IEEE Transactions on Neural Systems and Rehabilitation Engineering最新文献

Accuracy and Precision of Wearable-Derived Gait Parameters: How these Affect the Performance of Models for Fall Prediction in the Elderly. 可穿戴衍生步态参数的准确性和精度：这些参数如何影响老年人跌倒预测模型的性能。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-20 DOI: 10.1109/TNSRE.2025.3623129

Zeyang Guan, Jinghao Cai, Jiachen Wang, Yibin Li, Rui Song, Damiano Zanotto, Sunil K Agrawal, Huanghe Zhang

{"title":"Accuracy and Precision of Wearable-Derived Gait Parameters: How these Affect the Performance of Models for Fall Prediction in the Elderly.","authors":"Zeyang Guan, Jinghao Cai, Jiachen Wang, Yibin Li, Rui Song, Damiano Zanotto, Sunil K Agrawal, Huanghe Zhang","doi":"10.1109/TNSRE.2025.3623129","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3623129","url":null,"abstract":"Wearable sensors are widely used to assess spatiotemporal gait parameters and their variability, which are critical for fall risk prediction. However, the impact of gait analysis accuracy and precision on fall risk prediction remains unexplored. This study collected gait data from 95 older adults using instrumented footwear on an instrumented walkway which is recognized as a system with gold standards during the 6-minute walking test. Participants were classified into fallers and non-fallers based on retrospective fall history (falls in the 6 months prior to completing the experiment), prospective fall occurrence (falls in the subsequent 6 months after completing the experiment), and a combination of both. Gait parameters and their variability were estimated using three algorithms: the conventional foot displacement method and two support vector regression (SVR) techniques. These features were used to develop fall risk prediction models with four machine learning classifiers: logistic regression, decision tree, support vector machine, and artificial neural network. Our findings demonstrate that the accuracy and precision of gait analysis algorithms significantly influences the estimation of gait parameters and their variability, directly impacting fall risk prediction performance. Using a support vector classifier, the area under the receiver operating characteristic curve (AUC) values for predicting retrospective falls, prospective falls, and either fall type increased from 0.79, 0.84, and 0.77 (conventional method) to 0.85, 0.89, and 0.83 (SVR). These findings show the importance of refining gait analysis accuracy and precision in future studies that aim to use wearable sensors for fall risk assessment in older adults.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145336939","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

Localization of Realistic Spatial Patches of Complex Source Activity in MEG and EEG. MEG和EEG复杂源活动的真实空间斑块定位。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-17 DOI: 10.1109/TNSRE.2025.3622587

Amita Giri, Lukas Hecker, John C Mosher, Amir Adler, Dimitrios Pantazis

{"title":"Localization of Realistic Spatial Patches of Complex Source Activity in MEG and EEG.","authors":"Amita Giri, Lukas Hecker, John C Mosher, Amir Adler, Dimitrios Pantazis","doi":"10.1109/TNSRE.2025.3622587","DOIUrl":"10.1109/TNSRE.2025.3622587","url":null,"abstract":"Accurate localization of neural sources in Magnetoencephalography (MEG) and Electroencephalography (EEG) is essential for advancing clinical and research applications in neuroscience. Traditional approaches like dipole fitting (e.g., MUSIC, RAP-MUSIC) are limited to discrete focal sources, while distributed source imaging methods (e.g., MNE, sLORETA) assume sources distributed across the cortical surface. These methods, however, often fail to capture sources with complex spatial extents, limiting their accuracy in realistic settings. To address these limitations, we introduce PATCH-AP, an enhanced version of the Alternating Projection (AP) method that effectively localizes both discrete and spatially extended sources. We evaluated PATCH-AP against leading source localization methods, including distributed source imaging techniques (MNE, sLORETA), traditional dipole fitting (AP), and recent extended source methods (Convexity-Champagne (CC), FLEX-AP). PATCH-AP consistently outperformed these methods in simulations, achieving lower Earth Mover's Distance (EMD) scores-a metric indicating closer alignment with the true source distribution. In tests with real MEG data from a face perception task and auditory task, PATCH-AP demonstrated high alignment with the fusiform face area and auditory cortex region. These results highlight PATCH-AP's potential to enhance source localization accuracy, promising significant advancements in neuroscience research and clinical diagnostics.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145312680","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

