A novel deep domain adaptation method for automated detection of sleep apnea/hypopnea events
Objective. Sleep apnea –hypopnea syndrome (SAHS) is a common sleep-related respiratory disorder that is generally assessed for severity using polysomnography (PSG); however, the diversity of sampling devices and patients makes this not only costly but may also degrade the performance of the algorithms. Approach. This pa per proposes a novel deep domain adaptation module which uses a long short-term memory–convolutional neural network embedded with the channel attention mechanism to achieve autonomous extraction of high-quality features. Meanwhile, a domain adaptation module was built to achieve domain-invariant f eatur...
Source: Physiological Measurement - February 6, 2023 Category: Physiology Authors: Zonglin Du, Jiao Wang, Yingxin Ren and Yingtong Ren Source Type: research
Influence of neonatal endotracheal tube dimensions on oscillometry-acquired reactance: a bench study
Objective. To examine the influence of the endotracheal tube (ETT) on respiratory reactance (Xrs) measured with the forced oscillation technique (FOT) and develop a correction method for it. Approach. In a bench study, the reactance of ETTs (Xtube) with different dimensions was measured on a breathing test lung in various respiratory settings. Main results. Xtube can be accurately predicted by a fitted formula, with an R2 of 0.97, with negligible effects due to changes in respiratory pattern and lung volume. Significance. The developed formula offers the ability to measure ETT-independent Xrs values of patients, improving ...
Source: Physiological Measurement - January 31, 2023 Category: Physiology Authors: Rosemijne R W P Pigmans, Ruud W van Leuteren, Anouk W J Scholten, Chiara Veneroni, Anton H van Kaam, Jeroen Hutten, Raffaele L Dellac à and Frans H C de Jongh Source Type: research
Artificial intelligence can use physiological parameters to optimize treatment strategies and predict clinical deterioration of sepsis in ICU
Objective. Sepsis seriously threatens human life. Early identification of a patient's risk status and appropriate treatment can reduce septic shock risk and mortality. Our purpose is to design and validate an adjunctive therapy system based on deep reinforcement learning (DRL), which can provide treatment recommendations with providence and assess the patient's risk status and treatment options in the early stages. Approach. Data is from the Beth Israel Deaconess Medical Center. The raw data included 53 423 patients from MIMIC-III. Of these, 19 620 eligible samples were screened to form the final cohort. First, the patient...
Source: Physiological Measurement - January 30, 2023 Category: Physiology Authors: Quan Zhang, Jianqi Wang, Guohua Liu and Wenjia Zhang Source Type: research
Interpretation and further development of the hypnodensity representation of sleep structure
This study provides insights in, and proposes new, representations of sleep that may enhance our comprehension about sleep and sleep disorders. (Source: Physiological Measurement)
Source: Physiological Measurement - January 17, 2023 Category: Physiology Authors: Iris A M Huijben, Lieke W A Hermans, Alessandro C Rossi, Sebastiaan Overeem, Merel M van Gilst and Ruud J G van Sloun Source Type: research
Limitations in evaluating COVID-19 protective face masks using open circuit spirometry systems: respiratory measurement mask introduces bias in breathing pressure and perceived respiratory effort
Objective. In response to the COVID-19 pandemic and the resulting widespread use of protective face masks, studies have been and are being conducted to investigate potential side effects of wearing masks on the performance and physiological parameters of wearers. The purpose of the present study is to determine whether and to what extent the use of a respiratory measurement (RM) mask —which is normally used during open-circuit spirometry—influences the results of these types of studies. Approach. 34 subjects were involved in this intra-subject study with a cross-over design. Four different protective face masks, Commun...
Source: Physiological Measurement - January 13, 2023 Category: Physiology Authors: Robert Seibt, Mona B är, Monika A Rieger and Benjamin Steinhilber Source Type: research
Cardiovascular autonomic modulation during passive heating protocols: a systematic review
Objective. To conduct a systematic review of the possible effects of passive heating protocols on cardiovascular autonomic control in healthy individuals. Approach. The studies were obtained from MEDLINE (PubMed), LILACS (BVS), EUROPE PMC (PMC), and SCOPUS databases, simultaneously. Studies were considered eligible if they employed passive heating protocols and investigated cardiovascular autonomic control by spontaneous methods, such as heart rate variability (HRV), systolic blood pressure variability (SBPV), and baroreflex sensitivity (BRS), in healthy adults. The revised Cochrane risk-of-bias tool (RoB-2) was used to as...
