Cardiovascular Engineering and Technology最新文献

{"title":"Discriminating Breast Cancer Patients by Spectral Analysis of Arterial Pulse Waveforms.","authors":"Chao-Tsung Chen, Ting-Wei Yeh, Yi-Sheng Chou, Chi-Feng Cheng, Yi-Hsuan Lai, Chung-Hua Hsu, Hsin Hsiu","doi":"10.1007/s13239-026-00842-0","DOIUrl":"https://doi.org/10.1007/s13239-026-00842-0","url":null,"abstract":"<p><strong>Background/aim: </strong>Breast cancer (BC) remains a major health threat, highlighting the need for accessible screening. Characteristics of the cardiovascular system can be altered in BC patients. This study explored a noninvasive method combining arterial pulse-waveform analysis and classification to compare arterial pulse-waveform characteristics between BC patients (n = 51)) and age-matched controls (n = 76)).</p><p><strong>Methods: </strong>From one-minute radial waveform recordings, 40 harmonic indices (amplitude proportions, phase angles, and their variability) were derived. Significant differences in pulse-waveform indices were observed between groups, suggesting altered pulse-wave transmission conditions in BC patients. Two classifiers were compared: machine learning and a novel pulse-distribution analysis (PDA).</p><p><strong>Results: </strong>PDA demonstrated an acceptable discrimination with an AUC of 0.74, outperforming machine learning (AUC up to 0.58). Subgroup analysis by clinical factors such as TNM stage showed variable performance, with AUCs ranging from 0.66-0.93. Discrimination appeared to improve with disease progression (AUC 0.86 for stage IV), suggesting that tumor-induced vascular alterations may affect pulse-wave transmission.</p><p><strong>Conclusion: </strong>The primary contribution of this work is the identification of distinct pulse-waveform signatures in BC patients, providing a physiological basis for future development of noninvasive screening tools. The proposed method, characterized by its low cost and ease of use, warrants further validation in larger cohorts.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147977347","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 Multi-Surface Microelectrode Catheter for Targeted Energy Delivery in Cardiac Radiofrequency Ablation: A Proof of Concept Based on Computational Simulation.","authors":"Yuqi Wu, Xingkai Ji, Tong Ren, Xiaomei Wu, Shengjie Yan","doi":"10.1007/s13239-025-00818-6","DOIUrl":"10.1007/s13239-025-00818-6","url":null,"abstract":"<p><strong>Purpose: </strong>Inefficient energy delivery to blood remains a primary challenge in cardiac radiofrequency ablation (RFA), limiting procedural efficacy. This paper introduces and computationally validates a novel multi-surface microelectrode catheter (MSMC) designed to enhance targeted energy delivery and improve overall procedural efficiency.</p><p><strong>Methods: </strong>A 3D multiphysics computational model coupling electrical, thermal, fluid-dynamic, and mechanical fields was developed to simulate RFA. The performance of the MSMC was systematically compared against a traditional catheter by analyzing its energy distribution and thermal lesion characteristics under both standard (10-18 W vs. 30 W) and high-power short-duration (25 W vs. 60 W) protocols, assessing the impact of varying catheter angles (vertical, 45°, and parallel), and exploring its potential for real-time lesion monitoring via impedance analysis.</p><p><strong>Results: </strong>The MSMC directed over 75% of its energy to the myocardium, a threefold improvement over the traditional catheter (~22%), allowing the creation of comparable lesions with 40% less power. The design demonstrated high stability across different orientations. Furthermore, analysis of its impedance characteristics via Cole-Cole plots revealed a greater sensitivity for real-time lesion monitoring compared to the traditional catheter.</p><p><strong>Conclusions: </strong>The MSMC's design, which synergizes a multi-surface electrode structure with a contact-based discharge strategy, enables more efficient and predictable lesion formation. This computational proof-of-concept study confirms its potential to improve the safety, efficacy, and real-time control of RFA procedures, offering a promising pathway for the development of next-generation therapeutic devices.