Physiological measurement最新文献

{"title":"Approaching volume status via electrical impedance tomography - an explorative study in healthy volunteers.","authors":"Sophie Wölbert, Johannes Hell, Stefan Schumann","doi":"10.1088/1361-6579/adda8d","DOIUrl":"https://doi.org/10.1088/1361-6579/adda8d","url":null,"abstract":"<p><strong>Objective: </strong>&#xD;Monitoring the volume status of patients remains a fundamentally unresolved issue in the perioperative setting but also in intensive care medicine. Electrical impedance tomography (EIT) enables noninvasive and radiation-free functional imaging of impedance changes of a cross-sectional plane of the thorax.&#xD;Approach.&#xD;We hypothesized that cardiac-induced impedance fluctuations in the EIT signal contain information about the global volume status. Therefore, we recorded EIT signals from 24 healthy volunteers before and up to 100 min after ingestion of 750 ml liquid following more than nine houres fluid restriction. We isolated a characteristic cardiac-induced impedance profile from the global impedance curve and compared its characteristics to measures of non-invasive hemodynamic monitoring and the diameter of the vena cava inferior determined via ultrasonography.&#xD;Main results.&#xD;The diameter of the vena cava inferior, mean arterial pressure and stroke volume index, did not change systematically after liquid ingestion. Heart rate was increased 20 min after, and heart rate variability was increased immediately after liquid ingestion. The amplitude, the area under curve and gradients of its rise and decline of the characteristic cardiac-induced impedance profile changed 60 min after liquid ingestion.&#xD;Significance.&#xD;Cardiac-induced pulsatile signals in EIT recordings changed characteristically after liquid ingestion, loosely corresponding with changes in heart rate and heart rate variability. These signals may contain valuable information about the general volume status and may be utilized for enhanced monitoring of a patient's volume status.&#xD.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144102352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated classification of seizure onset pattern using intracranial electroencephalogram signal of non-human primates.","authors":"Fahimeh Mohagheghian, Sujin Jiang, Mark Jude Connolly, Ellen Darrow Sproule, Robert E Gross, Xiao Hu, Annaelle Devergnas","doi":"10.1088/1361-6579/add9e3","DOIUrl":"https://doi.org/10.1088/1361-6579/add9e3","url":null,"abstract":"<p><strong>Objective: </strong>&#xD;To develop and validate a machine learning framework for the classification of distinct seizure onset patterns using intracranial EEG (iEEG) recordings in a non-human primate (NHP) model of penicillin-induced seizures.&#xD;Approach:&#xD;iEEG data were collected from six NHPs, comprising 1,496 frontal and 549 temporal lobe seizures. Seizure onset patterns were manually categorized into five types: Sharp Activity (5-15 Hz), Low Amplitude Fast Activity (15-30 Hz), Delta Brush (1-3 Hz with bursts), High Amplitude Spike (2-5 Hz), and Polyspike. A Random Forest classifier was trained using features extracted from optimized seizure onset segments. Feature selection and seizure segment length optimization were performed using nested cross-validation to enhance classification accuracy and generalizability.&#xD;Main results:&#xD;The classifier achieved strong performance with F1-scores exceeding 79% for Sharp Activity, Low Amplitude Fast Activity, and High Amplitude Spike patterns. When validated on an independent temporal lobe seizure dataset, the model demonstrated robust generalizability, achieving precision and sensitivity above 80% for Sharp Activity and High Amplitude Spike.&#xD;Significance:&#xD;These findings demonstrate that the suggested spectral and dynamic features can effectively distinguish seizure onset patterns and generalize in distinct brain regions. Although there are limitations due to use of manual annotations and the sample size of certain categories, the proposed approach provides a framework for automatic classification of seizure onset patterns. Further, the framework has a potential use for epilepsy research and clinical applications in future.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GPT-PPG: A GPT-based foundation model for photoplethysmography signals.","authors":"Zhaoliang Chen, Cheng Ding, Saurabh Kataria, Runze Yan, Minxiao Wang, Randall J Lee, Xiao Hu","doi":"10.1088/1361-6579/add988","DOIUrl":"https://doi.org/10.1088/1361-6579/add988","url":null,"abstract":"<p><p>This study introduces a novel application of a Generative Pre-trained Transformer (GPT) model tailored for photoplethysmography (PPG) signals, serving as a foundation model for various downstream tasks. Adapting the standard GPT architecture to suit the continuous characteristics of PPG signals, our approach demonstrates promising results. Our models are pre-trained on our extensive dataset that contains more than 200 million 30s PPG samples. We explored different supervised fine-tuning techniques to adapt our model to downstream tasks, resulting in performance comparable to or surpassing current state-of-the-art (SOTA) methods in tasks like atrial fibrillation detection. A standout feature of our GPT model is its inherent capability to perform generative tasks such as signal denoising effectively, without the need for further fine-tuning. This success is attributed to the generative nature of the GPT framework.