IEEE Transactions on Biomedical Engineering最新文献

{"title":"Average Responses of Brain Displacement Under Rotational Loading for Computational Model Validation.","authors":"Ahmed A Alshareef, J Sebastian Giudice, Taotao Wu, Matthew B Panzer","doi":"10.1109/TBME.2025.3572300","DOIUrl":"https://doi.org/10.1109/TBME.2025.3572300","url":null,"abstract":"<p><strong>Objective: </strong>Computational models of the brain are typically validated using individual subjects from datasets of brain motion, but a comparison to an individual subject does not consider the biomechanical variation that naturally exists in the population. When data from multiple subjects is available, biomechanical corridors are constructed for the assessment of model biofidelity. However, a robust set of corridors for brain's biomechanical response due to applied head kinematics does not exist for model validation. The aim of this study was to create corridors based on a dataset of in situ brain displacement that included six specimens tested under a set of twelve loading conditions.</p><p><strong>Methods: </strong>There were three main factors that complicated this task, including variation in head kinematics, differences in the initial position of the sensors, and the clustering of spatially scattered data. We employed various numerical and statistical methods to account for these experimental variations, with optimization and validation of the techniques conducted using the existing in situ dataset and a computational brain model.</p><p><strong>Results: </strong>Corridors were constructed using average and standard deviation of the specimen responses in the dataset for 24 discrete locations within the brain. Peak displacement showed a variance of less than 30% for most brain sensor locations.</p><p><strong>Conclusion: </strong>The corridors will serve as a better validation tool for assessing the biofidelity of computational brain models and will help understand inter-subject variability in brain biomechanics.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144119381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-Invasive Assessment of Structural and Mechanical Microenvironment (MME) Changes during Long Bone Regeneration Using Multi-Modal and Multi-Parametric Ultrasound Imaging Techniques in a Segmental Tibial Sheep Model In Vivo.","authors":"Songyuan Tang, Peer Shajudeen, Francesca Taraballi, Candice Hasse, Fernando Cabrera, Xu Yang, Md Tauhidul Islam, Enrica De Rosa, Bradley Weiner, Matthew Becker, Ennio Tasciotti, Raffaella Righetti","doi":"10.1109/TBME.2025.3572366","DOIUrl":"https://doi.org/10.1109/TBME.2025.3572366","url":null,"abstract":"<p><strong>Objective: </strong>The underlying regeneration process of bony defects often exhibits multifaceted nature, which may not be completely characterized by imaging methods currently available to the clinic. In this paper, we present the first longitudinal study to use multi-modal and multi-parametric ultrasound (US) imaging to assess bone regeneration in situations of segmental defects. Our intention is to demonstrate the utility of 3-D US and ultra-sound elastography (USE) to monitor ongoing biological processes accompanying bone regeneration.</p><p><strong>Methods: </strong>We derived two imaging markers from the proposed multimodal US imaging technique: the new-bone bulk volume and fibrovascular connective tissue area and computed their global and local statistics in a subject-specific manner.</p><p><strong>Results: </strong>From a cohort of 5 sheep treated with baseline tissue engineered construct (TEC), the distance (mm) between surface reconstructions from multi-view 3-D US and CT was 0.30 ± 0.67 (60 days post implantation) and 0.22 ± 0.43 (120 days post implantation). From USE, we discovered a new contrast mechanism between the soft tissue and fibrovascular connective tissue in axial normal strain elastograms and corroborated it using end-point histology. From two sheep, we detected negative and positive correlations between the fibrovascular connective tissue area at 60 days post shell implantation and the area of bone mass that continued to form after 60 days post shell implantation.</p><p><strong>Conclusion: </strong>Based on our results, it is feasible to use the proposed multi-modal and multi-parametric US imaging technique to assess structural and mechanical micro-environmental changes.