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"206-222"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145968053","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":"ECG and PPG Signals-Based Premature Ventricular Contraction Detection Methods: A Review, Key Challenges, and Future Directions.","authors":"Shailesh Mohine, Nabasmita Phukan, M Sabarimalai Manikandan, Ram Bilas Pachori","doi":"10.1007/s13239-026-00819-z","DOIUrl":"10.1007/s13239-026-00819-z","url":null,"abstract":"<p><p>Premature ventricular contraction (PVC) is a common cardiac arrhythmia, and its timely and automated detection is crucial for preventing life-threatening cardiovascular events and reducing clinical workload in long-term monitoring. This paper reviews state-of-the-art PVC detection methods based on electrocardiogram (ECG) and photoplethysmogram (PPG) signals, employing signal processing techniques, traditional machine learning, and deep learning approaches. The existing methods are categorized into three groups: threshold-based or heuristic-based techniques, conventional machine learning models, and deep learning frameworks. Additionally, the paper provides an overview of ECG and PPG signal databases and the benchmark metrics used for performance evaluation. Given that most methods utilize R-peak and systolic peak detection during preprocessing, we also review various preprocessing techniques for detecting R-peaks in ECG signals and systolic peaks in PPG signals. Based on the performance and key contributions of existing PVC detection methods, we highlight major challenges and future directions, considering the presence of various noise sources in ECG and PPG signals-particularly under ambulatory and exercise conditions-and the resource constraints of wearable or portable long-term ECG and/or PPG monitoring devices.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"119-139"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115197","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":"Coronary CT Angiography-Based Prediction Model for Hemodynamically Significant Coronary Stenosis Integrating Morphological and Plaque Characteristics.","authors":"Chenxi Wang, Shuang Leng, Ru-San Tan, Ping Chai, Jiang Ming Fam, Adrian Fatt Hoe Low, Lohendran Baskaran, Lynette Teo, Felix Yung Jih Keng, Chee Yang Chin, Ching Ching Ong, John C Allen, Mark Yan-Yee Chan, Aaron Sung Lung Wong, Terrance Chua, Swee Yaw Tan, Soo Teik Lim, Liang Zhong","doi":"10.1007/s13239-026-00831-3","DOIUrl":"10.1007/s13239-026-00831-3","url":null,"abstract":"<p><strong>Purpose: </strong>A rising trend involves the application of machine learning to coronary computed tomography angiography (CCTA) for predicting physiological significance of coronary lesions. This study aimed to formulate a clinical model using CCTA-derived features and the least absolute shrinkage and selection operator (LASSO) regression method to predict hemodynamically significant coronary stenosis.</p><p><strong>Methods: </strong>The study population comprised individuals prospectively recruited from two tertiary medical centres with suspected or known coronary artery disease. The model was developed using patients from Centre 1 and independently validated in patients from Centre 2. All participants underwent CCTA followed by invasive coronary angiography with fractional flow reserve (FFR) measurements. The LASSO model incorporated coronary morphological and plaque features derived semi-automatically from CCTA, along with clinical and demographic variables, as input predictors. Model performance was assessed against the reference standard of invasive FFR ≤ 0.80.</p><p><strong>Results: </strong>The analysis included 210 diseased vessels from 133 patients-141 vessels from 84 patients in Centre 1 (development cohort) and 69 vessels from 49 patients in Centre 2 (validation cohort). Using the LASSO algorithm, nine predictive variables were selected from an initial set of 33 candidate features: heart rate, minimal lumen diameter (MLD), area stenosis, diameter stenosis ≥ 50%, lesion length/MLD⁴, necrotic core plaque volume, lesion entrance angle, remodeling index, and vessel-specific calcium score. In the validation cohort, the LASSO model demonstrated strong diagnostic performance at both vessel and patient levels. Per-vessel accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 93%, 86%, 98%, 96%, and 91%, respectively. Comparable performance was observed at the per-patient level, with corresponding values of 92%, 89%, 95%, 96%, and 88%, respectively. The area under the receiver operating characteristic curve (AUC) for the LASSO model at the vessel level was 0.950, significantly higher than that of CT-derived FFR (AUC = 0.857, P = 0.046) and diameter stenosis ≥ 50% (AUC = 0.641, P < 0.0001).</p><p><strong>Conclusions: </strong>A prediction model integrating coronary and plaque parameters outperformed existing CCTA-based methods in identifying hemodynamically significant coronary stenosis, offering improved accuracy for ischemia detection.