BMC biomedical engineering最新文献

{"title":"Comparative analysis of processed EEG indices and entropy-based metrics for assessing anesthetic depth: a scoping review - PRISMA-ScR.","authors":"Nuray Vakitbilir, Julia Ryznar, Vuk Roca, Tobias Bergmann, Isuru Herath, Rakibul Hasan, Kevin Y Stein, Amanjyot Singh Sainbhi, Noah Silvaggio, Mansoor Hayat, Jaewoong Moon, Frederick A Zeiler","doi":"10.1186/s42490-026-00112-z","DOIUrl":"10.1186/s42490-026-00112-z","url":null,"abstract":"<p><strong>Background: </strong>Processed electroencephalography (EEG) monitors such as the bispectral index (BIS) and patient state index (PSI), are used clinically to estimate anesthetic depth, yet their algorithmic design obscures how closely these indices reflect underlying neural complexity. Entropy-based analyses, grounded in information theory, provide a quantitative framework for characterizing EEG signal irregularity and have been proposed as physiologically interpretable alternatives. However, the relationship between these commercial indices and theoretical entropy measures remains unclear.</p><p><strong>Objectives: </strong>This systematic review aimed to (1) synthesize existing evidence on the relationship between commercially available processed EEG metrics and entropy-based EEG analyses, and (2) identify factors influencing their comparability, including algorithmic, demographic, and anesthetic variables.</p><p><strong>Methods: </strong>A comprehensive literature search identified experimental and clinical studies comparing BIS, PSI, and related commercial indices with theoretical entropy measures (e.g., approximate entropy, sample entropy, and permutation entropy, state entropy and response entropy) across various anesthetic agents and clinical populations. Data were extracted on study design, patient demographics, EEG metrics, analytical methods, and reported correlations or prediction probabilities.</p><p><strong>Results: </strong>Ninety-four studies were included, encompassing participants across diverse anesthetic modalities. Overall, BIS exhibited moderate-to-strong correlations with entropy-derived measures and comparable prediction probabilities for distinguishing anesthetic depth. Entropy indices demonstrated greater resistance to certain artifacts but higher susceptibility to electromyographic contamination. Age, anesthetic type, and the use of neuromuscular blocking agents significantly influenced the relationship between indices. Across studies, heterogeneity in preprocessing, entropy algorithms, and patient selection limited direct comparability.</p><p><strong>Conclusions: </strong>Commercially processed EEG indices and theoretical entropy measures capture overlapping but distinct dimensions of cortical dynamics during anesthesia. While both reliably track transitions in consciousness, discrepancies arise from differences in signal filtering, algorithm design, and physiological variability. Future research should prioritize transparent algorithmic frameworks and standardized entropy computation to enhance the interpretability and cross-device comparability of EEG-derived anesthesia monitors.</p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154472/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent applications of chaos theory in medical sciences: progress and challenges.","authors":"Oscar Espinosa, Angélica Ordóñez, Gabriela Puentes","doi":"10.1186/s42490-026-00111-0","DOIUrl":"10.1186/s42490-026-00111-0","url":null,"abstract":"<p><p>BACKGROUND: The application of chaos theory has positive results in different fields of science. Its nonlinear modeling properties and its vision of dynamic systems have enabled it to capture complex relationships in fields such as physics, financial econometrics, social systems and mathematical demography. This paper reviews the implication of chaos theory in the medical sciences. METHODOLOGY: We carried out a systematic literature review under Cochrane’s international standards. A search strategy was executed with indexed terms (MeSH, DeCS and Emtree) that varied according to each database (Embase, MEDLINE, SciELO, LILACS). The PROSPERO registration number was CRD42023491407. FINDINGS: In total, 2598 articles were retrieved, of which 20 were included. Algorithmic applications of chaotic systems were diverse. The medical fields with the largest studies were cardiology, neurology and oncology. The most used software was Matlab, however, in all cases, except one, we did not find open-source codes related to the studies. INTERPRETATION: We found a wide heterogeneity in the studies reviewed, and this was reflected in the scope of research results. While some papers focus on proving the existence of chaotic behavior or understanding the nature of the phenomena being studied, others propose practical implications, such as in prescribing medicines and organizing health units. CLINICAL