Estimating 3D Ground Reaction Forces During Daily Activities: A Reduced Sensor Setup and Virtual Pivot Point Approach. 在日常活动中估计三维地面反作用力：减少传感器设置和虚拟枢轴点方法。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-17 DOI: 10.1109/TNSRE.2025.3622734

Alessandro Castellaz, Frank J Wouda, Bert-Jan F Van Beijnum

{"title":"Estimating 3D Ground Reaction Forces During Daily Activities: A Reduced Sensor Setup and Virtual Pivot Point Approach.","authors":"Alessandro Castellaz, Frank J Wouda, Bert-Jan F Van Beijnum","doi":"10.1109/TNSRE.2025.3622734","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3622734","url":null,"abstract":"Ground reaction forces (GRF) during daily activities are critical for assessing joint loading, particularly in individuals with osteoarthritis (OA). Traditional GRF measurements rely on force plates, which restrict their use to laboratory environments. This study presents a novel method for estimating 3D GRF using a minimal sensor setup comprising three inertial measurement units (IMUs) and pressure insoles (PI), and exploiting the biomechanical concept of Virtual Pivot Point (VPP) to distribute the total GRF between the feet. Data were collected during various activities of daily living (ADL), including walking tasks, stair ascent/descent, and sit-to-stand movements. The proposed system demonstrates high accuracy, achieving relative root mean squared errors (rRMSE) below 15% and correlation coefficients exceeding 0.7 for all tasks, except sit-to-stand movements during Timed Up and Go test (TUG). This approach significantly reduces the sensor burden while maintaining performance comparable to more extensive setups. By combining the estimated 3D GRF with kinematics, joint loading can be estimated, enabling a portable setup for monitoring healthy subjects during ADL in real-world settings. The open-source MATLAB code and dataset are available in the 4TU Research Data repository [1].","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145312664","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

AdaptiveEdge: Adaptive Model Update for Motor-Intent Decoding with Knowledge Distillation and Efficient EMG Sensor System. AdaptiveEdge：基于知识蒸馏和高效肌电传感器系统的运动意图解码自适应模型更新。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-16 DOI: 10.1109/TNSRE.2025.3622132

Mustapha Deji Dere, Giwon Ku, Ji-Hun Jo, Saehyung Cheong, Sarfraz Ali, Boreom Lee

{"title":"AdaptiveEdge: Adaptive Model Update for Motor-Intent Decoding with Knowledge Distillation and Efficient EMG Sensor System.","authors":"Mustapha Deji Dere, Giwon Ku, Ji-Hun Jo, Saehyung Cheong, Sarfraz Ali, Boreom Lee","doi":"10.1109/TNSRE.2025.3622132","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3622132","url":null,"abstract":"Recent advancements in electromyogram (EMG)-based gesture decoding have enabled the development of active rehabilitation devices and enhanced human-machine interaction capabilities. While production-grade EMG sensors offer improved signal-to-noise ratios, their technical complexity necessitate innovative solutions to address inherent limitations. Additionally, EMG-based motor-intent decoders are prone to performance degradation due to factors such as fatigue, electrode shifts, and varying acquisition conditions. To address these challenges, we propose a low-cost EMG sensor grid alongside an advanced decoding strategy named AdaptiveEdge. This adaptive model update strategy integrates offline training with real-time on-device parameter updates, facilitating seamless adaptation to diverse EMG disturbance scenarios. Our comprehensive experiments demonstrated significant accuracy improvements: AdaptiveEdge yielded 10.18% higher accuracy (88.66%) when both offline and on-device update were utilized compared to 78.48% without offline training. Furthermore, AdaptiveEdge not only enhances decoding accuracy but also optimizes memory usage and energy consumption, making it particularly suitable for on-device applications such as neuroprosthetics. These advancements collectively pave the way for more effective and practical EMG-based devices, thereby improving human-machine interaction capabilities. The code associated with this study can be accessed here: https://github.com/deremustapha/AdpativeEdge.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145307948","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