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"175-187"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147596213","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":"Filling Fraction and Single Beat Method for Estimating Dead-Space Volume of Left Ventricle.","authors":"Melanie P Hager, George V Letsou, John C Criscione","doi":"10.1007/s13239-025-00809-7","DOIUrl":"10.1007/s13239-025-00809-7","url":null,"abstract":"<p><p>Accurate assessment of cardiac preload remains a clinical challenge, particularly in heart failure patients where preload manipulation is impractical or contraindicated. Ejection fraction (EF), while widely used, reflects a combination of preload, contractility, and afterload, and may obscure the specific contribution of preload. Inspired by a preload recruitable stroke work (PRSW) model for heart function, a concise, three factor expression for ejection fraction (EF) can be obtained where EF is directly proportional to preload, directly proportional to contractility, and inversely proportional to afterload. The contractility and afterload factors are common metrics; whereas the preload factor, filling fraction (FF), is a novel, dimensionless preload metric that sets a physiologic upperbound on EF. Unfortunately, FF measurement requires an estimate of the volume intercept or dead-space volume of the left ventricle, and such a measure has, conventionally, required preload manipulation with extrapolation to the volume axis. To address this, we propose a single-beat extrapolation method for estimating the volume intercept using end-diastolic and end-systolic measurements. In-silico testing across 10,000 synthetic left ventricular geometries demonstrates strong agreement between the estimated intercept and actual, prescribed dead-space volumes. This method enables non-invasive computation of FF from single-beat data without the need for in vivo preload manipulation. Potential clinical applications include characterizing cardiac function, stratifying heart failure subtypes, and enhancing diagnostic precision when EF is preserved but preload reserve is impaired. Future validation in clinical imaging datasets is warranted to assess real-world applicability.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"237-247"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13102796/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147345621","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":"Synthetic, Population-Based Virtual Patient Database Using a Digital Twin of the Cardiovascular System.","authors":"Richárd Wéber, Márta Viharos, Benjamin Csippa, Dániel Gyürki, György Paál","doi":"10.1007/s13239-026-00822-4","DOIUrl":"10.1007/s13239-026-00822-4","url":null,"abstract":"<p><strong>Purpose: </strong>The goal is to develop a cardiovascular virtual patient database (VPD) combining physiological and demographic data to provide the foundation for future applications in medical diagnostics, decision-making, credibility testing, and formal uncertainty analysis, and to enable its integration with three-dimensional (3D) hemodynamic models and to train neural networks.</p><p><strong>Methods: </strong>We generate an initial VPD by treating input parameters of a low-dimensional cardiovascular model as stochastic variables. Literature data and sensitivity analysis ensured physiological plausibility, while resampling improved physiological accuracy. Key physiological quantities are included such as systolic and diastolic aortic pressure, radial and carotid pressure, cardiac output, and diagnostic pulse wave velocities. Demographic factors (sex and age) are assigned based on their physiological impact. The open-source hemodynamic solver, first_blood, ensures accuracy and low computational time.</p><p><strong>Results: </strong>The initial VPD consists of 50,000 Virtual Patients; after resampling, 34,347 remain in the final VPD. The difference of diastolic and systolic aortic pressures between the VPD ( <math><mrow><mn>70.24</mn> <mo>±</mo> <mn>14.3</mn></mrow> </math> and <math><mrow><mn>116.8</mn> <mo>±</mo> <mn>16.11</mn></mrow> </math> mmHg) and the literature ( <math><mrow><mn>75.6</mn> <mo>±</mo> <mn>12.7</mn></mrow> </math> and <math><mrow><mn>113.0</mn> <mo>±</mo> <mn>11.2</mn></mrow> </math> mmHg) is low. The differences caused by the sex of the patient are reproduced well by the VPD: increased diastolic aortic pressure for males ( <math><mrow><mn>72.1</mn> <mo>±</mo> <mn>12.6</mn></mrow> </math> and <math><mrow><mn>68.5</mn> <mo>±</mo> <mn>15.4</mn></mrow> </math> for males and females respectively). The VPD also accurately includes higher pulse wave velocities with age, patients below year 30 have <math><mrow><mn>6.3</mn> <mo>±</mo> <mn>0.5</mn></mrow> </math> and above 70 have <math><mrow><mn>8.8</mn> <mo>±</mo> <mn>1.2</mn></mrow> </math> m/s with a linear increment in-between.</p><p><strong>Conclusions: </strong>The proposed methodology and first_blood solver effectively generate physiologically realistic virtual patient waveforms and demographic variability, providing a robust database for 3D cardiovascular simulations, machine-learning training datasets, and potential clinical decision support applications.