Physiological measurement最新文献

{"title":"Changes in calf skin temperature during ramp-incremental cycling exercise and their association with gas exchange and respiratory compensation thresholds.","authors":"Jose I Priego-Quesada, Nathan Mackay, Dami Adejuwon, Daniel A Keir","doi":"10.1088/1361-6579/ae8a10","DOIUrl":"10.1088/1361-6579/ae8a10","url":null,"abstract":"<p><p><i>Objective.</i>We tested the hypothesis that the oxygen uptake (O₂) associated with systematic changes in skin temperature (<i>T</i>_sk) during ramp-incremental exercise would coincide with the respiratory compensation point (RCP) and not the gas exchange threshold (GET).<i>Approach.</i>Thirty-eight healthy adults (16 females; 24 ± 5 years, body mass 73.0 ± 11.4 kg, height 174.8 ± 8.5 cm) completed a ramp-incremental exercise test on a cycle ergometer (20-45 W min^-1depending on self-reported aerobic fitness; selected to induce task disengagement within 10-15 min) in a climate-controlled laboratory. Throughout the protocol, ventilatory and gas exchange variables were acquired breath-by-breath using a metabolic cart and<i>T</i>_skof the posterior calf was recorded revolution-by-revolution using an infrared camera.<i>Main results.</i>The<i>T</i>_sk-time relationship exhibited either an abrupt or gradual deceleration as exercise time progressed. TheO₂associated with this change-point was identified visually or by finding the local maximum of the second derivative of a 6th-order polynomial fit to the data. TheO₂at GET and RCP were determined visually. Overall, theO₂at GET, RCP and<i>T</i>_skbreakpoint identified visually or modelled were 1884 ± 466, 2633 ± 747, 1969 ± 462, and 1769 ± 508 ml∙min^-1, respectively. Compared to theO₂at GET, higher values were reported when<i>T</i>_skbreakpoint was identified visually (<i>p</i>= 0.04, ESg = 0.3, 95%CI[1, 170 ml min^-1]) and lower by the second derivative (<i>p</i>< 0.01, ESg = 0.4, 95%CI[30, 199 ml min^-1]). Larger effect sizes were observed for RCP (visually:<i>p</i>< 0.001, ESg = 1.3, 95%CI[524, 803 ml min^-1]; second derivative:<i>p</i>< 0.001, ESg = 1.7, 95%CI[724, 1003 ml min^-1]). Intraclass correlation ofO₂between<i>T</i>_skand GET ranged from very good-to-excellent (0.67-0.92) but were not significant for RCP. For GET, mean absolute percentage error was 12.5% (95%CI: 9.4%-15.7%) and 14.5% (95%CI: 11.1%-17.9%) for the visual and second-derivative methods, respectively, and for RCP, 23.2% (95% CI: 18.6%-27.8%) and 31.4% (95% CI: 26.7%-36.2%).<i>Significance.</i>Findings suggest a statistical association between intensity-dependent changes in metabolism and the<i>T</i>_skresponse of the calf.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148437437","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":"Auxiliary-conditioned cross-attention with physiologically interpretable features for chagas disease detection from 12-lead ECGs.","authors":"Hyuno Im, Nahyun Lee, Taeyoung Kang, Taehwan Kim, Donggun Kim, Dongjae Lee, Seungsang Oh, Wuming Gong, Il-Youp Kwak","doi":"10.1088/1361-6579/ae8b72","DOIUrl":"10.1088/1361-6579/ae8b72","url":null,"abstract":"<p><p><i>Objective.</i>Chagas disease remains a major public-health concern in endemic regions, and chronic cardiac involvement often manifests as conduction abnormalities detectable on standard 12-lead electrocardiograms (ECGs). Reliable automated screening remains challenging because of dataset heterogeneity and label uncertainty, particularly when combining strongly labeled cohorts with large weakly labeled repositories.<i>Approach.</i>We propose a hybrid architecture that integrates a 1D ResNet encoder for local ECG morphology, a bidirectional GRU for long-range temporal context, and handcrafted physiological features and demographics through an auxiliary-conditioned cross-attention module. The auxiliary vector, comprising age, sex, and QRS/conduction descriptors, is projected into a query token that selectively attends to deep sequential embeddings for feature-aware temporal aggregation. To exploit heterogeneous sources while reflecting source reliability, we further adopt a source-aware weighted binary cross-entropy objective.<i>Main results.</i>As team CAUETUMN in the PhysioNet/Computing in Cardiology Challenge 2025, the framework achieved a score of 0.347 on the organizer-held REDS-II leaderboard-validation set during the official phase and 0.218 on the final hidden test set, ranking 17th among 41 eligible teams.<i>Significance.</i>These results suggest that conditioning detection on interpretable QRS and conduction descriptors supports a transparent and physiologically informed screening framework, while highlighting the difficulty of generalizing across heterogeneous cohorts.