IEEE Transactions on Neural Systems and Rehabilitation Engineering最新文献

{"title":"Cortico-Muscular Phase Connectivity During an Isometric Knee Extension Task in People With Early Parkinson’s Disease","authors":"Nina Omejc;Tomislav Stankovski;Manca Peskar;Miloš Kalc;Paolo Manganotti;Klaus Gramann;Sašo Džeroski;Uros Marusic","doi":"10.1109/TNSRE.2025.3527578","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3527578","url":null,"abstract":"Introduction: Cortico-muscular (CM) interactions provide insights into the flow of information between neural and motor systems. Reduced CM phase connectivity has been linked to functional impairments in clinical populations. Objective: This study aimed to determine whether similar reductions occur in individuals with Parkinson’s disease (PD), characterized primarily by motor impairments. Specifically, it aimed to characterize electroencephalography (EEG) and electromyography (EMG) power spectra during a motor task, assess CM phase connectivity, and explore how an additional cognitive task modulates these measures. Methodology: Fifteen individuals with early-stage PD and sixteen age-matched controls performed an isometric knee extension task, a cognitive task, and a combined dual task, while EEG (128 channels) and EMG (2x32 channels) were recorded. CM phase connectivity was analyzed through phase coherence and phase dynamics modeling. Results: The strongest CM phase coherence was observed in the lower beta band (12.5–15 Hz) over the Cz electrode and was significantly higher in healthy controls compared to individuals with PD during the motor task. The phase dynamics model additionally revealed stronger directional coupling from the Cz electrode to the active muscle, than in the reverse direction, with less pronounced phase coupling in the PD cohort. Notably, CM phase coherence exhibited distinct scalp topography and spectra characteristics compared to the EEG power spectrum, suggesting different mechanisms underlying Parkinsonian pathological beta power increase and CM phase connectivity. Lastly, despite high inter-individual variability, these metrics may prove useful for personalized assessments, particularly in people with heightened CM connectivity.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"488-501"},"PeriodicalIF":4.8,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835798","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184378","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}

{"title":"SSVEP Enhancement in Mixed Reality Environment for Brain–Computer Interfaces","authors":"Jieyu Wu;Feng He;Xiaolin Xiao;Runyuan Gao;Lin Meng;Xiuyun Liu;Minpeng Xu;Dong Ming","doi":"10.1109/TNSRE.2025.3526950","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3526950","url":null,"abstract":"Expanding the application possibilities of brain-computer interfaces (BCIs) is possible through their implementation in mixed reality (MR) environments. However, visual stimuli are displayed against a realistic scene in the MR environment, which degrades BCI performance. The purpose of this study was to optimize stimulus colors in order to improve the MR-BCI system’s performance. In the MR environment, a 10-command SSVEP-BCI was deployed. Various stimulus colors and background colors for the BCI system were tested and optimized in offline and online experiments. Color contrast ratios (CCRs) between stimulus and background colors were introduced to assess the performance difference among all conditions. Additionally, we proposed a cross-correlation task-related component analysis based on simulated annealing (SA-xTRCA), which can increase the signal-to-noise ratio (SNR) and detection accuracy by aligning SSVEP trials. The results of an offline experiment showed that the background and stimulus colors had a significant interaction effect that can impact system performance. A possible nonlinear relationship between CCR value and SSVEP detection accuracy exists. Online experiment results demonstrated that the system performed best with polychromatic stimulus on the colored background. The proposed SA-xTRCA significantly outperformed the other four traditional algorithms. The online average information transfer rate (ITR) achieved 57.58 ± 5.31 bits/min. This study proved that system performance can be effectively enhanced by optimizing stimulus color based on background color. In MR environments, CCR can be used as a quantitative criterion for choosing stimulus colors in BCI system design.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"420-430"},"PeriodicalIF":4.8,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10833816","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992969","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}