TRIAL NUMBER: Not applicable. </p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13134123/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147824228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-enzymatic sweat sensors for pediatric continuous glucose monitoring: a systematic review of engineering readiness and the cost-accuracy trade-off.","authors":"Oluwanifemi Temiloluwa Bolaji, Emmanuel Dominic Ephraim, Olumhense Benedict Adoghe, Deborah Daramola, Emmanuel Francis Kibuebu","doi":"10.1186/s42490-026-00109-8","DOIUrl":"10.1186/s42490-026-00109-8","url":null,"abstract":"<p><p>Continuous glucose monitoring (CGM) in children with type 1 diabetes is faced with major challenges due to prohibitive price, invasiveness and lack of compliance with insulin of the currently available interstitial devices, which is particularly severe in low- and middle-income countries (LMICs). To investigate emerging solutions, we have undertaken a systematic review (2016–2025) of non-invasive, sweat-based glucose sensors and used a structured biomedical engineering model to determine the technological maturity and pediatric and global health usage of the sensors. The review of 25 peer-reviewed articles indicates a significant shift to non-enzymatic sensing schemes based on strong approaches and incorporating highly sensitive nanomaterials like MXene and scalable libraries of fabrications. An analysis of qualitative cost accuracy trade-off, formalized by new, specially developed LMIC Scalability Score, proves that whereas complex and expensive systems would reach the lowest mean absolute relative difference (MARD), simpler and highly scalable devices would reach the same performance with a MARD value under 10.5%, making them possible and low-cost variants. To this end, the essential interventions that can be done to facilitate clinical translation in the short term are the design of advanced physiological time-lag simulations and the implementation of strong, age-focused pediatric clinical trials to bridge the technology innovation and clinical practice gap.</p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147694132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linking neurological status to functional outcomes in spinal cord injury: a multi-class, task-specific approach.","authors":"Miklovana Tuci, Lena Steck, Louis P Lukas, Olga Taran, Ruediger Rupp, Norbert Weidner, Martin Schubert, Frank Röhrich, Josina Waldmann, Yorck B Kalke, Rainer Abel, Doris Maier, Thomas Liebscher, Björn Zörner, Armin Curt, Marc Bolliger, Sarah C Brüningk, Catherine R Jutzeler","doi":"10.1186/s42490-026-00110-1","DOIUrl":"10.1186/s42490-026-00110-1","url":null,"abstract":"<p><p>BACKGROUND: Spinal cord injury (SCI) causes long-term neurological deficits resulting in functional disabilities. While longitudinal recovery patterns of sensorimotor outcomes after SCI have been studied, few analyses have applied machine learning to systematically model the relationship between neurological impairments and functional independence at different post-injury phases. METHODS: This study compared ordinal and nominal classification models predicting functional independence from sensorimotor status cross-sectionally. Inputs included motor and sensory scores from the International Standards for Neurological Classification of SCI, age, sex, and time since injury collected in the European Multicenter Study about SCI. Models were evaluated on a task from each domain of the Spinal Cord Independence Measure, namely grooming (self-care), bladder management (respiration and sphincter management), and indoor mobility (mobility). Analyses were stratified into early (≤ 40 days), intermediate (70–100 days), and late (> 182 days) post-injury phases. Models were ranked based on five evaluation metrics, and interpretability explored using Shapley Additive Explanations (SHAP). RESULTS: Model accuracy improved over time (early phase: 46–71%, late phase: 50–85%), indicating that functional independence is more reliably determined from sensorimotor scores in later post-injury phases. Across all scenarios, random forest achieved the best overall performance (0.93 ± 0.03, averaged across different metrics). Ordinal models yielded fewer severe misclassifications compared to nominal models. Motor scores were stronger predictors than sensory scores, with lower limb function (L2–L4) strongly associated with mobility, voluntary anal contraction with bladder control, and upper limb function (C6, C8) with grooming ability, highlighting that models utilise known relationships. CONCLUSION: We show that both multiclass and ordinal models can accurately classify SCIM-based functional independence outcomes after SCI from neurological assessments at different time points post-injury. Ordinal approaches provide particular clinical value by minimizing severe misclassifications, a crucial