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148456429","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 beat-to-beat blood pressure estimation using a multi-modal wearable deep learning approach.","authors":"Qiao Li, Zichao Shen, Mohamed Almadi, Ye Yang, Ning Zhang, Jacqueline Gong, Gary Strangman, Ting Xiang, Yuanting Zhang, Gari D Clifford, Quan Zhang","doi":"10.1088/1361-6579/ae85b4","DOIUrl":"10.1088/1361-6579/ae85b4","url":null,"abstract":"<p><p><i>Objective.</i>Cuffless blood pressure (BP) monitoring technologies, primarily based on pulse transit time (PTT) or photoplethysmography (PPG), frequently suffer from calibration drift due to their reliance on blood volume surrogates rather than direct pressure measurement. To address this physiological limitation, this study presents a multi-modal deep learning framework that integrates superficial temporal artery tonometry (STAT), which captures high-fidelity pressure waveform morphology, with electrocardiography (ECG) and PPG signals.<i>Approach.</i>A custom wearable device was developed to simultaneously acquire these signals during dynamic perturbations. Extracted features included heart rate from ECG, PTT from ECG-PPG pairs, and BP-related metrics derived from PTT and STAT. Signal quality indices for ECG, PPG, and STAT signals were also computed to assess signal reliability. A temporal convolutional network (TCN) model was designed to capture the complex, non-linear dependencies between these multi-modal features and beat-to-beat BP.<i>Main results.</i>The approach was rigorously validated using leave-one-subject-out cross-validation on 29 recordings from ten healthy volunteers undergoing isometric handgrip exercises. The proposed TCN model significantly outperformed traditional PTT and STAT-only baselines, achieving a mean absolute difference of 5.58 mmHg for systolic BP , 4.39 mmHg for mean BP and 4.34 mmHg for diastolic BP. Notably, the TCN model exhibited significantly lower errors (<i>p</i>  0.05, Wilcoxon Test) during dynamic BP fluctuations compared to baseline models.<i>Significance.</i>The study demonstrates that fusing tonometry-derived pressure morphology with hemodynamic timing features effectively mitigates the limitations of conventional PTT methods. This approach offers a robust solution for continuous, calibration-resilient BP estimation.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13402944/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148376697","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":"Dual warm-start fusion versus attention-based fusion in low-label ECG-PCG classification: a controlled ablation study.","authors":"Erkan Kıymık","doi":"10.1088/1361-6579/ae85b7","DOIUrl":"10.1088/1361-6579/ae85b7","url":null,"abstract":"<p><p><i>Objective.</i>Multimodal electrocardiography-phonocardiography (ECG-PCG) learning is promising for cardiac screening, but it remains unclear whether its gains are driven mainly by complex fusion architectures or by well-initialized modality-specific encoders. This study examined the relative contribution of warm-start initialization and fusion complexity in low-label ECG-PCG classification.<i>Approach</i>. A controlled ablation study was performed using synchronized recordings from the PhysioNet/CinC 2016 Training-A subset. ECG-only, PCG-only, cold-start fusion, single warm-start fusion, dual warm-start fusion, attention fusion, and gated-attention fusion models were evaluated across 5%, 10%, 25%, 50 %, and 100% paired-label ratios under matched training protocols. Robustness was further assessed using alternative PCG warm-start sources.<i>Main results</i>. Dual warm-start fusion numerically outperformed cold-start fusion across all label budgets, with AUROC gains up to +0.050 and statistically significant improvements at four of five label ratios. In contrast, attention and gated-attention fusion provided no statistically reliable advantage over simple dual warm-start concatenation and became inferior at higher label ratios despite added complexity. Multimodal gains over the strongest single modality were label-dependent, being largest at intermediate label ratios and negligible at full supervision. Additional frozen-encoder and pre-classifier feature-space analyses showed that end-to-end fine-tuning was preferable to encoder freezing, and that attention altered latent geometry without translating into superior diagnostic discrimination.<i>Significance</i>. The findings indicate that, in label-limited ECG-PCG classification, modality-specific encoder warm-starting is a more reliable performance driver than additional fusion complexity. These results support label-budget-aware evaluation of multimodal physiological signal models before adopting more complex fusion modules.