IEEE Transactions on Biomedical Engineering最新文献_第10页

Development of Ocular Muscle Stimulation Systems and Optimization of Electrical Stimulus Parameters for Paralytic Strabismus Treatment 开发眼肌刺激系统并优化用于麻痹性斜视治疗的电刺激参数。

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-16 DOI: 10.1109/TBME.2024.3460814

Kyeongho Eom;Han-Sol Lee;Minju Park;Seung Min Yang;Jong Chan Choe;Suk-Won Hwang;Young-Woo Suh;Hyung-Min Lee

{"title":"Development of Ocular Muscle Stimulation Systems and Optimization of Electrical Stimulus Parameters for Paralytic Strabismus Treatment","authors":"Kyeongho Eom;Han-Sol Lee;Minju Park;Seung Min Yang;Jong Chan Choe;Suk-Won Hwang;Young-Woo Suh;Hyung-Min Lee","doi":"10.1109/TBME.2024.3460814","DOIUrl":"10.1109/TBME.2024.3460814","url":null,"abstract":"Paralysis of the extraocular muscles can lead to complications such as strabismus, diplopia, and loss of stereopsis. Current surgical treatments aim to mitigate these issues by resecting the paralyzed muscle or transposing the other recti muscles to the paralyzed muscle, but they do not fully improve the patient's quality of life. Electrical stimulation shows promise, while requiring further in vivo experiments and research on various stimulation parameters. In this study, we conducted experiments on rabbits to stimulate the superior rectus (SR) muscles using different parameters and stimulation waveforms. To provide various types of electrical stimulation, we developed the ocular muscle stimulation systems capable of both current controlled stimulation (CCS) and high-frequency stimulation (HFS), along with the chip that enables energy-efficient and safe switched-capacitor stimulation (SCS). We also developed electrodes for easy implantation and employed safe and efficient stimulation methods including CCS, SCS, and HFS. The in vivo animal experiments on normal and paralyzed SR muscles of rabbits showed that eyeball abduction angles were proportional to the current and pulse width of the stimulation. With the decaying exponential stimuli of the SCS system, eyeball abductions were 2.58× and 5.65× larger for normal and paralyzed muscles, respectively, compared to the rectangular stimulus of CCS. HFS achieved 0.92× and 0.26× abduction for normal and paralyzed muscles, respectively, with half energy compared to CCS. In addition, the continuous changes in eyeball abduction angle in response to varying stimulation intensity over time were observed.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"515-527"},"PeriodicalIF":4.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142286070","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}

引用次数: 0

Aperiodic Component Analysis in Quantification of Steady-State Visually Evoked Potentials 稳态视觉诱发电位量化中的非周期成分分析法

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-11 DOI: 10.1109/TBME.2024.3458060

Di Chen;Zhiqing Song;Yang Du;Sicong Chen;Xin Zhang;Yuanqing Li;Qiyun Huang

{"title":"Aperiodic Component Analysis in Quantification of Steady-State Visually Evoked Potentials","authors":"Di Chen;Zhiqing Song;Yang Du;Sicong Chen;Xin Zhang;Yuanqing Li;Qiyun Huang","doi":"10.1109/TBME.2024.3458060","DOIUrl":"10.1109/TBME.2024.3458060","url":null,"abstract":"<italic>Objective: In this study, we aimed to investigate whether and how the aperiodic component in electroencephalograms affects different quantitative processes of steady-state visually evoked potentials and the performance of corresponding brain-computer interfaces. <italic>Methods: We applied the Fitting Oscillations & One-Over-F method to parameterize power spectra as a combination of periodic oscillations and an aperiodic component. Electroencephalographic responses and system performance were measured and compared using four prevailing methods: power spectral density analysis, canonical correlation analysis, filter bank canonical correlation analysis and the state-of-the-art method, task discriminant component analysis. <italic>Results: We found that controlling for the aperiodic component prominently downgraded the performance of brain-computer interfaces measured by canonical correlation analysis (94.9% to 82.8%), filter bank canonical correlation analysis (94.1% to 87.6%), and task discriminant component analysis (96.5% to 70.3%). However, it had almost no effect on that measured by power spectral density analysis (80.4% to 78.7%). This was accompanied by a differential aperiodic impact between power spectral density analysis and the other three methods on the differentiation of the target and non-target stimuli. <italic>Conclusion: The aperiodic component distinctly impacts the quantification of steady-state visually evoked potentials and the performance of corresponding brain-computer interfaces. <italic>Significance: Our work underscores the significance of taking into account the dynamic nature of aperiodic activities in research related to the quantification of steady-state visually evoked potentials.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"468-479"},"PeriodicalIF":4.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10675437","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cardiac Time Intervals Under Motion Using Bimodal Chest E-Tattoos and Multistage Processing 使用双模胸部电子纹身和多级处理技术分析运动状态下的心脏时间间隔