advantage when distinguishing between functional independence classes that require fundamentally different care approaches. Interpretability analysis showed that the predictions are grounded in clinical knowledge. The developed models provide the basis for a modular prognostic framework, in which predicted ISNCSCI scores can be used to derive the most likely functional independence class, enabling a modular, computationally efficient and scalable approach to prediction in SCI care across a range of neurological and functional outcomes. </p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147694130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying mechanical and morphological properties of plantar foot soft tissues: a systematic review of techniques, methods and their clinimetric properties.","authors":"Alessandro Vicentini, Marieke A Mens, Arjan Malekzadeh, Jaap J van Netten, Mario Maas, Sicco A Bus","doi":"10.1186/s42490-026-00106-x","DOIUrl":"10.1186/s42490-026-00106-x","url":null,"abstract":"","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13014740/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomechanical evaluation of individual 3D-printed vertebrae.","authors":"Florian Metzner, Stefan Schleifenbaum, Christoph-Eckhard Heyde, Nicolas Heinz von der Höh","doi":"10.1186/s42490-026-00107-w","DOIUrl":"10.1186/s42490-026-00107-w","url":null,"abstract":"<p><p>BACKGROUND: Personalized 3D-printed bone models are becoming increasingly popular in clinical care. Common applications include the visualization of idiopathic deformities or complex joint fractures. Functionalizing such printed replicas in terms of individual mechanical properties holds great potential for clinical training and research but is challenging due to the complexity of the bone structure. This study aims at developing a parametrizable structure as a substitute for spongious bone by simplifying 3D reconstruction and printing. METHODS: 43 vertebrae from 6 body donors aged 86.8 ± 7.8 years were examined. Each spine underwent a clinical computed tomography scan. Cylindrical samples (Ø6 × 12 mm) were randomly taken from the left or right side of the vertebral body using a core drill in the superior-inferior direction. Specific software was used for determining the volumetric Hounsfield units of the spongious bone in each vertebral hemisphere. In parallel, a parametric hexagonal grid structure was designed using engineering software. All rods within the lattice have a variable length L and a fixed diameter of t = 0.4 mm. By varying the ratio t/L, six different porosities were defined. For each of these, five cylindrical lattice samples (diameter/length = 1/2) from two different synthetic resins were manufactured using the stereolithography printing process. All samples were mechanically characterized by uniaxial compressive testing. Curve fitting based on power functions (y = axb) allowed the determination of correlations between mechanical parameters and Hounsfield units (bone) as well as the lattice parameter t/L (3D-printed lattice). Finally, three vertebrae with varying bone quality were printed with their respected parameterized lattice and evaluated by comparing the axial screw pullout forces of the human and the respective printed bones. RESULTS: There is a significant correlation between the mechanical properties of the bone specimens and the determined Hounsfield units. Furthermore, the mechanical properties of the lattice can be excellently described by the ratio t/L. The printed vertebrae showed pull-out forces similar to those of osteoporotic bone. CONLUSION: The mechanical behavior of vertebral human spongious bone can be well reproduced by a 3D-printed generic lattice structure. Patient-specific bone models can be generated by integrating the parameterizable lattice structure into the specific bone contours. These models can help in improving patient care, for instance by enabling highly realistic surgical approaches for particularly complex anatomies. </p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13063776/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147370795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of a wearable movement tracking system in detecting hypomobility in acute ischemic cerebrovascular events.","authors":"Duc T Ha, Van Binh Nguyen, An T T Vo, Dieu T Truong, Tuan V Nguyen","doi":"10.1186/s42490-026-00105-y","DOIUrl":"10.1186/s42490-026-00105-y","url":null,"abstract":"<p><p>BACKGROUND: Detecting new or worsening hypomobility in acute ischemic cerebrovascular patients is challenging, especially when asleep or unattended. This study used a wearable movement acceleration monitoring system to identify changes in these patients, aiming to improve early detection. METHODS: Continuous bilateral upper limb acceleration data, clinical characteristics, specific treatments, stroke etiology, and