IEEE Transactions on Neural Systems and Rehabilitation Engineering最新文献

{"title":"Acoustic Motor Cortex Stimulation Enhances the Descending Analgesic Pathway to Alleviate Chronic Pain in Mice","authors":"Weiliang Fu;Guanghua Yang;Jin Ke;Tianwen Huang;Jinpeng Li;Xiaoyan Chen;Junjie Zou;Zhengrong Lin;Lili Niu;Yongjie Li","doi":"10.1109/TNSRE.2025.3564033","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3564033","url":null,"abstract":"Chronic pain poses considerable health risks, necessitating the development of effective treatments. Physical modulation of the motor cortex has demonstrated promise for pain relief; however, existing methods require invasive electrode implantation or have limited spatial resolution. Therefore, we developed a non-invasive, high-precision acoustic motor cortex stimulation (aMCS) system to alleviate chronic pain and explore its mechanisms. We developed a wearable aMCS system and employed the spared nerve injury (SNI) method to establish a mouse model of chronic pain. The model mice underwent aMCS with different acoustic parameters, and their pain behaviors were systematically evaluated. Subsequently, we established a long-term spinal cord two-photon system to monitor the effects of aMCS on spinal cord dorsal horn (SCDH) neuronal activity. Next, TRAP2-tdTomato mice were used to examine the effects of aMCS on the motor cortex and other regions of the descending analgesic pathway. Finally, we conducted magnetic resonance imaging, histology, and temperature monitoring to evaluate the safety of aMCS. aMCS with specific parameters significantly ameliorated pain behaviors in a mouse model of chronic pain. Two-photon calcium imaging indicated that aMCS reduced the intensity of neuronal activity in SCDH. Activity mapping in TRAP2-tdTomato mice revealed that aMCS enhanced neuronal activity in the primary motor cortex and zona incerta while diminishing it in the lateral periaqueductal gray and SCDH. Safety assessments confirmed the absence of deleterious effects on the stimulated region. aMCS provides a novel, non-invasive and effective approach to alleviating chronic pain by potentially enhancing the descending analgesic pathway.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1600-1610"},"PeriodicalIF":4.8,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10975825","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908396","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":"Analysis of Disease-Induced Changes in Human Locomotor Patterns Through the Co-Joint Synergistic Attention Algorithm","authors":"Jingyao Chen;Chen Wang;Zeng-Guang Hou;Pingye Deng;Liang Peng;Pu Zhang;Ningcun Xu","doi":"10.1109/TNSRE.2025.3563466","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3563466","url":null,"abstract":"Objective: Aiming to quantify and analyze disease-induced alterations in human movement, we explored the co-joint synergy patterns in locomotion through a vision-based co-joint synergistic attention algorithm. Methods: We recruited 30 participants (including 15 post-stroke patients and 15 healthy individuals) and extracted their 3D visual motor data for the joint feature coupling by a serial attention module. And we designed a dual-stream classification module for preclassification based on the spatio-temporal characteristics of the data. Then we extracted the important co-joint synergy patterns by a looping mask module and the co-joint synergy variability score. Results: Through the co-joint synergistic attention algorithm, we found significant differences in joint synergy patterns between post-stroke patients and healthy individuals during upper and lower limb tasks. Furthermore, we obtained quantitative results on the effect of specific diseases on co-joint synergy patterns among healthy individuals and patients. The validity of the result was verified by comparing with the commonly used Non-negative Matrix Factorization (NMF) and the Muscle Synergy Fractionation (MSF) methods. Conclusion: Specific diseases can cause changes in human movement patterns, and by the co-joint synergistic attention algorithm we can analyze the alterations in joint synergies and also quantify the importance of different synergy groups. Significance: This research proposes a new approach for identifying specific co-joint synergy patterns arising from disease-altered biomechanics, which provides a new targeted protocol for the rehabilitation process.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1695-1706"},"PeriodicalIF":4.8,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10974996","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925100","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":"What Can N100 and ASSR Assess in Patients With Disorders of Consciousness?","authors":"Yuzhen Chen;Hao Li;Qianqian Ge;Xiaoyang Kang;Hui Zheng;Shangen Zhang;Xiaogang Chen;Jianghong He;Xiaorong Gao","doi":"10.1109/TNSRE.2025.3563593","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3563593","url":null,"abstract":"Objective: Auditory Evoked Potentials (AEP), particularly the N100 component and the auditory steady-state response (ASSR), have been utilized in the clinical assessment of patients with Disorders of Consciousness (DOC). However, the specific utility of these measures remains debated across studies. Methods: To clarify the roles of N100 and ASSR in evaluating auditory function and levels of consciousness in DOC patients, we recorded N100 and ASSR responses in 30 DOC patients and assessed their significance at the individual