Physiological measurement最新文献

{"title":"Heart rate fragmentation and its relationship with baroreflex control in type 2 diabetes with and without cardiovascular autonomic neuropathy.","authors":"Gabriela Aguiar Mesquita Galdino, Thomas Beltrame, Letícia de Souza Sant'Anna, Andréia Machado Santos, Patrícia Rehder-Santos, Étore de Favari Signini, Rubens Fazan, Luiz Eduardo Virgilio Silva, Alberto Porta, Aparecida Maria Catai","doi":"10.1088/1361-6579/aeae9f","DOIUrl":"10.1088/1361-6579/aeae9f","url":null,"abstract":"<p><p><i>Objective.</i>The link between ultrafast heart period (HP) dynamics and baroreflex is poorly analyzed, especially in pathologies altering autonomic regulation. This study assesses this link via heart rate fragmentation (HRF) analysis in type 2 diabetes mellitus (T2DM) with or without cardiac autonomic neuropathy (CAN).<i>Approach.</i>Sixty-four individuals with T2DM, divided into those with CAN (DM_CAN,<i>n</i>= 28, 55-62 years, 17 males) and without CAN (DM_noCAN,<i>n</i>= 36, 49-61 years, 19 males), were evaluated at supine resting (REST) and during active standing (STAND). HRF was calculated using sequences of five consecutive HPs categorized as words with zero (<i>W</i>₀), one (<i>W</i>₁), two (<i>W</i>₂), three (<i>W</i>₃) and total (PIP) inflection points. Baroreflex control was assessed from HP and systolic arterial pressure (SAP) variabilities via cross-spectral analyses in low frequency (LF) and high frequency (HF) bands and via sequence method (SEQ). Also squared coherence between HP and SAP in LF and HF bands, namely<i>K</i>²_HP-SAP(LF) and<i>K</i>²_HP-SAP(HF), and percentage of baroreflex sequences (%_SEQ) were assessed.<i>Main results. W</i>₃was higher in DM_CANat REST compared to DM_noCANand W₃increased in STAND for both groups. At REST %_SEQand<i>K</i>²_HP-SAP(HF) were positively associated with<i>W</i>₀and<i>W</i>₁, while they were negatively associated with<i>W</i>₃and PIP. During STAND<i>K</i>²_HP-SAP(LF), %_SEQand α_SEQwere negatively correlated with PIP and<i>W</i>₃.<i>Significance</i>. Greater presence of inflection points in 4-beat words was associated with a less effective baroreflex, thus suggesting that an impaired baroreflex augmented the likelihood of fast HP changes in DM_CAN.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113484","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":"A contactless approach for accurate sleep stage detection using the Sleepal AI Lamp.","authors":"Zhuo Diao, Yueting Li, Jianpeng Wang, Shengyu Guan, Xinwei Wang, Wenxiong Cui, Xin Shi, Tong Liu, Kailai Sun, Jingyu Wang, Dian Fan, Thomas Penzel","doi":"10.1088/1361-6579/aeb104","DOIUrl":"10.1088/1361-6579/aeb104","url":null,"abstract":"<p><p><i>Objective.</i>To validate the accuracy and clinical feasibility of a noncontact radar system (Sleepal AI Lamp) for assessing sleep architecture and staging. Although noncontact radar sensors can capture respiratory and motor mechanics without physical attachment, robust validation in large-scale, pathologically diverse cohorts remains scarce.<i>Approach.</i>Nocturnal respiratory and body movement signals were assessed in 1022 adults using simultaneous measurements from a frequency-modulated continuous-wave bedside radar and gold-standard Polysomnography. The cohort included individuals with normal sleep profiles and patients with varying severities of obstructive sleep apnea. A frequency-augmented deep learning architecture interpreted these respiratory and movement signals.<i>Main results.</i>In the independent validation set, binary sleep-wake classification achieved 92.7% accuracy, a Cohen's kappa of 0.792, 96.4% sleep sensitivity, 80.8% sleep specificity, and a macro-averaged<i>F</i>1 score of 0.896. Four-stage classification (Wake, Light, Deep, and rapid eye movement (REM) sleep) achieved 77.2% accuracy, a Cohen's kappa of 0.677, a macro-averaged<i>F</i>1 score of 0.768, and balanced accuracy/macro-recall of 77.4%, with stage-specific<i>F</i>1 scores of 0.839, 0.740, 0.691, and 0.802 for Wake, Light, Deep, and REM, respectively.<i>Significance.