{"title":"Implementation and Tuning of Momentum-Based Controller for Standing Balance in a Lower-Limb Exoskeleton With Paraplegic User","authors":"A. Vallinas Prieto;A. Q. L. Keemink;E. H. F. van Asseldonk;H. van der Kooij","doi":"10.1109/TNSRE.2025.3526424","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3526424","url":null,"abstract":"Lower limb exoskeletons (LLEs) are wearable devices that can restore the movement autonomy of paraplegic users. LLEs can restore the users’ ability to stand upright and walk. However, most of the commercially available and clinically used LLEs rely on the user maintaining balance through the use of crutches. Recent improvements in the design and control of LLEs and other legged robots allow for autonomous balance control. In this work, we implement and evaluate a momentum-based standing balance controller in the Symbitron LLE, consisting of eight active (torque-controlled) and two passive joints. We first investigate how gain tuning of the center of mass tracking control law, part of a multi-objective optimal controller, affects balancing performance. We apply pushes on different device locations while in parallel-stance, compare the response for different gains, and derive heuristic guidelines for controller tuning given the control architecture, high-level goals, and hardware limitations. Next, we show how this controller successfully prescribes joint torques to the LLE to maintain balance with a paraplegic user. The LLE can autonomously balance the user and reject mediolateral and anteroposterior pushes in the order of 60 N at hip height (and 40 N at shoulder height) while standing in parallel-stance, staggered-stance with both feet at the same height, and staggered-stance with a height difference of 0.05 m between the feet. This work presents a viable control strategy for torque-controlled light-weight under-actuated LLEs to keep the balance of paraplegic users during stance, which is a necessary starting point towards autonomous balance control during gait.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"343-353"},"PeriodicalIF":4.8,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829591","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142962876","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}

{"title":"Finite Element Modelling for Biophysical Models of Nervous System Stimulation: Best Practices for Multiscale Adaptive Meshing","authors":"Rodrigo Osorio L.;Siobhan Mackenzie Hall;Francisco Saavedra R.;Pablo Aqueveque N.;James J. FitzGerald;Brian Andrews","doi":"10.1109/TNSRE.2024.3525343","DOIUrl":"https://doi.org/10.1109/TNSRE.2024.3525343","url":null,"abstract":"This paper presents methods for FEM modelling the peripheral and central nervous systems with considerations for meshing and computational constraints. FEM models in this context are convenient for testing hypothesises about the effects of different stimulation parameters and exploring different electrode designs before moving to in vitro and in vivo experiments. The methods presented in this paper are motivated by assessing differentiation errors from different mesh sizes and the transitions between different materials in the model. We aim to support the development of transparent and reproducible modelling experiments. Accurate and reproducible models are essential, given the importance of the applications in which these models are used. However, a dearth of literature is devoted to promoting best practices in finite element modelling for biophysical models. We evaluate the impact of differentiation errors on calculating the Activating Function and predicting action potentials in a Hodgkin-Huxley (H-H) axon model. We found that poor spatial discretisation facilitates the generation of double-derivative noise. However, it does not generate false predictions of action potentials on the H-H model. Activation thresholds were higher (57.5 mA) for coarser meshes than Fine and Extremely Fine (55 mA). Implementing Multiscale meshes with the finest refined sizes reduced material transition discontinuities reflected in the activating function calculation. Our findings support using the finest spatial discretisations possible within computational constraints, which may rely on adaptive meshing techniques. We advocate coupling the extracellular field to H-H-based axons to further limit potential error sources.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"298-309"},"PeriodicalIF":4.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10820855","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938187","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}

{"title":"Improving fMRI-Based Autism Severity Identification via Brain Network Distance and Adaptive Label Distribution Learning","authors":"Junling Du;Shangyu Wang;Rentong Chen;Shaoping Wang","doi":"10.1109/TNSRE.2024.3516216","DOIUrl":"https://doi.org/10.1109/TNSRE.2024.3516216","url":null,"abstract":"Machine learning methodologies have been profoundly researched in the realm of autism spectrum disorder (ASD) diagnosis. Nonetheless, owing to the ambiguity of ASD severity labels and individual differences in ASD severity, current fMRI-based methods for identifying ASD severity still do not achieve satisfactory performance. Besides, the potential association between brain functional networks(BFN) and ASD symptom severity remains under investigation. To address these problems, we propose a low&high-level BFN distance method and an adaptive multi-label distribution(HBFND-AMLD) technique for ASD severity identification. First, a low-level and high-level BFN distance(HBFND) is proposed to construct BFN that reflects differences in ASD severity. This method can measure the distance between the ASD and the health control(HC) on the low-order and high-order BFN respectively, which can distinguish the severity of ASD. After that, a multi-task network is proposed for ASD severity identification which considers the individual differences of ASD severity in communication and society, which considers the individual differences in language and social skills of ASD patients. Finally, a novel adaptive label distribution(ALD) technique is employed to train the ASD severity identification model, effectively preventing network overfitting by restricting label probability distribution. We evaluate the proposed framework on the public ABIDE I dataset. The promising results obtained by our framework outperform the state-of-the-art methods with an increase in identification performance, indicating that it has a potential clinical prospect for practical ASD severity diagnosis.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"162-174"},"PeriodicalIF":4.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10821533","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142918212","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}