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-10 DOI: 10.1109/TBME.2024.3454067

S. Bhattacharya;F. Santucci;M. Jankovic;T. Huang;J. Basu;P. Tan;E. Schena;N. Lu

{"title":"Cardiac Time Intervals Under Motion Using Bimodal Chest E-Tattoos and Multistage Processing","authors":"S. Bhattacharya;F. Santucci;M. Jankovic;T. Huang;J. Basu;P. Tan;E. Schena;N. Lu","doi":"10.1109/TBME.2024.3454067","DOIUrl":"10.1109/TBME.2024.3454067","url":null,"abstract":"<italic>Goal: We present a wireless, lightweight, stretchable, and chest-conformable sensor, known as the chest e-tattoo, coupled with an advanced signal processing framework to accurately identify various cardiac events, and thereby extract cardiac time intervals (CTIs) even during body motion. <italic>Methods: We developed a wireless chest e-tattoo featuring synchronous electrocardiography (ECG) and seismocardiography (SCG), with SCG capturing chest vibrations to complement ECG. Motion artifacts often compromise the efficacy of SCG, but the e-tattoo's slim, stretchy design allows strategic placement near the xiphoid process for improved signal quality. Nine participants were monitored during walking and cycling. To accurately extract CTIs, we implemented a multistage signal processing framework, named the FAD framework, combining adaptive Normalized Least Mean Squares (NMLS) filtering, ensemble averaging, and Empirical Mode Decomposition (EMD). <italic>Results: Key CTIs, especially left ventricular ejection time (LVET), were successfully extracted by our hardware-software system and showed strong agreement with those reported by an FDA-cleared bedside monitor even during substantial movements. The pre-ejection period (PEP) measured by the e-tattoo also aligned with previous findings. <italic>Conclusion: The bimodal chest e-tattoo combined with the FAD framework enables reliable CTI measurements during various activities. <italic>Significance: Managing cardiovascular disease at home necessitates continuous monitoring, which has been challenging with wearables due to signal sensitivity to motion. Accurately extracting cardiac events from synchronous SCG and ECG during motion can significantly enhance heart stress response quantification, offering a more comprehensive cardiac health assessment than ECG alone and marking a significant advancement in ambulatory cardiovascular monitoring capabilities.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 1","pages":"413-424"},"PeriodicalIF":4.4,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175223","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}

引用次数: 0

Deep Clustering for Epileptic Seizure Detection 用于癫痫发作检测的深度聚类技术

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-10 DOI: 10.1109/TBME.2024.3458177

Tala Abdallah;Nisrine Jrad;Sally El Hajjar;Fahed Abdallah;Anne Humeau-Heurtier;Eliane El Howayek;Patrick Van Bogaert