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"188-205"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13102896/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146183393","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":"Image-Based Medical Navigation Systems for Cardiac Interventions: Recent Technological Advances.","authors":"Luís C N Barbosa, João L Vilaça, Siobhán Moane, Pedro Morais","doi":"10.1007/s13239-026-00830-4","DOIUrl":"10.1007/s13239-026-00830-4","url":null,"abstract":"<p><strong>Background: </strong>The application of catheter-based treatments for a growing range of structural heart diseases (SHD) has significantly increased over the past five years, driven by technological advances in medical navigation systems, particularly those based on medical imaging. Multimodal cardiac imaging plays a crucial role in these systems by combining complementary anatomical, morphological, and functional information, thereby increasing diagnostic accuracy and improving the effectiveness of cardiovascular interventions and clinical outcomes. However, multimodal imaging poses challenges, including intermodality misalignment and the need to determine optimal integration methods for data from different imaging modalities.</p><p><strong>Methods: </strong>This article reviews the state-of-the-art image-based medical navigation systems used in catheter-based cardiac procedures. The review covers the period from 2019 to 2023 and includes a total of 44 articles. The methodologies in these studies are grouped into six main categories: Image Enhancement and Tracking, Image Fusion and Reconstruction, 3D Modeling/Printing, Extended Reality, and Artificial Intelligence (AI).</p><p><strong>Results: </strong>Most studies involve multimodality imaging, combining or transferring information across different modalities. The review emphasizes that current multimodal imaging techniques enhance the accuracy of procedures such as left atrial appendage closure (LAAC), transcatheter aortic valve implantation (TAVI), and catheter ablation therapy. These techniques rely on combinations of imaging modalities such as fluoroscopy, ultrasound, and computed tomography (CT) to enable real-time guidance and precise navigation during minimally invasive interventions.</p><p><strong>Conclusion: </strong>By integrating data from multiple sources, these systems improve diagnostic reliability and procedural success, meeting the complex demands of SHD treatment. Despite advances, real-time surgical guidance remains a major challenge, underscoring the need for continued research in this area.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"99-118"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13102890/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147582753","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":"Deep Learning Based Approach for Lossless ECG Compression.","authors":"Anumita Mitra, Palash Kundu, Rajarshi Gupta","doi":"10.1007/s13239-026-00821-5","DOIUrl":"10.1007/s13239-026-00821-5","url":null,"abstract":"<p><strong>Objective: </strong>Tele-monitoring is a useful platform for remote monitoring of cardiac patients, where compression plays a significant role in reducing the link burden and memory utilization of the source device. This paper describes a new approach for lossless ECG compression based on a deep-learning method via an adaptive autoregressive integrated moving average (ARIMA) model.</p><p><strong>Methods: </strong>Raw ECG signals were denoised and preprocessed to generate beat-cells for further processing. The ARIMA model uses the individual cardiac cycles to generate model parameters, which are then compressed. In this research, the optimal model hyperparameters were predicted by a deep autoencoder followed by a multilayer perceptron neural network (MLPNN) regressor combination. The predictor was tuned offline via particle swarm optimization (PSO), which produced the reference data for MLPNN tuning.</p><p><strong>Results: </strong>The technique uses 46 records of mitdb under PhysioNet, including 10 major abnormal beats: H, A, V, P, L, R, a, f, F and j. Because of the adaptive nature, compression quality is high with negligible loss. No deviations in the clinical features of the reconstructed beats are found. The mean CR and PRD% values were 41.51 and 0.209%, respectively, which are superior to those reported in published research on ECG compression.</p><p><strong>Conclusion: </strong>The proposed adaptive ECG compression model can be useful for real-time telemonitoring applications, efficient storage and transmission of streamlined data of critical patients under continuous monitoring.