</i>The findings support the validity of the 60 GHz radar-based system for automated assessment of sleep macrostructure. By capturing stage-specific respiratory and movement phenotypes without physical attachment, this technology may provide an unobtrusive tool for home-based screening, longitudinal recovery tracking, and population-level sleep epidemiology.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113510","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":"Detection of Chagas disease from the ECG: the George B. Moody PhysioNet Challenge 2025.","authors":"Matthew A Reyna, Soheil Saghafi, Zuzana Koscova, Audrey Weigle, Jan Pavlus, Andoni Elola, Salman Seyedi, Kiersten Campbell, Qiao Li, Sandhi M Barreto, Ester C Sabino, Antônio H Ribeiro, Antonio Luiz P Ribeiro, Reza Sameni, Gari D Clifford","doi":"10.1088/1361-6579/aead44","DOIUrl":"10.1088/1361-6579/aead44","url":null,"abstract":"<p><p><i>Objective.</i>Chagas disease is a parasitic infection that is endemic to Latin America and primarily transmitted by insects. When untreated, Chagas disease can cause cardiomyopathy. Serological testing capacities for Chagas disease are limited, but Chagas cardiomyopathy often manifests in electrocardiograms (ECGs), providing an opportunity to use ECG-based screening to prioritize patients for testing and treatment.<i>Approach.</i>The George B. Moody PhysioNet Challenge 2025 invited teams to develop algorithmic approaches for identifying potential cases of Chagas disease from ECGs. The Challenge metric, denoted by TPR@5%, measured the true positive rate of the top 5% of patients determined by an algorithm to be the most likely to have Chagas disease, reflecting the Brazilian serological testing capacity. The data included more than 360 000 ECGs from five Brazilian databases. We also developed an ensemble algorithm for the best-performing entries.<i>Main results.</i>This Challenge provided multiple innovations. First, we leveraged several datasets with labels from either patient reports or serological testing, providing a large dataset with weak labels and smaller datasets with strong labels. Second, we augmented the data to support model robustness and generalizability to unseen data sources. Third, we applied an evaluation metric, TPR@5%, that captured the local serological testing capacity for Chagas disease to frame the Challenge as a triage task. Fourth, we developed an ensemble model that combined the individual Challenge models to improve performance. These innovations provided reliable sensitivity at clinically relevant operating points. The performance of the top-performing Challenge model (Biomed-Cardio) varied performed well across datasets (TPR@5% of 0.468 on REDS-II and TPR@5% of 0.125 on ELSA-Brasil), and our ensemble-based approach demonstrated consistent performance across datasets (TPR@5% of 0.389 on REDS-II and TPR@5% of 0.146 on ELSA-Brasil).<i>Significance.</i>Over 630 participants from 111 teams submitted over 1300 entries during the Challenge, representing diverse approaches from academia and industry worldwide.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13682419/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149075742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliability and agreement between alternative CO₂paradigms for assessment of cerebrovascular reactivity in cerebral small vessel disease.","authors":"Osian Llwyd, Karolina Feakins, Catriona Stewart, James Thomas, Alastair Webb","doi":"10.1088/1361-6579/aeac99","DOIUrl":"10.1088/1361-6579/aeac99","url":null,"abstract":"<p><p>Cerebrovascular reactivity (CVR) to CO₂is increasingly used as an index of cerebrovascular health and function in trials in cerebral small vessel disease (CSVD). Further work is needed to determine the validity and optimal parameters of this technique. In 75 CSVD patients in the placebo-controlled, crossover OxHARP trial of sildenafil, agreement and reproducibility of baseline (1st visit) and placebo visit CVR was derived comparing 4% and 6% CO₂exposure. Peak response to each dose was used to estimate CVR (Δ cerebral blood velocity/ Δ end-tidal CO₂) using absolute (cm.s^-1/etCO₂%), fully standardised (%Δ/%Δ) or semi-standardised (%Δ/etCO₂%) approaches, and compared to CVR from delay-shifted, beat-to-beat associations