{"title":"Deep Clustering for Epileptic Seizure Detection","authors":"Tala Abdallah;Nisrine Jrad;Sally El Hajjar;Fahed Abdallah;Anne Humeau-Heurtier;Eliane El Howayek;Patrick Van Bogaert","doi":"10.1109/TBME.2024.3458177","DOIUrl":"10.1109/TBME.2024.3458177","url":null,"abstract":"Epilepsy is a neurological disorder characterized by recurrent epileptic seizures, which are often unpredictable and increase mortality and morbidity risks. <italic>Objective: The objective of this study is to address the challenges of EEG-based epileptic seizure detection by introducing a novel methodology, Deep Embedded Gaussian Mixture (DEGM). <italic>Methods: The DEGM method begins with a deep autoencoder (DAE) for embedding the input EEG data, followed by Singular Value Decomposition (SVD) to enhance the representational quality of the embedding while achieving dimensionality reduction. A Gaussian Mixture Model (GMM) is then employed for clustering purposes. Unlike conventional supervised machine learning and deep learning techniques, DEGM leverages deep clustering (DC) algorithms for more effective seizure detection. <italic>Results: Empirical results from two real-world epileptic datasets demonstrate the notable performance of DEGM. The method's effectiveness is particularly remarkable given the substantial size of the datasets, showcasing its ability to handle large-scale EEG data efficiently. <italic>Conclusion: In conclusion, the DEGM methodology provides a novel and effective approach for EEG-based epileptic seizure detection, addressing key challenges such as data variability and artifact contamination. <italic>Significance: By combining deep autoencoders, SVD, and GMM, DEGM achieves superior clustering performance compared to existing methods, representing a significant advancement in biomedical research and clinical applications for epilepsy. Its robust performance on large datasets underscores its potential for improving seizure detection accuracy, ultimately contributing to better patient outcomes.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"480-492"},"PeriodicalIF":4.4,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175219","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}

引用次数: 0

Enhancing Domain Diversity of Transfer Learning-Based SSVEP-BCIs by the Reconstruction of Channel Correlation 通过重建通道相关性增强基于迁移学习的 SSVEP-BCI 的领域多样性

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-10 DOI: 10.1109/TBME.2024.3458389

Wenlong Ding;Aiping Liu;Chengjuan Xie;Kai Wang;Xun Chen

{"title":"Enhancing Domain Diversity of Transfer Learning-Based SSVEP-BCIs by the Reconstruction of Channel Correlation","authors":"Wenlong Ding;Aiping Liu;Chengjuan Xie;Kai Wang;Xun Chen","doi":"10.1109/TBME.2024.3458389","DOIUrl":"10.1109/TBME.2024.3458389","url":null,"abstract":"<italic>Objective: The application of transfer learning, specifically pre-training and fine-tuning, in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) has been demonstrated to effectively improve the classification performance of deep learning methods with limited calibration data. However, effectively learning task-related knowledge from source domains during the pre-training phase remains challenging. To address this issue, this study proposes an effective data augmentation method called Reconstruction of Channel Correlation (RCC) to optimize the utilization of the source domain data. <italic>Methods: Concretely, RCC reconstructs training samples using probabilistically mixed eigenvector matrices derived from covariance matrices across source domains. This process manipulates the channel correlation of training samples, implicitly creating novel synthesized domains. By increasing the diversity of source domains, RCC aims to enhance the domain generalizability of the pre-trained model. The effectiveness of RCC is validated through subject-independent and subject-adaptive classification experiments. <italic>Results: The results of subject-independent classification demonstrate that RCC significantly improves the classification performance of the pre-trained model on unseen target subjects. Moreover, when compared to the fine-tuning process using the RCC-absent pre-trained model, the fine-tuning process using the RCC-enhanced pre-trained model yields significantly improved performance in the subject-adaptive classification. <italic>Conclusion: RCC proves to enhance the performance of transfer learning by optimizing the utilization of the source domain data. <italic>Significance: The RCC-enhanced transfer learning has the potential to facilitate the practical implementation of SSVEP-BCIs in real-world scenarios.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"503-514"},"PeriodicalIF":4.4,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175218","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}

引用次数: 0

Older Individuals Do Not Show Task Specific Variations in EEG Band Power and Finger Force Coordination 老年人在脑电图波段功率和手指力量协调方面没有表现出特定任务的变化

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-09 DOI: 10.1109/TBME.2024.3435480