{"title":"Low-Intensity Transcranial Ultrasound Stimulation Inhibits Epileptic Seizures in Motor Cortex by Modulating Hippocampus Neural Activity","authors":"Na Pang;Qianqian Wang;Jiamin Pei;Hailin Zhang;Yi Yuan;Jiaqing Yan","doi":"10.1109/TNSRE.2025.3525516","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3525516","url":null,"abstract":"Prior studies indicate that applying low-intensity transcranial ultrasound stimulation (TUS) to the hippocampus can suppress epileptic seizures. Nevertheless, it is unclear how TUS regulates hippocampal neural activity, and whether and how epileptic discharges in the motor cortex are suppressed by modulating hippocampal neural activity. To explore the answers of above questions, ultrasound was utilized to investigate the responses to the aforementioned inquiries by stimulating the hippocampus of mice with penicillin-induced epilepsy, while simultaneously recording the local field potentials (LFPs) in the hippocampus and the motor cortex (M1) throughout the experiment. The results showed that TUS: 1) reduced the amplitude and the strength of the <inline-formula> <tex-math>$boldsymbol {theta } $ </tex-math></inline-formula> frequency band in LFPs in the hippocampus and M1; 2) decreased the coupling strength of the <inline-formula> <tex-math>$boldsymbol {delta }$ </tex-math></inline-formula> - <inline-formula> <tex-math>$boldsymbol {gamma } $ </tex-math></inline-formula>, <inline-formula> <tex-math>$boldsymbol {theta } $ </tex-math></inline-formula> - <inline-formula> <tex-math>$boldsymbol {gamma }$ </tex-math></inline-formula> and <inline-formula> <tex-math>$boldsymbol {alpha } $ </tex-math></inline-formula> - <inline-formula> <tex-math>$boldsymbol {gamma } $ </tex-math></inline-formula> frequency bands in the hippocampus and M1; and 3) weakened the correlation of neural activity between the hippocampus and M1. The above results indicated that TUS effectively suppressed abnormal slow neural oscillations in the hippocampus, had a significant decoupling effect on slow-fast neural oscillations, and reduced the correlation of hippocampus-cortical neural activity. TUS of the hippocampus may be through the hippocampus-cortical circuits to suppress abnormal neural firing activity in M1.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"366-371"},"PeriodicalIF":4.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10820872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992967","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}

{"title":"Adaptive Modification in Agonist Common Drive After Combined Blood Flow Restriction and Neuromuscular Electrical Stimulation","authors":"Yi-Ching Chen;Chia-Chan Wu;Yeng-Ting Lin;Yueh Chen;Ing-Shiou Hwang","doi":"10.1109/TNSRE.2025.3525517","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3525517","url":null,"abstract":"Neuromuscular electrical stimulation (NMES) combined with blood flow restriction (BFR) has garnered attention in rehabilitation for its ability to enhance muscle strength, despite the potential to accelerate training-related fatigue. This study examined changes in force scaling capacity immediately following combined NMES and BFR, focusing on motor unit synergy between agonist pairs. Fifteen participants (<inline-formula> <tex-math>$23.3~pm ~1.8$ </tex-math></inline-formula> years) trained with combined BFR and NMES on the extensor carpi radialis longus (ECRL) muscle, with maximal voluntary contraction (MVC) of wrist extension, along with force and EMG in the ECRL and extensor carpi radialis brevis (ECRB), measured during a designate force-tracking before and after training. Factor analysis identified latent modes influencing motor unit coordination between the ECRB and ECRL. The results showed a significant decrease in MVC after training (<inline-formula> <tex-math>$text {p}lt 0.001$ </tex-math></inline-formula>). Post-test force fluctuations increased (p =0.031), along with a decrease in the mean inter-spike interval (M_ISI) in the ECRL (p =0.022). Factor analysis revealed an increase in the proportion of motor units (MUs) jointly regulated by the neural mode for both ECRB and ECRL, coupled with a decline in independently regulated MUs. Specifically, the proportion of MUs governed by the ECRL mode decreased, while those regulated by the ECRB mode increased. In conclusion, force generation capacity and force scaling are impaired after receiving combined NMES and BFR treatment. It involves redistribution of the common drive to MUs within two agonists, affecting the flexible coordination of muscle synergy and necessitating compensatory recruitment of MUs from the less fatigable agonist.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"372-379"},"PeriodicalIF":4.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10821494","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992970","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}