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148376659","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":"Augmenting single-lead ECG interpretation through QRS waveform decomposition and rotation.","authors":"W Brian Chiu, Faisal Amlani, Derek G Rinderknecht","doi":"10.1088/1361-6579/ae85b3","DOIUrl":"10.1088/1361-6579/ae85b3","url":null,"abstract":"<p><p><i>Objective</i>. The single-lead electrocardiogram (ECG) is widely used in watches and other wearable devices, with proven efficacy in cardiac rhythm interpretation. However, for morphological ECG interpretation, multiple viewpoints (leads) are generally necessary.<i>Approach</i>. This contribution introduces a novel methodology to rotate the QRS waveform of a single-lead ECG for estimating QRSs of different viewpoints that may be more favorable for morphological interpretation. This rotation can be achieved by recognizing that the three-dimensional QRS loop is approximately planar, and that the shape of any one-dimensional projection of a planar loop can be determined entirely by its component on the QRS plane. In particular, this methodology models a single-lead QRS as a composition of an 'intrinsic component' specific to the individual and an 'angular component' represented as a simple sinusoid defined by the 'phase' of the QRS along the continuum between monophasic and biphasic waveforms. Indeed, for any single-lead QRS of an arbitrary viewpoint on the QRS plane, its phase can be computed based on its isoelectric zero-crossing(s). Rotation of a QRS to a different (target) viewpoint can then be achieved by substitution of the angular component of the QRS with the angular component of the target phase.<i>Main results</i>. The performance of this methodology is assessed in this work with the large PhysioNet PTB-XL database, as a proof-of-concept application, where single-lead QRS complexes and their respective monophasic rotations are evaluated for single-lead prediction of human-annotated 12-lead ECG interpretation of left bundle branch block. Results forsingle-lead predictions of left bundle branch block via incorporating QRS rotation demonstrate again in positive predictive value and again in1 score for corresponding sensitivities of at least.<i>Significance</i>. Towards facilitating morphological interpretation, the QRS waveform of a single-lead ECG can be augmented to provide more favorable viewpoints of its QRS complex.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148376648","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":"Inter-patient multi-label ECG classification via low-rank adaptation fine-tuned large language models with dynamic graph convolutional network.","authors":"Yuhao Cheng, Lirong Wang","doi":"10.1088/1361-6579/ae85b6","DOIUrl":"10.1088/1361-6579/ae85b6","url":null,"abstract":"<p><p><i>Objective.</i>Electrocardiogram analysis is vital for cardiovascular diagnosis, yet traditional methods struggle with inter-patient variability and complex multi label correlations. Existing large language model (LLM) integrations often freeze internal parameters, which limits adaptation to idiosyncratic signal patterns across diverse subjects.<i>Approach.</i>To overcome these challenges, this study proposes a framework that integrates LLMs fine-tuned via low rank adaptation (LoRA) with a multi-label dynamic graph convolutional network. The application of LoRA allows the model to encode specific signal features and mitigate inter-patient variability while retaining essential clinical semantic knowledge. Furthermore, the dynamic graph convolutional module is designed to capture the complex correlations between diverse cardiac diseases, thereby enhancing the modeling of multi-label dependencies. The final inference strategy leverages refined semantic embeddings to achieve accurate classification of diagnostic categories without requiring extensive labeled training data for every new patient population.<i>Main results.</i>Experimental results on the PTB-XL dataset yield<i>F</i>1-scores of 0.781 for the five class task and 0.370 for the twenty class task, representing improvements of 12.4% and 12.9% respectively compared to state of the art methods. Evaluation on the CPSC2018 dataset further confirms robust cross-dataset generalization with an<i>F</i>1-score of 0.606, which corresponds to an 18.8% relative improvement over existing approaches.<i>Significance.</i>By effectively resolving inter patient variability and modeling disease correlations, the proposed framework provides a scalable and accurate solution for diagnosing cardiac conditions in complex clinical environments where annotated data is limited.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148376653","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":"Respiratory event type and duration modulate PPG waveforms in OSA.","authors":"Jutta Nurminen, Salla Hietakoste, Timothy Howarth, Brett Duce, Timo Leppänen, Teemu Laitinen, Antti Kulkas, Samu Kainulainen","doi":"10.1088/1361-6579/ae7feb","DOIUrl":"10.1088/1361-6579/ae7feb","url":null,"abstract":"<p><p><i>Objective.