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144079550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Catheter-to-tissue contact angle's effect on lesion formation and characterisation using multichannel bioimpedance method.","authors":"Anh Huyen Ngo, Minh Thao Hoang, Phuong Linh Nguyen, Thu Van Nguyen, Duc Thuan Nguyen, Minh Duc Nguyen","doi":"10.1088/1361-6579/add07f","DOIUrl":"https://doi.org/10.1088/1361-6579/add07f","url":null,"abstract":"<p><p><i>Objective.</i>Radiofrequency (RF) catheter ablation is a standard treatment for patients with cardiac arrhythmias, providing an efficient, minimally invasive solution. However, the ablation efficiency remains suboptimal due to numerous contributed factors that are overlooked in the literature and not monitored during the procedure. This paper explores the effect of catheter-to-tissue contact angles on lesion formations and the feasibility of the multichannel bioimpedance method in characterising the angles to inform cardiologists.<i>Approach.</i>Two silico simulations based on a realistic human model were built to: (1) simulate lesion formations with different catheter-to-tissue angles under varying conditions of powers and convection cooling, and (2) simulate multichannel bioimpedances measured at each catheter's location and angle. 13 locations were picked in all four chambers with 3 contact conditions (catheter lies along the muscle (0° and 180°), in perpendicular to the muscle (90°) and in middle angles (45° and 135°)). 64 electrodes divided into 4 bands were placed on the thorax for multichannel bioimpedances (3-terminal) measured between the catheter's second electrode E2 (I+,V+), and each pair of adjacent surface electrodes (I-,V-). ANOVA and Tukey's Honestly Significant Difference (HSD) tests were used to evaluate the contact angle's effect on the lesion formations and the bioimpedance's capability in distinguishing between angles.<i>Main results.</i>The results showed that 0° and 180° configurations generated significantly different lesions from other angles. The multichannel bioimpedances could recognise 0°/180° from other angles and correlated moderately to lesion sizes at low ablation power.<i>Significance.</i>This paper concludes that catheter-to-tissue angles can influence the lesion outcomes significantly and the multichannel bioimpedance is able to detect the angles that matter.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"46 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143974007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualizing functional network connectivity differences using an explainable machine-learning method.","authors":"Mohammad S E Sendi, Vaibhavi S Itkyal, Sabrina J Edwards-Swart, Ji Ye Chun, Daniel H Mathalon, Judith M Ford, Adrian Preda, Theo G M van Erp, Godfrey D Pearlson, Jessica A Turner, Vince D Calhoun","doi":"10.1088/1361-6579/adce52","DOIUrl":"https://doi.org/10.1088/1361-6579/adce52","url":null,"abstract":"<p><p><i>Objective</i>. Functional network connectivity (FNC) estimated from resting-state functional magnetic resonance imaging showed great information about the neural mechanism in different brain disorders. But previous research has mainly focused on standard statistical learning approaches to find FNC features separating patients from control. While machine learning models can improve classification accuracy, they often lack interpretability, making it difficult to understand how they arrive at their decisions.<i>Approach</i>. Explainable machine learning helps address this issue by identifying which features contribute most to the model's predictions. In this study, we introduce a novel framework leveraging SHapley Additive exPlanations (SHAPs) to identify crucial FNC features distinguishing between two distinct population classes.<i>Main results</i>. Initially, we validate our approach using synthetic data. Subsequently, applying our framework, we ascertain FNC biomarkers distinguishing between, controls and schizophrenia (SZ) patients with accuracy of 81.04% as well as middle aged adults and old aged adults with accuracy 71.38%, respectively, employing random forest, XGBoost, and CATBoost models.<i>Significance</i>. Our analysis underscores the pivotal role of the cognitive control network (CCN), subcortical network (SCN), and somatomotor network in discerning individuals with SZ from controls. In addition, our platform found CCN and SCN as the most important networks separating young adults from older.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"46 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144037805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting seizure episodes and high-risk events in autism through adverse behavioral patterns.","authors":"Yashar Kiarashi, Johanna Lantz, Matthew A Reyna, Conor Anderson, Ali Bahrami Rad, Jenny Foster, Tania Villavicencio, Theresa Hamlin, Gari D Clifford","doi":"10.1088/1361-6579/adcafd","DOIUrl":"https://doi.org/10.1088/1361-6579/adcafd","url":null,"abstract":"<p><p><i>Objective.</i>To determine whether historical behavior data can predict the occurrence of high-risk behavioral or Seizure events in individuals with profound Autism Spectrum Disorder (ASD), thereby facilitating early intervention and improved support.<i>Approach.