</p><p><strong>Significance: </strong>In the future, 3-D US and USE may become important quantitative tools for bone fracture healing diagnosis and prognosis.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144119390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive Information Decomposition as a Tool to Quantify Emergent Dynamical Behaviors In Physiological Networks.","authors":"Luca Faes, Gorana Mijatovic, Laura Sparacino, Alberto Porta","doi":"10.1109/TBME.2025.3570937","DOIUrl":"10.1109/TBME.2025.3570937","url":null,"abstract":"<p><strong>Objective: </strong>This work introduces a framework for multivariate time series analysis aimed at detecting and quantifying collective emerging behaviors in the dynamics of physiological networks.</p><p><strong>Methods: </strong>Given a network system mapped by a vector random process, we compute the predictive information (PI) between the present and past network states and dissect it into amounts quantifying the unique, redundant and synergistic information shared by the present of the network and the past of each unit. Emergence is then quantified as the prevalence of the synergistic over the redundant contribution. The framework is implemented in practice using vector autoregressive (VAR) models.</p><p><strong>Results: </strong>Validation in simulated VAR processes documents that emerging behaviors arise in networks where multiple causal interactions coexist with internal dynamics. The application to cardiovascular and respiratory networks mapping the beat-to-beat variability of heart rate, arterial pressure and respiration measured at rest and during postural stress reveals the presence of statistically significant net synergy, as well as its modulation with sympathetic nervous system activation.</p><p><strong>Conclusion: </strong>Causal emergence can be efficiently assessed decomposing the PI of network systems via VAR models applied to multivariate time series. This approach evidences the synergy/redundancy balance as a hallmark of integrated short-term autonomic control in cardiovascular and respiratory networks.</p><p><strong>Significance: </strong>Measures of causal emergence provide a practical tool to quantify the mechanisms of causal influence that determine the dynamic state of cardiovascular and neural network systems across distinct physiopathological conditions.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Temporal and Spectral Processing for Improved Digital Subtraction Angiography using Photon-Counting Detectors.","authors":"Suyu Liao, Xiaoxuan Zhang, Xiao Jiang, Matthew Tivnan, J Webster Stayman, Grace J Gang","doi":"10.1109/TBME.2025.3570925","DOIUrl":"10.1109/TBME.2025.3570925","url":null,"abstract":"<p><strong>Objective: </strong>Digital subtraction angiography (DSA) is the gold standard modality for diagnostics and guidance for interventional procedures. Spectral imaging has previously been explored for DSA, but severe noise amplification from material decomposition has impeded clinical adoption. We present a novel joint processing strategy that leverages both temporal and spectral information for material decomposition to address this issue.</p><p><strong>Methods: </strong>We develop a model-based material decomposition approach that utilizes the pre- and post-contrast images simultaneously for material estimation. Performance was evaluated on a small-vessel phantom on a test bench with a photon-counting detector. Joint processing was compared with temporal subtraction and previously proposed spectral DSA techniques including hybrid subtraction and conventional three-material decomposition. Additional simulation was performed to investigate performance with perfectly calibrated spectral response and sensitivity to patient motion.</p><p><strong>Results: </strong>The improved conditioning of the proposed method effectively reduces bias and noise in the spectral results and allows three-material decomposition with dual-energy spectral measurements. The method achieved more than an order of magnitude variance reduction compared to previously proposed spectral DSA techniques. Compared to temporal subtraction, a mean variance reduction of 23.9% was achieved in simulation and 10.8% in experimental data. The degree of reduction is object-dependent. Noise reduction achieved in physical experiments is slightly lower than that in simulation, likely due to bias from imperfect spectral calibration. The method is equally sensitive to motion compared to temporal subtraction.