level through statistical analyses. Results: Our findings indicate that, compared to N100, the significance of the ASSR response appears to be a more reliable marker of auditory function. However, neither N100 nor ASSR, at both response and microstate levels, could effectively distinguish between patients diagnosed with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). Additionally, we validated the role of ASSR using a portable EEG device in an independent cohort of 30 patients. Conclusion: In summary, our results suggest that ASSR holds promise for assessing auditory function in DOC patients, but its utility in differentiating levels of consciousness may require further consideration. Significance: These findings offer valuable insights for clinicians and neuroscientists in selecting and designing objective tools for DOC assessment.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1529-1538"},"PeriodicalIF":4.8,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10975008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888341","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":"Development and Validation of the Novel Exergame-Integrated Robotic Stepper Device for Seated Lower Limb Rehabilitation","authors":"Beycan Emre;Narayan Ashwin;Ofori Seyram;L. W. R. Joshua;Zhao Weihao;Haoyong Yu","doi":"10.1109/TNSRE.2025.3563191","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3563191","url":null,"abstract":"Seated rehabilitation is essential in early-stage recovery for patients who can sit but cannot stand or walk. Robotic-based lower limb rehabilitation provides precise, task-specific training for recovery, but its application in seated exercises remains limited, creating a significant gap in early-stage rehabilitation. This study presents a novel exergame-integrated robotic stepper for seated bilateral and multi-joint lower limb rehabilitation. Twenty healthy participants performed seated stepping exercises across eight modes: passive (G0), three-level assistive(G1-G3), active (G4), and three-level resistive (G5-G7). Results demonstrated a strong correlation between the stepper’s tilt angle and the ankle, knee, and hip joints. The device maintained consistent ROM for these joints across all modes, ensuring reliable joint engagement regardless of resistance or assistance levels. Weight shift increased progressively from passive (G0) to high resistance (G7), with higher shifts observed as assistance decreased and resistance increased. In assistive modes, a significant increase of 47.16% in weight shift was observed at low assistance (G3) (p <0.0167). In resistive modes, weight shift increased significantly by 86.08% in medium resistance (G6) and by 129.7% at high resistance (G7) (p <0.0167). Muscle activation significantly increased progressively from passive (G0) to high resistance (G7), with greater activations observed as assistance levels decreased and resistance levels increased (p <0.0083). These findings indicate that robotic stepper can be a versatile tool in progressive stroke rehabilitation, effectively adapting to different rehabilitation needs, from early-stage support to muscle strengthening.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1643-1652"},"PeriodicalIF":4.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10973188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924961","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":"A Multi-Level Integrated EEG-Channel Selection Method Based on the Lateralization Index","authors":"Junhong Luo;Qing Liu;Pengrui Tai;Guanglin Li;Yongcheng Li","doi":"10.1109/TNSRE.2025.3563416","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3563416","url":null,"abstract":"The importance of optimizing channel selection for portable brain-computer interface (BCI) technology is increasingly recognized. Effective channel selection reduces computational load and enhances user experience by making BCI systems more comfortable and easier to use. A significant challenge lies in reducing the number of electrodes without compromising decoding accuracy. Although some methods have been proposed in previous studies, these often increase computational load and overlook the importance of channel selection across different subjects. Therefore, we propose a novel Multi-level Integrated EEG-Channel Selection method based on the Lateralization Index (MLI-ECS-LI). This method leverages the lateralization index in selecting important channels and can achieve the channel selection for the cross-tasks and the cross-subjects scenarios. To evaluate the effectiveness of the proposed method, the time and frequency domain features from selected channels were extracted. Three widely used classifiers, Least Squares Support Vector Machine (LSSVM), Random Forest (RF), and Support Vector Machine (SVM) were used to classify movement types based on these features. Compared to the conventional condition (C1-C6), the average decoding accuracies across 21 healthy subjects demonstrated an improved performance of 6.6%, 4.9%, 6.9% (LSSVM); 3.8%, 2.8%, 4.5%(RF); and 7.6%, 5.6%, 9.2%(SVM) via using the channels selected from the conditions of the single task, the cross-tasks, and the cross-subjects scenarios, respectively. These results demonstrated the potential of the proposed method in improving the utility of the portable Motor Imagery Brain-Computer Interface (MI-BCI) and effectiveness in practical applications.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1586-1599"},"PeriodicalIF":4.