</i>We conducted an analysis of nine years of behavior and seizure data from 353 individuals with ASD. Our analysis focused on the seven most common behaviors labeled by a human, while all other behaviors were grouped into an 'other' category, resulting in a total of eight behavior categories. Using a deep learning algorithm, we predicted the occurrence of seizures and high-risk behavioral events for the following day based on data collected over the most recent 14 d period. We employed permutation-based statistical tests to assess the significance of our predictive performance.<i>Main results.</i>Our model achieved accuracies of 70.5% for seizures, 78.3% for aggression, 80.2% for SIB, and 85.7% for elopement. All results were significant for more than 85% of the population. These findings suggest that high-risk behaviors can serve as early indicators not only of subsequent challenging behaviors but also of upcoming seizure events.<i>Significance.</i>By demonstrating, for the first time, that behavioral patterns can predict seizures as well as adverse behaviors, this approach expands the clinical utility of predictive modeling in ASD. Early warning systems derived from these predictions can guide timely interventions, enhance inclusion in educational and community settings, and improve quality of life by helping anticipate and mitigate severe behavioral and medical events.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"46 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144006326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heart-carotid pulse-wave velocity via laser-Doppler vibrometry as a biomarker for arterial stiffening: a feasibility study.","authors":"Simeon Beeckman, Smriti Badhwar, Yanlu Li, Soren Aasmul, Nilesh Madhu, Hakim Khettab, Elie Mousseaux, Umit Gencer, Pierre Boutouyrie, Rosa Maria Bruno, Patrick Segers","doi":"10.1088/1361-6579/adcb85","DOIUrl":"https://doi.org/10.1088/1361-6579/adcb85","url":null,"abstract":"<p><p><i>Objective</i>. Large artery stiffening leads to an increase in cardiovascular risk and organ damage of the kidneys, brain or the heart. Biomarkers that allow for early detection of this phenomenon are a point of interest in research, with pulse-wave velocity (PWV) having been proven useful in predicting and monitoring arterial stiffness. We previously introduced a laser Doppler vibrometry (LDV) prototype which can measure carotid-femoral PWV (cfPWV). In this work, we assess the feasibility of using the same device to infer heart-carotid pulse-transit time (hcPTT) as a first step towards measuring heart-carotid PWV (hcPWV). The advantage of hcPWV over cfPWV is that the ascending aorta, which is the most distensible segment of the aorta contributing most to total arterial compliance, is included in the arterial pathway.<i>Approach</i>. Signals were simultaneously acquired from a location on the chest (near either the base or the apex of the heart) and the right carotid artery for 100 patients (45% female). Fiducial points on the heart waveforms are associated with opening and closure (second heart sound; S2) of the aortic valve, which can be combined with, respectively, the foot and dicrotic notch (DN) of the carotid waveform to retrieve hcPTT. Considering two distinct heart-signal measurement sites, four hcPTT estimations are evaluated in about 94% of all measurements.<i>Main results</i>. Correlations between these and known predictors of arterial stiffness i.e. age, blood pressure and carotid-femoral PTT via applanation tonometry indicated that combining S2 from a heart-measurement site located at the base of the heart, with the carotid DN yields hcPTT providing convincing correlations with known determinants of arterial stiffness (<i>ρ</i> = 0.377 with age).<i>Significance.</i>We conclude that LDV may provide a corollary biomarker of arterial stiffness, encompassing the ascending aorta.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"46 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144064420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the limitations of blood pressure estimation using the photoplethysmography signal.","authors":"Felipe M Dias, Diego A C Cardenas, Marcelo A F Toledo, Filipe A C Oliveira, Estela Ribeiro, Jose E Krieger, Marco A Gutierrez","doi":"10.1088/1361-6579/adcb86","DOIUrl":"https://doi.org/10.1088/1361-6579/adcb86","url":null,"abstract":"<p><p><i>Objetive.</i>Hypertension, a leading contributor to cardiovascular morbidity, underscores the need for accurate and continuous blood pressure (BP) monitoring. Photoplethysmography (PPG) emerges as a promising approach for continuous BP monitoring. However, the precision of BP estimates derived from PPG signals has been the subject of ongoing debate, requiring a comprehensive evaluation of their efficacy. This paper aims to provide the potentials and limitations regarding BP estimation from single-site PPG signals.<i>Approach.</i>We developed a calibration-based Siamese ResNet model for BP estimation. We compared the use of normalized PPG (N-PPG) against the normalized invasive arterial BP (N-IABP) signals as input. N-IABP signals, while not directly presenting systolic (SBP) and diastolic (DBP) BP values, are expected to offer more precise estimations than PPG since it is a direct pressure sensor inside the body. Thus, if N-IABP poses challenges in BP estimation, predicting BP from PPG signals might be even more challenging.<i>Main results.</i>Our evaluation, conducted using the AAMI and BHS standards on the VitalDB dataset, revealed that inference using N-IABP signals meet with AAMI standards for both SBP and DBP, with errors of1.29±6.33mmHg for systolic pressure and1.17±5.78for diastolic pressure. In contrast, N-PPG based inference exhibited inferior performance than N-IABP, presenting1.49±11.82mmHg and0.89±7.27mmHg for systolic and diastolic pressure respectively in their best setup.