Continuous Monitoring of Head Turns: Compliance, Kinematics, and Reliability of Wearable Sensing. 头部转动的连续监测：顺应性、运动学和可穿戴传感的可靠性。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-15 DOI: 10.1109/TNSRE.2025.3622072

Selena Y Cho, Leland E Dibble, Peter C Fino

{"title":"Continuous Monitoring of Head Turns: Compliance, Kinematics, and Reliability of Wearable Sensing.","authors":"Selena Y Cho, Leland E Dibble, Peter C Fino","doi":"10.1109/TNSRE.2025.3622072","DOIUrl":"10.1109/TNSRE.2025.3622072","url":null,"abstract":"Wearable devices offer objective mobility metrics for continuous monitoring but often focus on traditional measures like step count or gait speed. Other quantitative metrics such as head kinematics may provide valuable insights into mobility, balance, and sensory integration, given the head's central role in coordinating vestibular, ocular, and postural control. Yet, basic knowledge about capturing daily living head turns, including participant compliance, algorithms, normative data, and reliability, is not yet established. This study aimed to resolve this knowledge gap by capturing head and trunk movement kinematics over a 7-day period and to establish normative data in healthy adults. Participants (n = 24) wore head-mounted sensors for an average of 16.38 hours per day (SD = 4.43), completing 5,163 (SD = 1,466) head turns daily, with 72% occurring independently of trunk motion. Head turn amplitude (M = 58.18°, SD = 4.26°) was comparable to lumbar turns, while peak velocity was higher for head turns (M = 104.49°/s, SD = 12.08°/s). By the second day, all head turn metrics achieved excellent reliability (ICC > 0.9), supporting the feasibility of multi-day monitoring. Additionally, we examined the relationship between head motion and other mobility metrics and established recommendations for implementing similar protocols for capturing future studies, including the minimum number of days required for reliable data collection. Findings from this study provide a foundation for future multi-day continuous monitoring of head kinematics in both healthy and clinical populations.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145300151","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

Impaired functional brain-heart interplay sustains depressive symptomatology. 功能受损的脑-心相互作用维持抑郁症状。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-15 DOI: 10.1109/TNSRE.2025.3621769

Vincenzo Catrambone, Francesca Mura, Elisabetta Patron, Claudio Gentili, Gaetano Valenza

{"title":"Impaired functional brain-heart interplay sustains depressive symptomatology.","authors":"Vincenzo Catrambone, Francesca Mura, Elisabetta Patron, Claudio Gentili, Gaetano Valenza","doi":"10.1109/TNSRE.2025.3621769","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3621769","url":null,"abstract":"Depressive symptoms are a leading worldwide cause of mental disorders and disability, strongly affecting emotional processing and regulation. Leveraging recent evidence on the cardiogenic generation of emotion, we hypothesize that dysfunctional behavior in depressive symptomatology is sustained by impaired nervous-system-wise dynamics. Accordingly, this study aims to experimentally characterize functional Brain-Heart Interplay (BHI) patterns specific to emotional dysregulation and processing in subjects exhibiting depressive symptoms compared to healthy controls. Functional BHI has been estimated through a synthetic data generation model, separately modeling and quantifying ascending peripheral-to-central, and descending central-to-peripheral interaction in a time-resolved way. Results gathered from a cohort of 72 individuals indicate that depressive symptoms are associated with continuous efferent central-to-peripheral hyperactivity, particularly in neutral and negative valence conditioning, and afferent vagal-to-central hypoactivity. This hypoactivity seems to be specific to negative emotional processing. Moreover, the expected modulation of ascending interplay during emotional elicitation was detected in healthy controls only, whereas a descending central-to-peripheral modulation in response to emotional conditioning has been found associated to depressive symptomatology, for the first time. This study offers novel insights into the systemic investigation of the neurophysiological bases of depression, serving as an exemplary pathological manifestation of the dysfunctional brain-heart axis.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145300070","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

Evaluation of Lower-Limb Brunnstrom Recovery Stage via High-density Plantar Pressure and Global Fuzzy Granular Support Vector Machine. 基于高密度足底压力和全局模糊颗粒支持向量机的下肢Brunnstrom恢复阶段评价。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-14 DOI: 10.1109/TNSRE.2025.3620833