</p><p><strong>Conclusion: </strong>The proposed method addresses a major image quality challenge limiting previous approaches and outperforms temporal subtraction.</p><p><strong>Significance: </strong>Such improvements facilitate the clinical translation of spectral angiography.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying Chaotic Behavior in Noisy Dynamical Systems: A Study on Heartbeat Dynamics.","authors":"Martina Bianco, Andrea Scarciglia, Claudio Bonanno, Gaetano Valenza","doi":"10.1109/TBME.2025.3566470","DOIUrl":"10.1109/TBME.2025.3566470","url":null,"abstract":"<p><strong>Background: </strong>Heart rate variability (HRV) series reflects the dynamical variation of R-R intervals in time and is one of the outputs of the cardiovascular system. This system has been recognized for generating nonlinear and complex dynamics, with the latter referring to a high sensitivity to small -theoretically infinitesimal - input changes. While early research associated chaotic behavior with the cardiovascular system, evidence of stochastic inputs, i.e., a physiological noise, invalidated those conclusions.</p><p><strong>Aim: </strong>We introduce a novel methodological framework for quantifying the presence of regular or chaotic dynamics in noisy dynamical systems. We aim to perform a comprehensive characterization of the cardiovascular system dynamics, accounting for dynamical noise inputs.</p><p><strong>Methodology: </strong>The method relies on the estimation of asymptotic growth rate of noisy mean square displacement series in a two-dimensional phase space. Cardiac oscillatory components are modelled through an Inverse-Gaussian function. We validated the proposed method using synthetic series comprising well-known regular and chaotic maps. We applied the method to real HRV series from 23 healthy subjects, as well as 28 patients with atrial fibrillation and 34 congestive heart failure, gathered during unstructured long-term activity.</p><p><strong>Results: </strong>Results on synthetic data validate the correctness of the method. While cardiac pathology does not modulate chaotic behavior, atrial fibrillation induces higher sensitivity to input changes.</p><p><strong>Conclusion: </strong>The proposed methodological framework provides a quantitative means for characterizing physiological dynamics in terms of regular versus chaotic patterns. Our findings demonstrate that HRV series is the output of a non-chaotic (regular) system driven by dynamical noise.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid KLT-LSTM Tracking for Robust Organ Motion Monitoring in 2D Ultrasound-Guided End-Organ Therapies.","authors":"Maryam Zebarjadi, Anna J Organ, Daniel P Zachs, Hubert H Lim","doi":"10.1109/TBME.2025.3570552","DOIUrl":"10.1109/TBME.2025.3570552","url":null,"abstract":"<p><strong>Objective: </strong>Recent research highlights the potential of ultrasound (US) stimulation as a noninvasive tool for modulating neural and cellular signaling in the spleen and liver to treat inflammatory diseases and diabetes. However, challenges like nerve activation failures, off-target stimulation, and organ motion during respiration can affect treatment efficacy. This study introduces a novel tracking framework for accurate liver and spleen motion tracking using US imaging to overcome these challenges.</p><p><strong>Methods: </strong>The tracking framework integrates an enhanced Kanade-Lucas-Tomasi (EKLT) tracker with a long short-term memory (LSTM) predictor. The EKLT tracker provides precise annotations that improve LSTM training, while the LSTM compensates for occlusions and noise by making predictions based on prior data and dynamically adjusting the region of interest (ROI). Spleen motion tracking was evaluated using 40 recordings from 10 participants, each undergoing four distinct breathing patterns. Additionally, the method was evaluated on a liver motion dataset from MICCAI, collected from 9 subjects.</p><p><strong>Results: </strong>Spleen tracking was most accurate during slow, shallow breathing, with an average error of 0.4 ± 0.4 mm, and had an average error of 1.37 ± 0.9 mm during fast, deep breathing. Liver tracking results showed high accuracy with an average error of 0.3 ± 0.2 mm.</p><p><strong>Conclusion: </strong>The EKLT-LSTM framework offers advantages over previous tracking models, providing high accuracy in tracking liver and spleen motion under occlusion and noisy conditions.