Balasubramanian Eswari;Sivakumar Balasubramanian;Varadhan SKM

{"title":"Older Individuals Do Not Show Task Specific Variations in EEG Band Power and Finger Force Coordination","authors":"Balasubramanian Eswari;Sivakumar Balasubramanian;Varadhan SKM","doi":"10.1109/TBME.2024.3435480","DOIUrl":"10.1109/TBME.2024.3435480","url":null,"abstract":"<italic>Objective: Controlling and coordinating finger force is crucial for performing everyday tasks and maintaining functional independence. Aging naturally weakens neural, muscular, and musculoskeletal systems, leading to compromised hand motor function. This decline reduces cortical activity, finger force control and coordination in older adults. Objective: To investigate independently the EEG band power and finger force coordination in older individuals and compare the results with young healthy adults. Methods: Twenty healthy young adults aged 20–30 (26.96 ± 2.68) and fourteen older adults aged 58–72 (62.57 ± 3.58) participated in this study. Participants held the instrumented handle gently for five seconds then lifted and held it for an additional five seconds in the two conditions: fixed (thumb platform secured) and free condition (thumb platform may slide on slider). Results: In the older individuals there was no difference observed in the finger force synergy indices, and EEG beta band power between the two task conditions. However, in the young group synergy indices and EEG beta band power were less in free condition compared to fixed condition. Additionally, in the fixed condition, older adults showed a reduced synergy indices and reduced EEG beta band power than the young adults. Conclusion: Older participants exhibited consistent synergy indices and beta band power across conditions, while young adults adjusted strategies based on tasks. Task-dependent finger force synergy indices were observed in young adults, contrasting with older individuals Additionally, it is suggested that EEG band power and synergy indices may be related, indicating potential associations between EEG activity and finger force coordination.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 1","pages":"4-13"},"PeriodicalIF":4.4,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175224","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}

引用次数: 0

Hierarchical Optimization for Personalized Hand and Wrist Musculoskeletal Modeling and Motion Estimation 针对个性化手部和腕部肌肉骨骼建模与运动估算的层次优化技术

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-09 DOI: 10.1109/TBME.2024.3456235

Lijun Han;Long Cheng;Houcheng Li;Yongxiang Zou;Shijie Qin;Ming Zhou

{"title":"Hierarchical Optimization for Personalized Hand and Wrist Musculoskeletal Modeling and Motion Estimation","authors":"Lijun Han;Long Cheng;Houcheng Li;Yongxiang Zou;Shijie Qin;Ming Zhou","doi":"10.1109/TBME.2024.3456235","DOIUrl":"10.1109/TBME.2024.3456235","url":null,"abstract":"<italic>Objective: Surface electromyography (sEMG) driven musculoskeletal models are promising to be applied in the field of human-computer interaction. However, due to the individual-specific physiological characteristics, generic models often fail to provide accurate motion estimation. This study optimized the general model to build a personalized model and improve the accuracy of motion estimation. <italic>Methods: Inspired by the coupling effect of wrist/hand movement, a hierarchical optimization approach for personalizing musculoskeletal models (HOPE-MM) is proposed, which aligns with the physiological characteristics of the human wrist and hand. To verify the effectiveness of personalized musculoskeletal model, single joint motions and simultaneous joint motions are estimated. In addition, Sobol sensitivity analysis is conducted to identify the key parameters of musculoskeletal model, providing guidance for model simplification. <italic>Results: The mean pearson correlation coefficient between the predicted joint angles and the measured joint angles are 0.95 <inline-formula><tex-math>$pm$</tex-math></inline-formula> 0.03 and 0.93 <inline-formula><tex-math>$pm$</tex-math></inline-formula> 0.01 for simultaneous wrist and metacarpophalangeal (MCP) joint movements, respectively, which have a significant improvement compared with the state-of-the-art works. By optimizing only the key parameters including tendon slack length, maximal isometric force and optimal fiber length, the performances of simplified model are comparable to the full-parameter model. <italic>Conclusion: These results provide insights into the effects of muscle-tendon parameters on musculoskeletal model, and musculoskeletal models personalized using hierarchical optimization methods can improve the accuracy of motion estimates. <italic>Significance: These findings facilitate the clinical application of musculoskeletal models in rehabilitation and robotic control.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 1","pages":"454-465"},"PeriodicalIF":4.4,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175225","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}