Qiangqiang Chen, Xiaoyu Chen, Linjie He, Taiyang Liu, Lingyu Liu, Lingjing Jin, Chen Chen, Bin Yin, Wei Chen, Wenting Qin, Hongyu Chen

{"title":"Evaluation of Lower-Limb Brunnstrom Recovery Stage via High-density Plantar Pressure and Global Fuzzy Granular Support Vector Machine.","authors":"Qiangqiang Chen, Xiaoyu Chen, Linjie He, Taiyang Liu, Lingyu Liu, Lingjing Jin, Chen Chen, Bin Yin, Wei Chen, Wenting Qin, Hongyu Chen","doi":"10.1109/TNSRE.2025.3620833","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3620833","url":null,"abstract":"Low interrater reliability and inefficiency are present in the subjective clinical Brunnstrom recovery stage (BRS-LL) assessment for stroke patients. Although wearable technology offers solutions, existing BRS-LL automatic assessment studies face a trade-off between accuracy and ease of use: multimodal systems are accurate, but complex, while single-modal methods are simpler but less accurate. To address the complexity of sensor deployment, we develop flexible high-density (HD) plantar pressure (PP) sensing insoles (48 units) that naturally integrate into regular shoes without external modules. PP data are collected from 52 stroke patients. The high-dimensional 297 PP features are extracted to enhance signal representation. A global fuzzy granular support vector machine (GFGSVM) algorithm is proposed to overcome the accuracy limitations of unimodal studies. The results show that the increased PP sensing density from 12 to 48 units enhances feature-BRS-LL correlations (69% improved by over 20%) and BRS-LL classification accuracy by 8.1%-11.6%, highlighting the advantages of HD PP sensor. Through leave-one-subject-out cross-validation, GFGSVM achieves an accuracy of 95.9% sample level and 98.1% individual patient level, surpassing five popular evaluation algorithms by 12.8%-26.2%. The system's accuracy exceeds single-modal (+9.1%) and multimodal studies (+1.71%) by utilizing only a pair of HD PP insoles with GFGSVM. Overall, this study provides an efficient BRS-LL evaluation scheme that combines both portability for clinical applications and high assessment accuracy, effectively resolving the trade-off and offering an effective tool for long-term monitoring and screening of stroke patients.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145292166","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

Immediate Modulations of Cheek Acupuncture on Brain Oscillations and Connectivity in Individuals with Chronic Pain. 颊针对慢性疼痛患者脑振荡和连通性的即时调节。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-14 DOI: 10.1109/TNSRE.2025.3621122

Xintong Chen, Shanbao Tong, Yi Zhu, Tao Xu, Xiaoli Guo, Wenhui Zhong

{"title":"Immediate Modulations of Cheek Acupuncture on Brain Oscillations and Connectivity in Individuals with Chronic Pain.","authors":"Xintong Chen, Shanbao Tong, Yi Zhu, Tao Xu, Xiaoli Guo, Wenhui Zhong","doi":"10.1109/TNSRE.2025.3621122","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3621122","url":null,"abstract":"Chronic pain challenges global healthcare due to its complexity and the limitations of current treatments. Cheek acupuncture (CA), which targets specific acupoints on the cheek based on the biological holographic model, has shown promise for immediate pain relief. Despite its efficacy across various clinical studies, the mechanisms underlying its analgesic effects remain unclear. In this study, through resting electroencephalography analysis of 37 participants with chronic pain before, during, and after CA therapy, we investigated the electrophysiological modulations underlying the immediate analgesic effects of CA, with further comparison to an additional 13 participants with chronic pain undergoing sham acupuncture to exclude the potential placebo effects. Compared with sham acupuncture, CA demonstrated a significant immediate analgesic effect for chronic pain. Meanwhile, CA also triggered significant modulations on brain oscillations and their synchrony, which are distinct at different acupuncture procedures. Specifically, needle insertion of CA significantly reduced theta oscillations and enhanced gamma oscillations, suggesting a downregulation of hyperactive thalamic activity and an improvement of feedforward communication in pain processing; while after needle withdrawal, beta-band synchrony within the frontal lobe was decreased, indicating an improvement in the efficiency of feedback regulatory information transmission by reducing excessive connections. These modulations together improve the integration of nociceptive and contextual information in pain processing. Notably, the reduced theta oscillations were significantly correlated with the magnitude of pain relief and exerted a weak mediating effect in analgesia. Our findings provide electrophysiological insights into the immediate analgesic mechanism of CA.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145292186","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