<i>Significance.</i>Our findings establish a critical benchmark for PPG performance, providing realistic expectations for its BP estimation capabilities. We concluded that while PPG signals contain BP-correlated information, they may not suffice for accurate prediction.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"46 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144036596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Apple watch accuracy in monitoring health metrics: a systematic review and meta-analysis.","authors":"Ju-Pil Choe, Minsoo Kang","doi":"10.1088/1361-6579/adca82","DOIUrl":"10.1088/1361-6579/adca82","url":null,"abstract":"<p><p><i>Objective</i>. Wearable technology like the Apple Watch is increasingly important for monitoring health metrics. Accurate measurement is crucial, as inaccuracies can impact health outcomes. Despite extensive research, findings on the Apple Watch's accuracy vary across different conditions. While previous reviews have summarized findings, few have utilized a meta-analytic approach. This study aims to quantitatively evaluate the accuracy of the Apple Watch in measuring health metrics. The accuracy of the Apple Watch was assessed in measuring energy expenditure (EE), heart rate (HR), and step counts (steps).<i>Approach</i>. We searched Embase, PubMed, Scopus, and SPORTDiscus for studies on adults using the Apple Watch compared to reference measures. The Bland-Altman framework was applied to assess mean bias and limits of agreement (LoA), with robust variance estimation to address within-study correlations. Heterogeneity was assessed across variables such as age, health status, device series, activity intensity, and activity type. Additionally, the mean absolute percentage error (MAPE) reported in the included studies was summarized by subgroups.<i>Main results</i>. This review included 56 studies, comprising 270 effect sizes on EE (71), HR (148), and steps (51). The meta-analysis showed a mean bias of 0.30 (LoA: -2.09-2.69) for EE (kcal min^-1), -0.12 (LoA: -11.06-10.81) for HR (beats min^-1), -1.83 (LoA: -9.08-5.41) for steps (steps min^-1). The forest plots showed variability in LoA across subgroups. For MAPE, all subgroups for EE exceeded the 10% validity threshold, while none of the subgroups for HR exceeded this threshold. For steps, some subgroups exceeded 10%, highlighting variability in accuracy based on different conditions.<i>Significance</i>. This study demonstrates that while the Apple Watch generally provides accurate HR and step measurements, its accuracy for EE is limited. Although HR and step measurements showed acceptable accuracy, variability was observed across different user characteristics and measurement conditions. These findings highlight the importance of considering such factors when evaluating validity.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143812039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting motor skills in preschool age: a focus on balance regulation.","authors":"Stephan Gutschow, Dominik D Kranz, Sascha Tamm, Andy Papke, Aileen Kotzsch, Jan F Kraemer, Niels Wessel","doi":"10.1088/1361-6579/adc86d","DOIUrl":"10.1088/1361-6579/adc86d","url":null,"abstract":"<p><p><i>Objective</i>. This study examines the influence on balance regulation of a training program of targeted coordination exercises to improve balance skills in preschool children between the ages of 3 and 7 (in German 'Kindergarten'). On average, the children received targeted, age-appropriate training in basic coordination over a period of 3-4 years during their preschool years. The present results consider selected measurements of balance skills in 5- to 7-year-old children at the end or in the last third of the intervention period. It aims to determine if structured training programs can significantly improve postural control and serve as early interventions for enhancing motor skills.<i>Approach</i>. A cohort of 136 children participated in weekly two-hour coordination training over three years, focusing on foundational motor skills, including balance and spatial orientation. Postural control was measured using the Leonardo Mechanograph® GRFP LT force plate system, employing both linear and nonlinear analyses. The experimental group's performance was compared to a control group of 86 children who did not receive targeted training.<i>Main Results</i>. The experimental group exhibited significant improvements in balance regulation, reflected in steadier posture and reduced fluctuations (<i>p</i>< 0.01). Nonlinear analysis revealed increased stability and frequent occurrence of stationary balance phases. Linear discriminant analysis showed moderate separability (AUC = 0.69) between groups based on balance parameters. The findings underscore the role of intensive, targeted coordination training in enhancing neurophysiological modulation of postural control.<i>Significance</i>. The study highlights the potential of early, structured motor skill programs to address declining physical activity trends and improve holistic child development. These interventions could play a critical role in promoting health, preventing postural issues, and supporting cognitive and motor development in early childhood.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143772863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}