from general linear models (GLM). Single-point measurements showed less inter- and intra-participant variability. The 6% CO₂prompted higher absolute and standardised CVR values, although this was not observed with the semi-standardised of analysis. CVR estimates using absolute values showed comparable inter- and intra-participant variability across CO₂challenges. However, reproducibility improved when CVR values were standardised following exposure to 6% CO₂or derived using GLM that incorporated data from both 4% and 6% CO₂data. The strongest agreement between CVR methods was achieved with analyses using absolute values. CVR assessments were reproducible, but this reliability was influenced by CO₂dose and the analytical approach. While single-point measurements showed the best inter- and intra-participant variability, overall, CVR estimation using a GLM demonstrated a superior test-retest reliability across visits.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149063539","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":"CSTO-Net: Cross-View Spectral-Transport and Topology-Operator Network for EEG Emotion Recognition.","authors":"Zhaoyi Sun, Jian Liu, Zhaolong Liu, Guangxin Wu, Hua Jianning","doi":"10.1088/1361-6579/aeb59e","DOIUrl":"https://doi.org/10.1088/1361-6579/aeb59e","url":null,"abstract":"<p><strong>Objective: </strong>Multi-view electroencephalography (EEG) emotion recognition must decide how the spectral graph sets of different connectivity views correspond and how their graph propagation operators interact. We present CSTO-Net, a cross-view spectral-transport and topology-operator network for EEG-based emotion recognition.&#xD;&#xD;Approach: CSTO-Net integrates three window-wise views: dynamic differential entropy (DDE) as node attributes, amplitude-envelope Pearson correlation coefficient (PCC) graphs, and phase-locking value (PLV) graphs. Cross-View Spectral Transport Routing (CSTR) formulates PCC-PLV spectral correspondence as an entropy-regularized optimal-transport problem with explicit marginal constraints, deliberately separating correspondence estimation from band-importance estimation. Directional Cross-Topology Modulation (DCTM) performs ordered composition of the two routed propagation operators on shared node features and encodes order-dependent propagation discrepancy via a provably skew-symmetric graph-operator commutator with signed decomposition.&#xD;&#xD;Main results: On the Database for Emotion Analysis using Physiological Signals (DEAP) dataset, CSTO-Net achieves 93.95 ± 2.50% valence and 94.97 ± 2.72% arousal accuracy under the subject-dependent setting, and 93.73% and 94.54% under participant-wise five-fold subject-independent cross-validation across 32 participants. On the SJTU Emotion EEG Dataset (SEED), it achieves 93.12% under the standard subject-dependent split, 91.36% under 15-fold leave-one-subject-out evaluation across 15 participants, and 98.05 ± 2.32% under subject-dependent five-fold cross-validation. Ablation studies confirm that both CSTR and DCTM contribute substantially to recognition accuracy.&#xD;&#xD;Significance: These results demonstrate that explicit cross-view spectral correspondence and topology-operator-level interaction provide complementary benefits for EEG emotion recognition, offering an interpretable route for modeling order-sensitive interactions between functional connectivity views.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207648","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":"Dynamic indicators of resilience in COVID-19 patients: a comprehensive analysis of heart rate dynamics.","authors":"Anna Kuranova, Geeske Peeters, Jan Wijgerse, Jeannette B Peters, Evertine J Abbink, Harry van Goor, Sebastian Bredie, René Melis","doi":"10.1088/1361-6579/aeafa9","DOIUrl":"10.1088/1361-6579/aeafa9","url":null,"abstract":"&lt;p&gt;&lt;p&gt;&lt;i&gt;Objective.&lt;/i&gt;Physiological resilience-the ability to maintain or regain homeostasis after a stressor-is rarely quantified in clinical practice. Complex-systems theory proposes dynamic indicators of resilience based on variation, autocorrelation, and complexity in physiological signals. We examined whether such indicators, derived from routine ward-monitor heart-rate (HR) data, were associated with in-hospital COVID-19 severity and long-term survival.