in-hospital outcomes were collected from patients. The primary outcome was newly emerging or worsening hypomobility during monitoring. An XGBoost model, trained with synthetic minority oversampling to address class imbalance and validated via 5-fold cross-validation, analyzed movement acceleration features to diagnose hypomobility timing. Model performance was evaluated through AUC and feature importance metrics. RESULTS: From April 2023 to February 2025, 85 patients with acute ischemic cerebrovascular events were enrolled; three were excluded due to data errors. A total of 82 patients were included in the analysis, comprising 76 (92.7%) with ischemic stroke and 6 (7.3%) with transient ischemic attack. Among them, 26 (31.7%) were women. The median monitoring duration was 26.9 hours (IQR: 24.6–46.5), with 15 patients (18.3%) developing hypomobility. The XGBoost model achieved an AUC of 0.975 (95% CI: 0.965–0.985) and a mean AUC of 0.975 (SD 0.003) across folds. Optimized with a learning rate of 0.1, maximum depth of 6, and 200 boosting rounds, the model, at a cutoff of 0.587, recorded an average sensitivity of 0.969 and specificity of 0.900, accurately detecting 96.9% of the hypomobility cases. The overall metrics included a sensitivity of 0.966, specificity of 0.900, positive predictive value of 0.896, negative predictive value of 0.968, and F1-score of 0.930. The SHAP (SHapley Additive exPlanations) analysis revealed the significant contributions of the interaction terms (mean |SHAP| = 3.475) and slope features for movement changes (e.g., 1-min RSMA and LSMA slopes), while elevating the importance of the ‘Likely weak side’ predictor (mean |SHAP| = 2.053) in orienting asymmetry. CONCLUSION: This wearable movement acceleration monitoring system, by continuously tracking upper limb acceleration data, effectively detects the onset of hypomobility in acute ischemic cerebrovascular patients, highlighting its substantial potential for clinical application in enabling timely interventions and improving patient outcomes. </p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"8 1","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12882146/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146133689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility study of an insole-type active assist device for ankle alignment correction during stepping in patients with knee osteoarthritis.","authors":"Taku Itami, Ryuichi Hirota, Masakatsu Iwase, Yoichi Oi, Koji Ebisu, Takaaki Aoki","doi":"10.1186/s42490-026-00104-z","DOIUrl":"10.1186/s42490-026-00104-z","url":null,"abstract":"<p><p>OBJECTIVES: This feasibility study aimed to examine whether an insole-type active assist device designed to dynamically adjust ankle alignment at heel contact can be safely delivered and evaluated during an on-the-spot stepping task in patients with medial knee osteoarthritis (OA). The study specifically assessed the feasibility of intervention delivery, testing procedures, and motion-capture-based outcome measurement. METHODS: Six ambulatory patients with medial knee OA (Kellgren–Lawrence grade II–III) performed repeated on-the-spot stepping trials under two conditions: Active (device control enabled) and Inactive (device control disabled). The assist device tilts the heel toward eversion in response to detected ankle inversion at heel contact. Feasibility outcomes included participant recruitment and completion, safe execution of the stepping task, device activation during trials, successful acquisition and analysis of motion capture data, and occurrence of adverse events. Lateral knee thrust was quantified descriptively using a three-dimensional motion capture system to characterize measurement variability and inform future study design. RESULTS: All participants provided informed consent and completed the stepping protocol (6/6, 100%), with no adverse events observed. The stepping task and testing procedures were safely performed in all cases. Motion capture data were successfully acquired and analyzed for all trials (90/90, 100%). The assistive mechanism was activated in at least one stepping trial in five of six participants (83%), with activation occurring in 39 of 90 stepping trials (43%). Across conditions, lateral knee thrust values showed substantial inter-individual and condition-related variability, ranging approximately from 30 to 110 mm across participants. CONCLUSIONS: This study demonstrates the feasibility and safety of delivering an insole-type active assist intervention and conducting motion-capture-based evaluations during an on-the-spot stepping task in patients with medial knee OA. The observed variability in lateral knee thrust highlights important considerations for outcome selection and sample size planning, supporting progression to future adequately powered studies to evaluate clinical and biomechanical