引用次数: 0

A Current-Based EEG Amplifier and Validation With a Saline Phantom and an SSVEP Paradigm 基于电流的脑电图放大器以及盐水模型和 SSVEP 范例的验证。

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-06 DOI: 10.1109/TBME.2024.3455270

Daniel Comadurán Márquez;Sarah J. Anderson;Kent G. Hecker;Kartikeya Murari

{"title":"A Current-Based EEG Amplifier and Validation With a Saline Phantom and an SSVEP Paradigm","authors":"Daniel Comadurán Márquez;Sarah J. Anderson;Kent G. Hecker;Kartikeya Murari","doi":"10.1109/TBME.2024.3455270","DOIUrl":"10.1109/TBME.2024.3455270","url":null,"abstract":"<italic>Objective: This work describes current-mode electroencephalography amplifiers to record the electrical activity of the tangentially oriented cells. Electroencephalography (EEG) measures the summed electrical activity from pyramidal cells in the brain by using non-invasive electrodes placed on the scalp. Traditional, voltage-based measurements are done with differential amplifiers. Depending on the location of the electrodes used for the differential measurement, EEG can estimate electrical activity from radially (common or average reference) or tangentially (bipolar derivation) oriented neurons. A limitation of the bipolar derivation is that when the electrodes are too close together, the conductive solution used to improve electrode-skin impedance can short-circuit the electrodes. Magnetoencephalography (MEG) also enables measurements from tangentially oriented cells without concerns about short-circuiting the electrodes. However, MEG is a more expensive, and a less available technology. Measuring from both radial and tangential cells can improve the resolution to localize the origin of brain activity; this could be extremely useful for diagnoses and treatment of several neurological disorders. <italic>Methods: Circuit design from previous implementations was improved and the device was compared to a voltage-based (vEEG) amplifier in a saline phantom and in humans with a steady state visually evoked potentials paradigm. <italic>Results: The current-based (cEEG) amplifier satisfied suggested electrical parameters for EEG amplifiers and exhibited higher sensitivity to tangential dipoles in the phantom study. It measured brain activity using the same scalp electrodes as vEEG amplifiers with comparable performance. <italic>Conclusion: current-based EEG amplifiers can be comparable to traditional voltage-based amplifiers and offer complementary information.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 1","pages":"445-453"},"PeriodicalIF":4.4,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142972","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}

引用次数: 0

An Automated and Robust Tool for Musculoskeletal and Finite Element Modeling of the Knee Joint 用于膝关节肌肉骨骼和有限元建模的自动化稳健工具。

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-05 DOI: 10.1109/TBME.2024.3438272

Amir Esrafilian;Shekhar S. Chandra;Anthony A. Gatti;Mikko J. Nissi;Anne-Mari Mustonen;Laura Säisänen;Jusa Reijonen;Petteri Nieminen;Petro Julkunen;Juha Töyräs;David J. Saxby;David G. Lloyd;Rami K. Korhonen