&lt;i&gt;Approach.&lt;/i&gt;Routine ward-monitor HR data from 181 hospitalized COVID-19 patients were analyzed at 1 min resolution. Dynamic indicators were calculated for the first valid 270 min interval after admission and for an extended 1620 min summary based on the first six sequential valid 270 min intervals within the first three days post-admission. For the extended summary, indicators were calculated per interval and summarized as change from the first interval. Logistic regression was used to assess associations with an in-hospital composite outcome of COVID-19-related complications, ICU admission, or death. Cox proportional hazards models were used to examine survival; systematic post-discharge follow-up was conducted only in patients aged ⩾60 years. Models were adjusted for age and sex.&lt;i&gt;Main Results.&lt;/i&gt;Greater minute-level HR variation during the early 270 min interval, reflected by standard deviation (SD) and range, was associated with lower odds of severe in-hospital disease (OR = 0.62,&lt;i&gt;p&lt;/i&gt;= 0.02 for SD; OR = 0.64,&lt;i&gt;p&lt;/i&gt;= 0.01 for range) and better survival (hazard ratio = 0.51,&lt;i&gt;p&lt;/i&gt;= 0.045 for SD). Short-lag autocorrelations during the 270 min interval were positively associated with quick sequential organ failure assessment, but were not clearly associated with the in-hospital severity composite. Sample entropy showed time-scale-dependent associations with in-hospital severity: higher sample entropy during the 270 min interval was associated with higher odds of severe disease (OR = 1.46,&lt;i&gt;p&lt;/i&gt;= 0.04), whereas higher sample entropy in the extended 1620 min summary was associated with lower odds of severe disease (OR = 0.68,&lt;i&gt;p&lt;/i&gt;= 0.02). Higher fractal dimension (FracDim) in the extended summary was associated with increased long-term mortality in age-interaction models (hazard ratio = 1.93,&lt;i&gt;p&lt;/i&gt;= 0.04). Age-dependent patterns were observed, most clearly for the association between FracDim and long-term mortality.&lt;i&gt;Significance.&lt;/i&gt;Minute-level HR dynamics may contain clinically relevant information beyond conventional static HR summaries. In this exploratory study, early HR variation and autocorrelation appeared most relevant for acute disease severity, whereas extended-window complexity indicators showed more mixed and age-dependent associations. These findings suggest that dynamic resilience indicators can be extracted from routinely collected monitoring data, but require validation in larger cohorts with standardized preprocessing, transparent handling of monitoring","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113452","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":"Small-sample ERP-assisted screening for depression and audio multimodal fusion based on the MODMA dataset.","authors":"Jiaxuan Wan, Zhenshen Qu","doi":"10.1088/1361-6579/aeb59c","DOIUrl":"https://doi.org/10.1088/1361-6579/aeb59c","url":null,"abstract":"<p><strong>Objective: </strong>Event-related potentials (ERPs) may provide objective neurophysiological markers for depression-assisted screening. We benchmarked structured ERP features and strictly paired ERP-audio fusion in small-sample, subject-level settings.</p><p><strong>Approach: </strong>Two experiments on MODMA used leakage-controlled leave-one-subject-out (LOSO) validation, with all preprocessing, tuning and fusion restricted to training folds. Experiment I included 52 ERP subjects retained after quality control (QC) (23 with major depressive disorder (MDD) and 29 healthy controls (HC)), each represented by a 60-feature vector, to compare machine learning (ML) and deep learning (DL) models. This paper additionally evaluated convolutional neural network (CNN)-based architectures (EEGNet and ShallowConvNet) on a multichannel ERP time-series representation (28 channels × 129 samples) constructed from subject-level averaged cue-locked and dot-locked ERPs. Experiment II used 37 strictly paired ERP-audio subjects (16 MDD, 21 HC) with 178 audio features to evaluate unimodal and decision-level fusion under balanced and screening objectives.