effectiveness. </p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":" ","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12857131/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146088156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of virtual unenhanced images on a prototype silicon photon counting detector CT: preliminary clinical results.","authors":"Aria M Salyapongse, Timothy P Szczykutowicz, Meghan G Lubner, Zhye Yin, Ming Yan, Meghan Yue, Krista McClure, Giuseppe V Toia","doi":"10.1186/s42490-026-00103-0","DOIUrl":"10.1186/s42490-026-00103-0","url":null,"abstract":"<p><p>BACKGROUND: To compare virtual unenhanced images (VUE) from a prototype deep silicon photon-counting detector computed tomography (PCD CT) system with true unenhanced images (TUE). METHODS: Five subjects including various anatomic structures were scanned on a prototype deep silicon PCD CT at 120 kV across different phases with mA adjusted for anatomy and subject size. Five thin and three thick slices were selected from each image set at two locations to provide a variety of anatomy, including vessels, soft tissue, and adipose. Regions of interest were drawn over the anatomy on both TUE and VUE images. VUE error was defined as VUE CT number in Hounsfield units (HU) minus the TUE CT number. RESULTS: For all tested structures, 82% had a VUE error less than 10 HU, and 62% had a VUE error less than 5 HU. Vessels demonstrated VUE errors less than 10 HU and less than 5 HU for 70.4% and 40.7% of tested structures, respectively. Soft tissue had VUE errors less than 10 HU and 5 HU in 96.9% and 84.4%, and adipose had VUE errors less than 10 HU and 5 HU in 75% and 58.4% of tested structures. CONCLUSION: With the prototype scanner and VUE algorithm, the majority of tested anatomic structures demonstrated VUE error less than 10 HU. For all but vessels, the majority of structures demonstrated VUE error less than 5 HU. With such small differences in HU between VUE and TUE images, further work may support removing TUEs from scanning protocols. </p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":" ","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12918634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146069220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IMU-based joint axis identification method for arbitrary joints in OpenSim - a simulation study.","authors":"Iris Wechsler, Julian Shanbhag, Sandro Wartzack, Anne D Koelewijn, Jörg Miehling","doi":"10.1186/s42490-025-00102-7","DOIUrl":"10.1186/s42490-025-00102-7","url":null,"abstract":"<p><p>In musculoskeletal simulation, individualized joint axes enhance the accuracy and reliability of kinematic and kinetic simulation results. We investigated the correctness and performance of an analytical method for identifying the instantaneous axis of rotation between two bodies based on motion data in OpenSim. The instantaneous center of rotation is the point at which two bodies have the same velocity. The relative linear and angular velocity between the two bodies, as well as their relative position to each another, are required as inputs to calculate it. Using the instantaneous center of rotation, fixed or moving joint centers of rotation can be identified. To prove the general applicability of the method, the instantaneous centers of rotation of a revolute joint of a simple double pendulum model and the hip and knee joint of a more complex musculoskeletal model were investigated. The hip joint is defined as a ball joint. The knee joint is defined as an OpenSim custom joint which describes the motion of the child segment in relation to the parent segment as a function of generalized coordinates. To verify the correctness of the approach in OpenSim, the moving centers of rotation were calculated using synthetic noisefree data. The results were compared to the implementation of the respective joints in the model which act as the ground truth. White Gaussian noise was added to the synthetic data to analyze its effect on the quality of the calculated centers of rotation. We were able to correctly identify the center of rotation of each joint using noisefree data. In the case of noisy data, joint centers of rotation can be determined by applying additional filtering or optimization methods to the calculated instantaneous centers of rotation. Consequently, we are able to determine the center of rotation for arbitrary joints based on noisy synthetic data. This approach is applicable for both fixed and moving centers of rotation which distinguishes it from commonly used methods in the field of biomechanical simulation.</p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"7 1","pages":"16"},"PeriodicalIF":0.0,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12639932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145574961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}