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10973187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908395","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":"Topology-Guided Graph Masked Autoencoder Learning for Population-Based Neurodevelopmental Disorder Diagnosis","authors":"Yueying Li;Xiaotong Zhang;Shihan Guan;Guolin Ma;Youyong Kong","doi":"10.1109/TNSRE.2025.3562662","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3562662","url":null,"abstract":"Exploring the pathogenic mechanisms of brain disorders within population is an important research in the field of neuroscience. Existing methods either combine clinical information to assist analysis or use data augmentation for sample expansion, ignoring the mining of individual information and the exploration of inter-individual associations in population. To solve these problems, this work proposes a novel approach for detecting abnormal neural circuits associated with brain diseases, named Topology-guided Graph Masked autoencoder Learning method (TGML), which focuses on individual representation and intra-population association, to achieve the effective diagnosis of brain diseases within the population. Concretely, the TGML comprises 1) the <underline>t</u>opology-<underline>g</u>uided <underline>g</u>roup <underline>a</u>ssociation <underline>m</u>odule (T<inline-formula> <tex-math>${G}^{{2}}$ </tex-math></inline-formula>AM) that reconstructs the edges and update the initial population graph, 2) the <underline>i</u>ntra-<underline>p</u>opulation <underline>i</u>nteraction <underline>m</u>asked <underline>a</u>uto<underline>e</u>ncoder network (IPI_MAE) captures the discriminative characteristics of subjects based on the novel Masked Autoencoder, which incorporates traditional masked autoencoders into a task-related process. The proposed method is evaluated on two neurodevelopmental disorder diagnosis tasks of Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). The results show that the proposed TGML achieves significant improvements and surpasses the state-of-the-art methods.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1550-1561"},"PeriodicalIF":4.8,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10971381","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888430","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":"An Interventional Brain-Computer Interface for Long-Term EEG Collection and Motion Classification of a Quadruped Mammal","authors":"Sining Li;Gan Liu;Fan Feng;Ziqing Chang;Wenyu Li;Feng Duan","doi":"10.1109/TNSRE.2025.3562922","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3562922","url":null,"abstract":"Brain-computer interfaces (BCI) acquire electroencephalogram (EEG) signals to effectively address postoperative motor dysfunction in stroke patients by discerning their motor intentions during significant movements. Traditionally, noninvasive BCIs have been constrained by limitations in their usage environments; whereas, invasive BCIs damage neural permanently. Therefore, we proposed a novel interventional BCI, in which electrodes are implanted along the veins into the brain to acquire intracerebral EEG signals without an open craniotomy. We collect EEG signals from the primary motor cortex in the superior sagittal sinus of sheep during three different significant movements: laying down; standing; and walking. The first three month data are used to train the neural network, and The fourth month of data were used to validate. The deep learning model achieved an 86% accuracy rate in classifying motion states in validation. Furthermore, the results of the power spectral density (PSD) show that the signal power in the main frequency band did not decrease over a period of five months, which demonstrates that the interventional BCI has the ability to effectively capture EEG signals over long periods of time.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1633-1642"},"PeriodicalIF":4.8,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10972026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925273","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":"Enhanced Brain Functional Interaction Following BCI-Guided Supernumerary Robotic Finger Training Based on Sixth-Finger Motor Imagery","authors":"Shuaifei Huang;Yuan Liu;Zhuang Wang;Wenlai Wu;Jun Guo;Weiguo Xu;Dong Ming","doi":"10.1109/TNSRE.2025.3562700","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3562700","url":null,"abstract":"Supernumerary robotic finger (SRF) has shown unique advantages in the field of motor augmentation and rehabilitation, while the development of brain computer interface (BCI) technology has provided the possibility for direct control of SRF. However, the neuroplasticity effects of BCI-actuated SRF (BCI-SRF) training based on the “six finger” motor imagery paradigm are still unclear. This study recruited 20 healthy right-handed participants and randomly assigned them to either a BCI-SRF training group or a sham SRF training group. During the testing phase before and after 4 weeks of training, all participants were tested for SRF-finger opposition sequence behavior, resting state fMRI (rs-fMRI), and task-based fMRI (tb-fMRI). The results showed that compared with the Sham group, the BCI-SRF group improved the accuracy rate of the SRF-finger opposition sequence by 132%. The activation analysis of tb-fMRI before and after training revealed a significant increase in left middle frontal gyrus only in the BCI-SRF group. In addition, the BCI-SRF group showed an increase in FC between the right primary motor cortex and left cerebellum inferior lobe, as well as between the left middle frontal gyrus and the right precuneus lobe after training, while there was no significant change in the Sham group. In addition, only the BCI-SRF group showed a significant increase in clustering coefficients after training. Moreover, the increase in the clustering coefficients of the two groups is positively correlated with the improvement of the accuracy of the SRF-finger opposition sequences. These results indicate that the integration of BCI and SRF significantly regulates the functional interaction between motor learning and cognitive imagery brain regions, enhances the integration and processing ability of brain networks for local information, and improves human-machine interaction behavioral performance.