</i>Obstructive sleep apnea (OSA) increases circulatory system load and risk of cardiovascular diseases (CVDs). Despite being biomarkers of vascular health, photoplethysmography (PPG) signal waveforms have not been systematically investigated in patients with OSA. Thus, we aimed to study the immediate effects of respiratory event characteristics on PPG waveforms and to examine potential patterns that could be associated with cardiovascular health.<i>Approach.</i>We retrospectively analyzed 520 clinical polysomnographies from suspected OSA patients, focusing on three PPG signal segments: 10 s before, during, and 10 s after respiratory events (<i>n</i>= 14442 in each segment). We determined PPG waveform parameters (full width at half maximum (FWHM) as well as differences in absolute and relative time (Δ<i>t</i>, Δ<i>t</i>_rel) and amplitude (Δ<i>A</i>, and Δ<i>A</i>_rel) between systolic peak and dicrotic notch) within each segment and tested the effect of respiratory event type (apnea vs hypopnea) and duration (10-20 s, 20-30 s, ⩾30 s).<i>Main results.</i>Before and during respiratory events, longer respiratory events significantly (<i>p</i>< 0.001) increased Δ<i>A</i>_reland FWHM, and decreased Δ<i>A</i>and Δ<i>t</i>_rel. These findings were significantly (<i>p</i>< 0.001) more pronounced during apneas than hypopneas. After the events, all PPG waveform parameters fluctuated strongly. Moreover, the type and duration of the respiratory event, pre-event values of PPG parameters, and heart rate were significantly (<i>p</i>< 0.001) associated with changes in the parameter values during the event.<i>Significance.</i>By analyzing PPG characteristics, we could enhance the evaluation of physiological stress caused by respiratory events in patients with OSA and therefore provide tools for the risk assessment of CVDs.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148284056","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 bronchopulmonary dysplasia in infants and prediction of school-age lung function from tidal breathing data using recurrent neural networks.","authors":"Abdessamad Falhi, Malena Gwerder, Céline Rüttimann, Urs Frey, Edgar Delgado-Eckert","doi":"10.1088/1361-6579/ae85b1","DOIUrl":"https://doi.org/10.1088/1361-6579/ae85b1","url":null,"abstract":"<p><p><i>Objective.</i>To test whether machine learning (ML) models trained on tidal breathing flow time series can discriminate between individuals with and without respiratory disease and predict lung function indices obtained from conventional pulmonary function testing.<i>Background.</i>accurate assessment of respiratory function in infants and young children is challenging because conventional pulmonary function testing requires sophisticated equipment and/or active patient cooperation. Tidal breathing measurements, in contrast, can be obtained non-invasively with little or no patient cooperation and at low cost, yet their clinical utility has been limited. We hypothesized that sufficiently long tidal breathing flow time series contain clinically relevant information that can be extracted using a recurrent neural network known as a long short-term memory (LSTM) network.<i>Approach.</i>We evaluated LSTM models in two scenarios within the Basel-Bern Infant Lung Development cohort. First, we assessed the ability of a model trained on flow and derived volume time series to detect bronchopulmonary dysplasia (BPD) in 329 infants. Second, we examined whether a model trained on tidal breathing flow alone could predict forced expiratory volume in one second (FEV₁) in 135 school-age children. Signals were filtered and normalized prior to model training, and performance was evaluated on held-out test datasets.<i>Main results.</i>For BPD detection, the model achieved 97.0% accuracy, 100% specificity, 91.7% sensitivity, 100% precision, and an F1-score of 95.7%. For FEV₁prediction, Bland-Altman analysis showed a mean bias of -0.009 l (95% CI -0.091-0.074), with limits of agreement of -0.416 l and 0.399 l. The mean relative prediction error was 13.7%.<i>Significance.</i>These findings demonstrate that temporal patterns in tidal breathing flow signals contain diagnostically and functionally relevant information. ML applied to tidal breathing measurements may provide a low-burden, minimal-cooperation approach for early respiratory disease detection and functional assessment across early life stages.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"47 7","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148456441","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 changes in hand height alter absorbance, but not pulsation, in the finger pulse plethysmograph.","authors":"Onur Howie, Jamie R K Marland, Ralph Shackleton, Gordon Drummond","doi":"10.1088/1361-6579/ae7f7a","DOIUrl":"10.1088/1361-6579/ae7f7a","url":null,"abstract":"<p><p><i>Objective.