Graph Signal Entropy for Analyzing Functional Brain Abnormalities of Alzheimer's Disease Patients. 图信号熵分析阿尔茨海默病患者脑功能异常。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-13 DOI: 10.1109/TNSRE.2025.3620444

Rui Pu, Xiaoying Song, Li Chai

{"title":"Graph Signal Entropy for Analyzing Functional Brain Abnormalities of Alzheimer's Disease Patients.","authors":"Rui Pu, Xiaoying Song, Li Chai","doi":"10.1109/TNSRE.2025.3620444","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3620444","url":null,"abstract":"A majority of research shows that the brain complexity of Alzheimer's disease (AD) patients is smaller than that of healthy controls (HCs). In this paper, we propose a novel method based on graph signal entropy to investigate the complexity of functional brain networks in AD patients. By using a spectral graph wavelet filter to decompose the subjects' BOLD signal, we generate distinct functional brain networks for each graph frequency band. We then use the multivariate dispersion entropy to examine the abnormal complexity of AD patients across different graph frequency bands. Experimental results reveal that in the low and mid-frequency bands, the brain complexity of AD patients is generally larger than that of HCs, which challenges the conventional understanding that AD is consistently associated with reduced complexity. Moreover, widely reported abnormal brain regions in AD, such as the hippocampus and parahippocampal gyrus, exhibit significant differences only at specific frequency bands, indicating the necessity of frequency-resolved analysis. These findings uncover new characteristics of functional brain networks in AD patients and provide deeper insights into the disease's complex neural mechanisms.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145285978","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

Human Locomotion Implicit Modeling Based Real-Time Gait Phase Estimation. 基于实时步态相位估计的人体运动隐式建模。

IF 5.2 2区医学

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-10-13 DOI: 10.1109/TNSRE.2025.3621076

Yuanlong Ji, Xingbang Yang, Ruoqi Zhao, Qihan Ye, Quan Zheng, Yubo Fan

{"title":"Human Locomotion Implicit Modeling Based Real-Time Gait Phase Estimation.","authors":"Yuanlong Ji, Xingbang Yang, Ruoqi Zhao, Qihan Ye, Quan Zheng, Yubo Fan","doi":"10.1109/TNSRE.2025.3621076","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3621076","url":null,"abstract":"Gait phase estimation based on inertial measurement unit (IMU) signals facilitates precise adaptation of exoskeletons to individual gait variations. However, challenges remain in achieving high accuracy and robustness, particularly during periods of terrain changes. To address this, we develop a gait phase estimation neural network based on implicit modeling of human locomotion, which combines temporal convolution for feature extraction with transformer layers for multi-channel information fusion. A channel-wise masked reconstruction pre-training strategy is proposed, which first treats gait phase state vectors (a three-dimensional representation composed of a polar-encoded phase value and its first-order time derivative) and IMU signals as joint observations of human locomotion, thus enhancing model generalization. Experimental results on datasets involving level walking, stair ascent/ descent, slope ascent/descent, and transitions between level ground and these terrains demonstrate that the proposed method outperforms existing baseline approaches, achieving a gait phase RMSE of 2.729 ± 1.071% and gait phase rate MAE of 0.037 ± 0.016% under stable terrain conditions with a look-back window of 2 seconds, and a phase RMSE of 3.215 ± 1.303% and rate MAE of 0.050 ± 0.023% under terrain transitions. Hardware validation with one subject (N = 1) wearing a hip exoskeleton further confirms that the algorithm can reliably identify gait cycles and key events, adapting to various continuous motion scenarios. This work lays the groundwork for more adaptive exoskeleton systems capable of robust real-time gait assistance in varied and dynamic environments.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"PP ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145285993","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