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"155-174"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147318781","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":"Chordae Rupture Alters Tricuspid Valve Leaflet Biomechanics.","authors":"Julia Clarin, Keyvan A Khoiy, Samuel D Salinas, Dipankar Biswas, Kourosh T Asgarian, Francis Loth, Rouzbeh Amini","doi":"10.1007/s13239-025-00815-9","DOIUrl":"10.1007/s13239-025-00815-9","url":null,"abstract":"<p><strong>Purpose: </strong>Tricuspid valve chordae tendineae rupture is a valvular lesion that is often overlooked, though is postulated to be more prevalent than currently known. We examined the hemodynamics and biomechanical response of the tricuspid valve leaflets following chordae rupture to understand how acute changes in the post-rupture mechanical environment may contribute to long-term remodeling responses.</p><p><strong>Methods: </strong>Porcine valve leaflet deformation was studied in an intact heart in an ex vivo setup using sonomicrometry techniques before and after chordae rupture, which was induced by severing a chordae bundle connected to the septal leaflet.</p><p><strong>Results: </strong>Following chordae rupture, pulmonary artery pressure dropped approximately 5 mmHg ( <math><mrow><mi>p</mi> <mo>=</mo> <mn>0.048</mn></mrow> </math> ), indicating that valvular regurgitation occurred immediately after rupture. Mean maximum principal stretch of the septal leaflet increased 12% after rupture ( <math><mrow><mi>p</mi> <mo>=</mo> <mn>0.006</mn></mrow> </math> ).</p><p><strong>Conclusion: </strong>The immediate changes in post-rupture septal leaflet stretches show that chordae tendineae rupture acutely alters the biomechanical environment of the tricuspid valve, which may result in chronic tissue remodeling responses. The tricuspid valve is one of the four valves in the heart. Rupture of supporting structures of the tricuspid valve leaflet, known as chordae tendineae, may be more common than previously thought. In this study, we used excised pig hearts to examine how chordae rupture affects valvular function. With our experimental beating heart system, we pumped fluid through the hearts under realistic conditions and measured changes in pressure and leaflet motion before and after chordae rupture. After rupture, we observed a change in pressures and leaflet motion, causing the valve to leak and become less efficient. These changes may influence how the valve functions over time.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"223-236"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13102865/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907408","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":"Robust Design of Nonlinear Adaptive Hammerstein Filter Structure Using Evolutionary Algorithm: Real-Time Application to ECG Signals.","authors":"Shubham Yadav, Suman Kumar Saha, Rajib Kar","doi":"10.1007/s13239-025-00814-w","DOIUrl":"10.1007/s13239-025-00814-w","url":null,"abstract":"<p><strong>Objective: </strong>Electrocardiogram (ECG) signals are well-known non-stationary heart signals of lower strength. Due to their small amplitude, it attracts other biomedical artefacts from the surrounding. This research mainly focuses on removing artefacts from the electrocardiogram signals.</p><p><strong>Method: </strong>The work presented uses the recent metaheuristic techniques to design a nonlinear adaptive Hammerstein filter-based structure efficiently. Many powerful metaheuristic optimisation algorithms, such as particle swarm optimisation algorithm with constriction factor, flower pollination algorithm, marine predators' algorithm and growth optimiser, have been applied for the optimal design of adaptive Hammerstein filter-based structures. The proposed structure has been analysed for electrocardiogram with various noise signals such as muscle artefact, white Gaussian noise etc. RESULTS: Among the adopted-metaheuristic algorithms applied to adaptive Hammerstein filter-based structures, the growth optimiser-optimised adaptive Hammerstein filter-based structures performed better with improved signal-to-noise ratio and minimal mean squared error values. A digital signal processor kit is used to authenticate the simulation outcomes.</p><p><strong>Conclusion: </strong>The results (mean squared error: 3.698E-08 and signal-to-noise ratio improvement: 12 dB) obtained through the proposed technique ensure its supremacy compared to other state-of-the-art techniques.</p><p><strong>Significance: </strong>Hence, the proposed method can be utilised for electrocardiogram signal enhancement.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"140-154"},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907443","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}