</p><p><strong>Main results: </strong>In Experiment I, SVM-RBF achieved area under the ROC curve (AUC) 0.859 vs 0.588 for TinyMLP ($Delta$AUC = +0.271). On ERP time-series inputs, EEGNet achieved AUC = 0.640 and ShallowConvNet achieved AUC = 0.540, both inferior to the engineered-feature SVM baseline. In Experiment II, the best unimodal baseline was audio SVM-RBF (AUC = 0.753). Fusion achieved AUC to 0.762 and increased specificity (Spec) to 0.810 under the balanced objective, and increased recall (Rec) to 0.813 with a false-negative rate (FNR) of 0.188 under the screening objective.</p><p><strong>Significance: </strong>This study provides a leakage-controlled, strictly paired, subject-level evaluation framework for depression-assisted screening and shows that ERP-audio fusion offers objective-dependent complementary value.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207706","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":"Continuous Site-Specific Intravascular Monitoring of Arterial and Venous Blood Oxygenation In Vivo.","authors":"John Racadio, Gyula Gál, Gerald W Lucassen, Ross Schierling, Draženko Babić","doi":"10.1088/1361-6579/aeb59d","DOIUrl":"https://doi.org/10.1088/1361-6579/aeb59d","url":null,"abstract":"<p><strong>Objective: </strong>Conventional pulse oximetry provides continuous non-invasive arterial oxygen saturation, whereas arterial and venous blood gas analysis provides intermittent reference measurements. Neither modality continuously monitors saturation at a selected deep intravascular site. In this proof-of-concept feasibility study, we assessed whether intravascular diffuse reflectance spectroscopy tracks the direction and time course of prespecified arterial, central venous, and regional renal venous oxygenation changes, alongside conventional pulse oximetry where an arterial comparator was appropriate.&#xD;Approach. Three separate experimental protocols were performed in three pigs (one animal per protocol; n=1 per condition). Oxygen saturation was monitored with the iBLOS sensing wire in the abdominal aorta during apnea-induced systemic hypoxemia, in the inferior vena cava (IVC) during repeated hypoxic challenges, and in the right renal vein during transient venous outflow obstruction. Conventional pulse oximetry was recorded concurrently during the arterial and IVC protocols as an arterial monitoring comparator; no blood-gas samples were collected in these feasibility experiments.&#xD;Main results. Continuous intravascular blood oxygenation level monitoring detected rapid and dynamic arterial desaturation and reoxygenation during systemic apnea and demonstrated reproducible responses during repeated hypoxic challenges. Venous oxygenation measured in the inferior vena cava exhibited lower baseline oxygen saturation and slower desaturation-recovery kinetics than arterial measurements, reflecting physiological oxygen extraction and circulatory transit delays. During renal vein occlusion, oxygen saturation proximal to the obstruction progressively decreased toward near-complete oxygen depletion before rapidly recovering following restoration of venous outflow. These regional physiological measurements are not feasible using peripheral pulse oximetry. &#xD;Significance. This feasibility platform provides continuous, site-specific intravascular saturation trends in vascular territories that conventional non-invasive monitoring cannot directly sample. With validation against contemporaneous blood-gas measurements and evaluation in larger studies, it could help fill a monitoring gap during ischemia, reperfusion, and endovascular intervention.&#xD.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207655","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":"Continuous blood pressure and autonomic activity during road-traffic noise: a multimodal time-course analysis.","authors":"Tizian Dege, Jan Helders, Christian Laufs, Andreas Herweg, Christoph Hoog Antink","doi":"10.1088/1361-6579/aeb105","DOIUrl":"10.1088/1361-6579/aeb105","url":null,"abstract":"<p><p><i>Objective.