</p><p><strong>Significance: </strong>The EKLT-LSTM is suitable for end-organ modulation applications and can be adapted to other ultrasound-guided therapies and bioelectronic medicine.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalizing the Pressure Reactivity Index for Quantifying Cerebral Autoregulation in Neurocritical Care.","authors":"Jennifer K Briggs, J N Stroh, Brandon Foreman, Soojin Park, Tellen D Bennett, David J Albers","doi":"10.1109/TBME.2025.3570249","DOIUrl":"https://doi.org/10.1109/TBME.2025.3570249","url":null,"abstract":"<p><strong>Objective: </strong>The Pressure Reactivity Index (PRx) is a common metric for assessing cerebral autoregulation in neurocritical care. This study aimed to enhance the clinical utility of PRx by developing a personalized PRx algorithm (pPRx) and identifying ideal hyperparameters.</p><p><strong>Methods: </strong>Algorithmic errors were quantified using simulated data and multimodal monitoring data from traumatic brain injury patients from the Track-TBI dataset. Using linear regression, heart rate was identified as a potential cause of PRx error. The pPRx method was developed by reparameterizing PRx averaging to heartbeats. Ideal hyperparameters for the standard PRx algorithm were identified that minimized algorithmic errors.</p><p><strong>Results: </strong>PRx was sensitive to hyperparameters and patient variability. Errors were related to patient heart rates. By parameterizing PRx to heartbeats, the pPRx methodology significantly reduced noise and sensitivity to both patient variability and hyperparameter selection. In the standard PRx algorithm, averaging windows of 10 seconds and correlation windows of 40 samples resulted in the lowest overall error.</p><p><strong>Conclusion: </strong>Personalized PRx enhances the robustness and accuracy of cerebral autoregulation estimation by addressing patient- and hyperparameter-sensitivity. This improvement is crucial for reliable clinical decision-making in neurocritical care.</p><p><strong>Significance: </strong>Robust estimation of cerebral autoregulation would be beneficial for identifying precision medicine targets and improving outcomes for neurocritical care patients. We systematically increased the robustness of PRx to make it more consistent across patient populations.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single Treatment Boiling Histotripsy Focused Ultrasound Ablation Neither Negates nor Enhances the Activity of α-CD40 in a Pancreatic Cancer Model.","authors":"Mariia Stepanechko, Awndre Gamache, Frederic Padilla, Madison Nemshick, Lydia Kitelinger, Claire Conarroe, Matthew DeWitt, John A Hossack, Timothy Nj Bullock","doi":"10.1109/TBME.2025.3568594","DOIUrl":"10.1109/TBME.2025.3568594","url":null,"abstract":"<p><strong>Objective: </strong>Pancreatic adenocarcinoma (PDAC) tumors are often unresectable and do not respond to standard anti-cancer treatments. Boiling histotripsy (BH) is a mechanical focused ultrasound ablation regimen that can target nonoperable tumors. BH is a non-invasive procedure that might synergize with immunotherapies being developed for PDAC. We reasoned that BH-mediated release of tumor antigen and damage-associated molecular patterns would augment tumor immunity and cooperate with α-CD40 therapy.</p><p><strong>Methods: </strong>We explored the efficacy of BH ablation either as monotherapy for PDAC or in combination with systemically administered αCD40 agonistic antibodies in controlling tumor outgrowth. We further assessed the changes in the tumor immune compartment and the ability of BH to release tumor antigens by flow cytometry.</p><p><strong>Results: </strong>A single BH treatment could not control tumor growth and had limited independent immunostimulatory properties. BH effectively liberated tumor antigen into the tumor microenvironment for acquisition by local phagocytes but did not promote its presence in the tumor-draining lymph nodes. BH did not activate either tumor- or lymph noderesident conventional dendritic cells. BH did not impede the ability of α-CD40 immunotherapy to reduce the tumor burden and promote the infiltration of M1-like macrophages and IFNγ+ CD8+ T cells to the tumor microenvironment, suggesting that antibody access to the ablated tissue was not obstructed.</p><p><strong>Conclusion: </strong>Our findings indicate that PDAC tumor progression cannot be halted by BH ablation using sub-total ablation, and that the BH treatment regimen utilized in this study has limited immunogenicity.