</i>Previous studies of finger pulse plethysmography have used large changes in finger height to assess how pressure influences light transmission. Light transmission is affected by pulsation transmitted from the arterial pressure, and also by the volume of blood held in the finger vasculature. Smaller changes of hand height, in relation to the neck, could elucidate more precisely the pressures and mechanisms associated with vascular volume changes.<i>Approach.</i>We studied 18 (15 male, 3 female) healthy young volunteers in warm quiet surroundings, with one arm supported horizontally at the level of the shoulder. Comparisons were made with the hand placed 5 cm above and 5 cm below the horizontal, in random sequence. Red and infrared transmission were recorded from a standard pulse oximeter finger probe. Sections of recording were chosen where short periods of vasoconstriction were absent. Total absorbance values at peak and trough, and absorbance pulse amplitude, were calculated. We compared measures in the two hand positions, and before and after inflation of a cuff at the wrist, within each subject.<i>Main results.</i>In the dependent position, infrared light absorbances were greater: peak, 0.054 (0.043, 0.070) and trough (0.053 (0.045, 0.069) (median, quartiles) (<i>P</i>< 0.0001). Pulse amplitude was unaffected. Cuff inflation had no effect on the peak and trough values, but pulse amplitude decreased: the difference between paired values for infrared was 0.0049 (0.0075, 0.0015) and red, 0.0030 (0.0043, 0.0010) (median paired difference, 95% confidence limits). (<i>P</i>< 0.005).<i>Significance.</i>The minimal effect of cuff venous obstruction supports previous work reporting flow limitation in venous drainage of the arm. Our observations suggest that an increase in filling pressure caused by lowering the hand by 10 cm increases overall blood volume in the finger, suggesting that the plethysmograph waveform may result from pressure changes much less than arterial.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148278359","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 tracking of aortic aneurysm diameter with peripheral pulse waves: a computational framework combining sequential Markov chain Monte Carlo with Kalman filtering.","authors":"Kiran Bhattacharyya","doi":"10.1088/1361-6579/ae85b5","DOIUrl":"10.1088/1361-6579/ae85b5","url":null,"abstract":"<p><p><i>Objective.</i>Abdominal aortic aneurysms (AAA) affect more than 1% of adults over 50 and carry significant mortality risk. Current surveillance relies on intermittent imaging (ultrasound or MRI) at 6-24 month intervals, which may miss rapid growth acceleration between visits. We investigate the feasibility of continuous aneurysm diameter tracking using peripheral pulse waves, like those detected by photoplethysmography (PPG) devices.<i>Approach.</i>We use a simplified one-dimensional (1D) hemodynamic model that simulates pulse wave propagation from the heart to the pedal digital artery. We first demonstrate diameter estimation when the hemodynamic model parameters defining systemic circulation are known within bounds for an individual, aggregating thousands of observations over hours or days. We then address the more challenging scenario where systemic parameters are only known to be within wider population-level bounds, using a sequential Monte Carlo approach that combines an ensemble Markov chain Monte Carlo (MCMC) sampler with Kalman filtering to marginalise over unknown parameters while tracking the aneurysm diameter. Both approaches are evaluated through 12 month tracking simulations of virtual patients with constant and accelerating aneurysm growth.<i>Main results.</i>While single-observation diameter estimation is fundamentally limited by noise and confounding variables, aggregating 1 600 measurements under baseline noise conditions reduces diameter uncertainty to 0.8 mm when patient-specific hemodynamic parameters are known within bounds. In this setting, tracking simulations across eight virtual patients achieve average root-mean-square error (RMSE) of0.3 mm. When systemic parameters are known only within population-level bounds, joint Bayesian estimation over the full parameter space achieves a median RMSE of 0.65 mm (1.40.3 mm, meanstandard error) across 50 virtual patients, remaining within clinically relevant ranges despite the underlying parameters being only partially identifiable.<i>Significance.</i>These computational results suggest that peripheral pulse wave monitoring through PPG sensors could complement traditional imaging for AAA, potentially enabling earlier detection of growth and more timely intervention.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148376732","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}