{"title":"Multiscale Intermuscular Coupling Analysis via Complex Network-Based High-Order O-Information","authors":"Chang Yu;Qingshan She;Michael Houston;Tongcai Tan;Yingchun Zhang","doi":"10.1109/TNSRE.2025.3525467","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3525467","url":null,"abstract":"Intermuscular coupling analysis (IMC) provides important clues for understanding human muscle motion control and serves as a valuable reference for the rehabilitation assessment of stroke patients. However, the higher-order interactions and microscopic characteristics implied in IMC are not fully understood. This study introduced a multiscale intermuscular coupling analysis framework based on complex networks with O-Information (Information About Organizational Structure). In addition, to introduce microscopic neural information, sEMG signals were decomposed to obtain motor units (MU). We applied this framework to data collected from experiments on three different upper limb movements. Graph theory-based analysis revealed significant differences in muscle network connectivity across the various upper limb movement tasks. Furthermore, the community division based on MU showed a mismatch between the distribution of muscle and motor neuron inputs, with a reduction in the dimension of motor unit control during multi-joint activity tasks. O-Information was used to explore higher-order interactions in the network. The analysis of redundant and synergistic information within the network indicated that numerous low-order synergistic subsystems were present while sEMG networks and MU networks were predominantly characterized by redundant information. Moreover, the graph features of macroscopic and microscopic network exhibit promising classification accuracy under KNN, showing the potential for engineering applications of the proposed framework.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"310-320"},"PeriodicalIF":4.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10821496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938188","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}

{"title":"Assessing Hand Function in Trans-Radial Amputees Wearing Myoelectric Hands: The Virtual Eggs Test (VET)","authors":"M. Controzzi;L. Angelini;P. Randi;P. Mucci;A. Mazzeo;R. Ferrari;E. Gruppioni;C. Cipriani","doi":"10.1109/TNSRE.2024.3524791","DOIUrl":"https://doi.org/10.1109/TNSRE.2024.3524791","url":null,"abstract":"The evaluation of hand function is of great importance to both clinical practice and biomedical research and is frequently evaluated by manual dexterity. Most of the assessment procedures evaluate the gross or the fine dexterity of the hand, but few of them are devoted to the assessment of both. We developed the Virtual Eggs Test (VET): it resembles the task of transporting fragile and robust objects, thus requiring both gross and fine dexterity. The test is composed of 11 Virtual Eggs that collapse if the grasping force exceeds their breaking thresholds, ranging from 0.4 N to 11.5 N. The test aims to transport each Virtual Egg over the barrier in the centre of the test platform without breaking it and as fast as possible. The metrics measured during the test are combined and provide two indexes that evaluate, respectively, gross and fine dexterity. We verify the concurrent validity and the construct validity of the VET with a target population of 30 trans-radial amputees wearing a myoelectric hand and the test-retest reliability on a control population of 35 healthy individuals. The results suggest the ability of the VET to assess hand function specifically in handling breakable objects, using both gross and fine dexterity over time. However, further research is needed to verify its correlation with other tests and the ability of amputees to perform activities of daily living.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"286-297"},"PeriodicalIF":4.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10819437","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938186","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}

{"title":"Hierarchical Contrastive Representation for Accurate Evaluation of Rehabilitation Exercises via Multi-View Skeletal Representations","authors":"Zhejun Kuang;Jingrui Wang;Dawen Sun;Jian Zhao;Lijuan Shi;Yusheng Zhu","doi":"10.1109/TNSRE.2024.3523906","DOIUrl":"https://doi.org/10.1109/TNSRE.2024.3523906","url":null,"abstract":"Rehabilitation training is essential for the recovery of patients with conditions such as stroke and Parkinson’s disease. However, traditional skeletal-based assessments often fail to capture the subtle movement qualities necessary for personalized care and are not optimized for scoring tasks. To address these limitations, we propose a hierarchical contrastive learning framework that integrates multi-view skeletal data, combining both positional and angular joint information. This integration enhances the framework’s ability to detect subtle variations in movement during rehabilitation exercises. In addition, we introduce a novel contrastive loss function specifically designed for regression tasks. This new approach yields substantial improvements over existing state-of-the-art models, achieving over a 30% reduction in mean absolute deviation on both the KIMORE and UIPRMD datasets. The framework demonstrates robustness in capturing both global and local movement characteristics, which are critical for accurate clinical evaluations. By precisely quantifying action quality, the framework supports the development of more targeted, personalized rehabilitation plans and shows strong potential for broad application in rehabilitation practices as well as in a wider range of motion assessment tasks.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"201-211"},"PeriodicalIF":4.8,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938189","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}