Source: Physiological Measurement - January 12, 2023 Category: Physiology Authors: Felipe Castro Ferreira, Michelle Cristina Salabert Vaz Padilha, Teresa Mell da Mota Silva Rocha, Ligia Soares Lima, Angelica Carandina, Chiara Bellocchi, Eleonora Tobaldini, Nicola Montano, Pedro Paulo da Silva Soares and Gabriel Dias Rodrigues Source Type: research
A dynamic learning-based ECG feature extraction method for myocardial infarction detection
In this study, a dynamic learning algorithm is applied to discover prominent features for identifying MI patients via mining the hidden inherent dynamics in ECG signals. Firstly, the distinctive dynamic features extracted from the multi-scale decomposition of dynamic modeling of the ECG signals effectively and comprehensibly represent the pathological ECG changes. Secondly, a few most important dynamic features are filtered through a hybrid feature selection algorithm based on filter and wrapper to form a representative reduced feature set. Finally, different classifiers based on the reduced feature set are trained and tes...
Source: Physiological Measurement - January 4, 2023 Category: Physiology Authors: Qinghua Sun, Zhanfei Xu, Chunmiao Liang, Fukai Zhang, Jiali Li, Rugang Liu, Tianrui Chen, Bing Ji, Yuguo Chen and Cong Wang Source Type: research
Evaluation of raw segmental bioelectrical impedance variables throughout anterior cruciate ligament reconstruction rehabilitation
Background. Raw bioelectrical impedance analysis (BIA) variables are related to physical function in healthy and diseased populations. Therefore, BIA may be an insightful, noninvasive method of assessment to track following anterior cruciate ligament reconstruction (ACLR). Objectives. Evaluate phase angle, reactance and impedance at 50 kHz (PhA50, Xc50, and Z50, respectively) in the operative (OP) and non-operative (NOP) limbs during ACLR rehabilitation. Approach. Seventeen patient (12 M, 5 F; 18.8 ± 4.8 years) clinic reports were evaluated prior to ACLR (PRE), two- (2 W), six- (6 W), and twelve-weeks (12 W) post-ACLR and...
Source: Physiological Measurement - December 28, 2022 Category: Physiology Authors: Christopher J Cleary, Joseph P Weir, Bryan G Vopat and Ashley A Herda Source Type: research
Age-dependent cardiorespiratory directional coupling in wake-resting state
Objective. Cooperation in the cardiorespiratory system helps maintain internal stability. Various types of system interactions have been investigated; however, the characteristics of the interactions have mostly been studied using data collected in well-defined physiological states, such as sleep. Furthermore, most analyses provided general information about the interaction, making it difficult to quantify how the systems influenced one another. Approach. Cardiorespiratory directional coupling was investigated in different age groups (20 young and 19 elderly subjects) in a wake-resting state. The directionality index (DI) ...
Source: Physiological Measurement - December 28, 2022 Category: Physiology Authors: Heenam Yoon Source Type: research
Deep feature-domain matching for cardiac-related component separation from a chest electrical impedance tomography image series: proof-of-concept study
Objectives. The cardiac-related component in chest electrical impedance tomography (EIT) measurement is of potential value to pulmonary perfusion monitoring and cardiac function measurement. In a spontaneous breathing case, cardiac-related signals experience serious interference from ventilation-related signals. Traditional cardiac-related signal-separation methods are usually based on certain features of signals. To further improve the separation accuracy, more comprehensive features of the signals should be exploited. Approach. We propose an unsupervised deep-learning method called deep feature-domain matching (DFDM), wh...