{"title":"An Automated and Robust Tool for Musculoskeletal and Finite Element Modeling of the Knee Joint","authors":"Amir Esrafilian;Shekhar S. Chandra;Anthony A. Gatti;Mikko J. Nissi;Anne-Mari Mustonen;Laura Säisänen;Jusa Reijonen;Petteri Nieminen;Petro Julkunen;Juha Töyräs;David J. Saxby;David G. Lloyd;Rami K. Korhonen","doi":"10.1109/TBME.2024.3438272","DOIUrl":"10.1109/TBME.2024.3438272","url":null,"abstract":"<italic>Objective: To develop and assess an automatic and robust knee musculoskeletal finite element (MSK-FE) modeling pipeline. <italic>Methods: Magnetic resonance images (MRIs) were used to train nnU-Net networks for auto-segmentation of knee bones (femur, tibia, patella, and fibula), cartilages (femur, tibia, and patella), menisci, and major knee ligaments. Two different MRI sequences were used to broaden applicability. Next, we created MSK-FE models of an unseen dataset using two MSK-FE modeling pipelines: template-based and auto-meshing. MSK models had personalized knee geometries with multi-degree-of-freedom elastic foundation contacts. FE models used fibril-reinforced poroviscoelastic swelling material models for cartilages and menisci. <italic>Results: Volumes of knee bones, cartilages, and menisci did not significantly differ (<italic>p>0.05) across MRI sequences. MSK models estimated secondary knee kinematics during passive knee flexion tests consistent with <italic>in vivo and simulation-based values from the literature. Between the template-based and auto-meshing FE models, estimated cartilage mechanics often differed significantly (<italic>p<0.05),>Conclusion: The template-based modeling provided a more rapid and robust tool than the auto-meshing approach, while the estimated knee biomechanics were comparable. Nonetheless, the auto-meshing approach might provide more accurate estimates in subjects with distinct knee irregularities, e.g., cartilage lesions. <italic>Significance: The MSK-FE modeling tool provides a rapid, easy-to-use, and robust approach for investigating task- and person-specific mechanical responses of the knee cartilage and menisci, holding significant promise, e.g., in personalized rehabilitation planning.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 1","pages":"56-69"},"PeriodicalIF":4.4,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10666719","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142139931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-Sensing Cavitation Detection for Pulsed Cavitational Ultrasound Therapy 用于脉冲空化超声波疗法的自感应空化检测。

IF 4.4 2区医学

IEEE Transactions on Biomedical Engineering Pub Date : 2024-09-05 DOI: 10.1109/TBME.2024.3454798

Clara Magnier;Wojciech Kwiecinski;Daniel Suarez Escudero;Suxer Alfonso Garcia;Elise Vacher;Maurice Delplanque;Emmanuel Messas;Mathieu Pernot

{"title":"Self-Sensing Cavitation Detection for Pulsed Cavitational Ultrasound Therapy","authors":"Clara Magnier;Wojciech Kwiecinski;Daniel Suarez Escudero;Suxer Alfonso Garcia;Elise Vacher;Maurice Delplanque;Emmanuel Messas;Mathieu Pernot","doi":"10.1109/TBME.2024.3454798","DOIUrl":"10.1109/TBME.2024.3454798","url":null,"abstract":"<italic>Objectives: Monitoring cavitation during ultrasound therapy is crucial for assessing the procedure safety and efficacy. This work aims to develop a self-sensing and low-complexity approach for robust cavitation detection in moving organs such as the heart. <italic>Methods: An analog-to-digital converter was connected onto one channel of the therapeutic transducer from a clinical system dedicated to cardiac therapy, allowing to record signals on a computer. Acquisition of successive echoes backscattered by the cavitation cloud on the therapeutic transducer was performed at a high repetition rate. Temporal variations of the backscattered echoes were analyzed with a Singular-Value Decomposition filter to discriminate signals associated to cavitation, based on its stochastic nature. Metrics were derived to classify the filtered backscattered echoes. Classification of raw backscattered echoes was also performed with a machine learning approach. The performances were evaluated on 155 <italic>in vitro acquisitions and 110 signals acquired <italic>in vivo during transthoracic cardiac ultrasound therapy on 3 swine. <italic>Results: Cavitation detection was achieved successfully in moving tissues with high signal to noise ratio <italic>in vitro (cSNR = 25±5) and <italic>in vivo (cSNR = 20±6) and outperformed conventional methods (cSNR = 11±6). Classification methods were validated with spectral analysis of hydrophone measurements. High accuracy was obtained using either the clutter filter-based method (accuracy of 1) or the neural network-based method (accuracy of 0.99). <italic>Conclusion: Robust self-sensing cavitation detection was demonstrated to be possible with a clutter filter-based method and a machine learning approach. <italic>Significance: The self-sensing cavitation detection method enables robust, reliable and low complexity cavitation activity monitoring during ultrasound therapy.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 1","pages":"435-444"},"PeriodicalIF":4.4,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142139932","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}

引用次数: 0