</i>Noise-induced stress is a prominent risk to well-being. Despite its relevance to cardiovascular load, blood pressure (BP) is rarely used in noise studies, because conventional cuff-based measurements have low temporal resolution. Continuous non-invasive BP (cNIBP) enables beat-to-beat monitoring, resolving short-lived, phase-dependent dynamics (latency, peak response, recovery) averaged out in intermittent protocols. This work records a detailed timeline of the stress response to realistic road-traffic noise during a cognitively demanding task, evaluating cNIBP alongside established autonomic markers (electrodermal activity (EDA) and heart rate (HR)).<i>Approach.</i>An experimental study with 36 participantscombined a 2-back mental task with three noise conditions: road traffic noise at 58.12 and 52.12 dB(A) and ambient noise at 30.2 dB(A). Each test comprised a 60 s<i>Rest</i>, 120 s<i>Trial</i>, and 60 s<i>Recovery</i>phase. Systolic (SBP) and diastolic BP (DBP) and HR were monitored via cNIBP; EDA via skin conductance. Signals were split into 24 non-overlapping ten-second intervals and analysed with within-subject comparisons.<i>Main results.</i>Both SBP and DBP provided detailed information about the cardiovascular response. Unlike HR and EDA, which mainly reflected transient changes around stressor onset, cNIBP captured sustained elevations during the<i>Trial</i>and their decline during recovery, adding complementary information missed by common autonomic markers. HR also showed a pronounced order effect, with increased responses during the first block independent of noise condition, whereas blood-pressure trajectories were more robust.<i>Significance.</i>These findings show that cNIBP resolves the onset, persistence, and recovery of the cardiovascular response to road-traffic noise, information that intermittent cuff measurements and common autonomic markers miss.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113438","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":"KDM-Net: a large-kernel and bi-mamba integrated network for 12-lead atrial arrhythmia classification.","authors":"Yinghao Sun, Mujun Zang, Tong Liu, Shusen Zhou, Chanjuan Liu, Qingjun Wang","doi":"10.1088/1361-6579/aeb59f","DOIUrl":"https://doi.org/10.1088/1361-6579/aeb59f","url":null,"abstract":"<p><strong>Objective: </strong>Automatic recognition of atrial arrhythmias is important for early clinical screening and computer-aided diagnosis. Distinguishing atrial fibrillation from atrial flutter remains challenging because of their similar electrocardiographic manifestations and&#xD;high risk of misclassification. This study aimed to develop an effective model for atrial arrhythmia classification with improved multi-lead feature utilization, long-range temporal modeling, and cross-patient generalization.</p><p><strong>Approach: </strong>We propose KDM-Net, which takes&#xD;12-lead electrocardiogram signals as input. The network employs a large-kernel K module to enhance the perception of waveform morphology and rhythm patterns, a D module to recalibrate and fuse multi-lead features, and a bidirectional Mamba-based M module to&#xD;model long-range temporal dependencies. KDM-Net was evaluated on the combined CUSPH and PTB-XL dataset under an inter-patient protocol.</p><p><strong>Main results: </strong>In five-fold cross-validation, KDM-Net achieved an average accuracy and F1-score of 96.04% and&#xD;89.21%, respectively. On the independent patient-level test set, the accuracy and F1-score were 96.41% and 88.31%, respectively. On the CinC 2020 external test set, the model achieved an accuracy and F1-score of 91.14% and 80.41%, respectively. KDM-Net&#xD;outperformed several representative models in comparative experiments.</p><p><strong>Significance: </strong>KDM-Net effectively integrates multi-lead spatial information and long-range temporal dependencies, demonstrating strong recognition performance and promising cross-patient&#xD;generalization. It provides an effective solution for the intelligent diagnosis of atrial arrhythmias.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207658","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}