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-intrusive Reduced Order Modeling of Patient-specific Cochlear Implantations.","authors":"Fynn Bensel, Daniel Kipping, Marlis Reiber, Yixuan Zhang, Udo Nackenhorst, Waldo Nogueira","doi":"10.1109/TBME.2025.3568593","DOIUrl":"https://doi.org/10.1109/TBME.2025.3568593","url":null,"abstract":"<p><strong>Objective: </strong>Cochlear implants successfully treat severe to profound hearing loss patients. Patient-specific numerical simulations can yield important insights that could guide surgical planning and the interpretation of post-operative measurements. However, these simulations have a high computational effort.</p><p><strong>Methods: </strong>A non-intrusive reduced-order model has been used to replace the patient-specific model generation and simulation of different electrical stimulation sources, reducing the computational time and enabling fast response simulations. The reduced-order model combines proper orthogonal decomposition with radial basis function interpolation. The dataset used to build the reduced order model consists of 528 different solutions, also referred to as snapshots, from 24 cochlear models, with each cochlea subjected to 22 simulations with varying electrical stimuli. Each simulation is characterized by five parameters, three specifying the cochlea geometry and two specifying the electrode array position and the active electrode.</p><p><strong>Results: </strong>A leave-one-out strategy was used to verify the accuracy of the reduced-order model. The presented approach reduces the time for the patient-specific model generation and simulation from nearly 1.5 hours to less than a second while providing a high accuracy of the solutions with a relative error of 2.5% compared to the finite element solution.</p><p><strong>Conclusion: </strong>The presented non-intrusive reduced order model can predict the 3D intracochlear voltage distribution for new patients and implant positions.</p><p><strong>Significance: </strong>This work demonstrates the feasibility of fast patient-specific simulations. These numerical investigations could support the fitting of cochlear implants, the design of individualized sound coding strategies and surgery-dependent decision-making.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Calibration of EMG-Informed Neuromusculoskeletal Models Through Differentiable Physics and Muscle Synergies.","authors":"Matthew J Hambly, Matthew T O Worsey, David G Lloyd, Claudio Pizzolato","doi":"10.1109/TBME.2025.3569682","DOIUrl":"https://doi.org/10.1109/TBME.2025.3569682","url":null,"abstract":"<p><strong>Objective: </strong>Electromyogram (EMG)-informed neuromusculoskeletal (NMS) models can predict physiologically plausible muscle forces and joint moments. However, calibrating model parameters (e.g., optimal fiber length, tendon slack length) to the individual is time-consuming, with the optimization often requiring hours to converge and typically not accounting for unrecorded muscle excitations. This study addresses these limitations by incorporating differentiable physics and muscle synergies into the calibration of NMS models.</p><p><strong>Methods: </strong>We implemented an NMS model with auto-differentiable Hill-type muscles, enabling the use of adaptive gradient descent optimizers. Two types of calibration were evaluated: a standard EMG-driven approach and a synergy-hybrid approach that also synthesized unrecorded excitations. These methods were evaluated using upper and lower limb data, each from a single participant.</p><p><strong>Results: </strong>The calibration time was reduced by up to 26 times while maintaining comparable accuracy in moment predictions. Compared to the EMG-driven calibration, the synergy-hybrid calibration improved the estimates of model parameters for reduced number of EMG channels.</p><p><strong>Conclusion: </strong>Autodifferentiable Hill-type muscle models greatly reduce NMS model calibration time and enables the synthesis of unrecorded muscle excitations through muscle synergies, facilitating the calibration of all muscle parameters.</p><p><strong>Significance: </strong>This new rapid calibration could support deployment of NMS models in time-sensitive applications, including real-time biomechanical analyses and personalized neurorehabilitation.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}