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1519-1528"},"PeriodicalIF":4.8,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10971363","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888342","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":"Enhancing Neural Activation in Older Adults: Action Observation-Primed Swallowing Imagery Reveals Age-Related Connectivity Patterns","authors":"Hao Xiong;Jin-Jin Chen;Meng-Huan Wang;Lu Zhang;Feng Lin","doi":"10.1109/TNSRE.2025.3562573","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3562573","url":null,"abstract":"Aging-related swallowing decline, known as presbyphagia, significantly increases the risk of dysphagia and aspiration pneumonia in older adults. Enhancing cortical activation and functional connectivity through non-invasive methods is crucial for improving swallowing function. This study investigates the use of action observation (AO) as a priming method to enhance motor imagery (MI) for promoting swallowing-related cortical activity. A total of 22 healthy young adults and 20 healthy older adults were recruited. Participants completed two swallowing imagery tasks: an 8-minute AO-primed task and an 8-minute unprimed task. Functional near-infrared spectroscopy was used to measure changes in oxyhemoglobin concentration as an indicator of cortical activation. Corrected imaginary phase-locking values (ciPLVs) were calculated to estimate functional connectivity between brain regions. In young adults, AO-primed tasks showed widespread bilateral activation in the sensorimotor cortex, supplementary motor area (SMA), and visual cortex, while unprimed tasks activated only the right inferior frontal gyrus. In older adults, AO-primed tasks activated the left sensorimotor cortex, SMA, and visual cortex, but unprimed tasks did not result in any significant cortical activation. Despite both age groups recruiting similar cortical networks, older adults exhibited reduced connectivity, particularly in the prefrontal-sensorimotor pathways during AO-primed tasks. AO-priming enhances cortical activation and connectivity in both young and older adults during swallowing imagery tasks. However, older adults demonstrate weaker neural connectivity, suggesting that age-related cortical decline may limit the effectiveness of such interventions. AO-primed MI may serve as a promising strategy for improving swallowing function in older populations.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1574-1584"},"PeriodicalIF":4.8,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10971424","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896117","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":"Flexor Synergy Assessment and Therapy for Persons With Stroke Using the ULIX Low Impedance Robot","authors":"Shawn J. DiRocco;Rafael Casas;Seraphina A. Culp;Peter S. Lum","doi":"10.1109/TNSRE.2025.3562527","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3562527","url":null,"abstract":"The flexor synergy after stroke results in involuntary activation of distal muscles when lifting the shoulder against gravity. This contributes to impaired ability to perform activities of daily living. Robotic exoskeletons can be useful in assessing the strength of the synergy and applying therapy modes that promote improved movement patterns. In this study, we evaluated 16 chronic stroke patients using the Ultra Low Impedance eXoskelton (ULIX). The subjects performed two synergy assessment tasks, elbow extension and hand opening while holding shoulder flexion at greater than 70 degrees with various gravity support levels. Joints not part of the tasks were locked in place. During the assessment tasks, increasing gravity support resulted in more elbow extension and reduced grip force; however, EMG contraction ratios of distal muscles compared to deltoids increased when gravity support was increased. A free cup reaching task was performed using several proposed therapy modes. During the cup reaching task, the therapy modes increased range of motion and improved the shoulder-elbow kinematic coordination compared with gravity support alone. There was a strong correlation between synergy expression in the elbow extension task and performance of the cup reaching task. Isolating movement to shoulder flexion and elbow extension during the assessment task resulted in better elbow extension than in the cup reaching task where all joints were free to rotate.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"1509-1518"},"PeriodicalIF":4.8,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10969986","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888340","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}