart failure. Transvalvularly placed PLVADs may result in aortic regurgitation due to unstable pump position during fully supported operation, which may diminish the pumping effect of forward flow and predispose to complications. Therefore, accurate
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Potential limitations of measuring ambulatory activity of part-time wheelchair users: a comparative study of two research grade activity monitors Physiol. Meas. (IF 3.2) Pub Date : 2023-09-21 Wilshaw Stevens, Fernanda Harlett, Robert L Wimberly, Kirsten Tulchin-Francis
Objective. Research grade activity monitors such as the StepWatch Activity Monitor (SAM) and Actigraph have been shown to be highly accurate for the assessment of ambulatory activity, but some individuals function in the community using a combination of both walking and wheelchair activity. The purpose of this study was to assess the accuracy of the SAM and Actigraph at not detecting ambulatory activity