Source: Physiological Measurement - December 28, 2022 Category: Physiology Authors: Ke Zhang, Maokun Li, Haiqing Liang, Juan Wang, Fan Yang, Shenheng Xu and Aria Abubakar Source Type: research
Multi-modal fusion model for predicting adverse cardiovascular outcome post percutaneous coronary intervention
Conclusion. To the best of our knowledge, this is the first study that developed a deep learning model with joint fusion architecture for the prediction of post-PCI prognosis and outperformed machine learning models developed using traditional single-source features (clinical variables or E CG features). Adding ECG data with clinical variables did not improve prediction of all-cause mortality as may be expected, but the improved performance of related cardiac outcomes shows that the fusion of ECG generates additional value. (Source: Physiological Measurement)
Source: Physiological Measurement - December 22, 2022 Category: Physiology Authors: Amartya Bhattacharya, Sudarsan Sadasivuni, Chieh-Ju Chao, Pradyumna Agasthi, Chadi Ayoub, David R Holmes, Reza Arsanjani, Arindam Sanyal and Imon Banerjee Source Type: research
An empirical study of modified beat SQI based majority voting fusion method for heart-rate estimation in noisy multimodal cardiovascular signals
This study aims to: (i) propose a modified beat signal quality index-based majority voting fusion (MMVF) method to deal with extremely noisy cardiovascular signals; (ii) generate synthetic noise datasets from standard PhysioNet datasets by adding different types of ECG noises, i.e. baseline wander (bw), electrode motion (em), muscle artifact (ma), and realistic artificial ABP noises in clean or low-noise ECG and ABP signals, respectively; and (iii) analyze the effectiveness of the MMVF method for heart-rate estimation with different combinations of beat detectors. Approach. The modified beat signal quality index in the pro...
Source: Physiological Measurement - December 22, 2022 Category: Physiology Authors: Shalini A Rankawat Source Type: research
Lung volumes measurement using novel pressure derived method in participants with obstructive, restrictive and healthy lungs
Conclusions. Lung volumes measured by BP and CT had high concordance in the scenario of varied pulmonary conditions including lung bullae, restrictive and obstructive diseases. The new PDM device, had low intra-test variability, and was easy to perform, with a reasonable co ncordance with BP. (Source: Physiological Measurement)
Source: Physiological Measurement - December 20, 2022 Category: Physiology Authors: Jacob Zac, Salomon Zac, Rogelio P érez-Padilla, Arantxa Remigio-Luna, Nicolas Guzmán-Boulloud, Laura Gochicoa-Rangel, Carlos Guzmán-Valderrábano and Ireri Thirión-Romero Source Type: research
Seizure forecasting using machine learning models trained by seizure diaries
Objectives. People with refractory epilepsy are overwhelmed by the uncertainty of their next seizures. Accurate prediction of future seizures could greatly improve the quality of life for these patients. New evidence suggests that seizure occurrences can have cyclical patterns for some patients. Even though these cyclicalities are not intuitive, they can be identified by machine learning (ML), to identify patients with predictable vs unpredictable seizure patterns. Approach. Self-reported seizure logs of 153 patients from the Human Epilepsy Project with more than three reported seizures (totaling 8337 seizures) were used t...
Source: Physiological Measurement - December 14, 2022 Category: Physiology Authors: Ezequiel Gleichgerrcht, Mircea Dumitru, David A Hartmann, Brent C Munsell, Ruben Kuzniecky, Leonardo Bonilha and Reza Sameni Source Type: research
Application of Fourier-Bessel expansion and LSTM on multi-lead ECG for cardiac abnormalities identification
Objective. The availability of online electrocardiogram (ECG) repositories can aid researchers in developing automated cardiac abnormality diagnostic systems. Using such ECG repositories, this study aims to develop an algorithm that can assist physicians in diagnosing cardiac abnormalities. Approach. The PhysioNet/CinC 2021 Challenge has opened the venues for creating benchmark algorithms using standard and relatively diverse 12-lead ECG datasets. This work attempts to create a new machine learning approach for identifying common cardiac abnormalities using an ensemble-based classification with two models resulting from tw...
Source: Physiological Measurement - December 12, 2022 Category: Physiology Authors: Nidhi Kalidas Sawant and Shivnarayan Patidar Source Type: research
