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Ma Y, Wang L, Li T, Zhang J, Funahashi S, Wu J, Wang X, Zhang K, Liu T, Yan T. Disrupted coordination between primary and high-order cognitive networks in Parkinson's disease based on morphological and functional analysis. Brain Struct Funct 2025; 230:48. [PMID: 40208328 DOI: 10.1007/s00429-025-02909-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Accepted: 03/21/2025] [Indexed: 04/11/2025]
Abstract
Patients with Parkinson's disease (PD) exhibit structural and functional alterations in both primary and high-order cognitive networks, but the interactions within aberrant functional networks and relevant structural foundation remains unexplored. In this study, the functional networks (FN) and the morphometric similarity networks (MSN) were constructed respectively based on the time-series data and gray matter volume from the MRI data of PD patients and controls. The efficiency, average controllability and k-shell values of the FN and MSN were calculated to evaluate their ability of information transmission and identify structural and functional abnormalities in PD. The abnormal regions were categorized into five types: regions with MSN abnormalities, regions with FN abnormalities, regions with both MSN and FN abnormalities, regions with abnormalities only in MSN but not in FN and regions with abnormalities only in FN but not in MSN. Further, the dynamic causal model (DCM) was used to evaluate the causal relationship of information flow between the identified regions. In the network property analysis of the FN, PD patients showed decreased global efficiency and connectivity in the visual network (VIS) and increased global efficiency in higher-order cognitive networks, including the ventral attention network (VAN), default mode network (DMN), and the limbic network (LIM) but no difference in MSN. In the DCM analysis of the regions, PD patients exhibited increased excitatory transition from the visual areas to the superior frontal gyrus, whereas had disturbed information flow from the visual areas to the insula and the orbitofrontal cortex. These findings suggest changes in structural and functional brain of PD patients, and advance our understanding of PD pathogenesis from different neural dimensions.
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Affiliation(s)
- Yunxiao Ma
- School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Li Wang
- School of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100081, China.
| | - Ting Li
- College of Software, Taiyuan University of Technology, Taiyuan, 030024, China
| | - Jian Zhang
- School of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100081, China
| | - Shintaro Funahashi
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Jinglong Wu
- School of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100081, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100081, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100081, China
| | - Tiantian Liu
- School of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100081, China.
| | - Tianyi Yan
- School of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100081, China
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Esmaeili SV, Esmaeili R, Shakerian M, Dehghan H, Yazdanirad S, Heidari Z, Habibi E. A method for rapid assessment of visual ergonomics and lighting conditions (RAVEL): An in-depth development and psychometrics study. Work 2025; 80:441-460. [PMID: 39240610 DOI: 10.3233/wor-240052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/07/2024] Open
Abstract
BACKGROUND In workplaces heavily reliant on visual tasks, various factors can significantly influence an individual's performance, necessitating the use of reliable tools to identify and mitigate these factors. OBJECTIVE This study aimed to develop a swift assessment method for visual ergonomics and lighting conditions, evaluating its validity in real-world scenarios. METHODS The questionnaire's content validity was determined by a panel of experts using the content validity ratio (CVR) and content validity index (CVI). Construct validity was assessed through exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and latent class analysis (LCA). Internal consistency was measured using Cronbach's alpha coefficient. The RAVEL index, derived from the calculated effect coefficients of items, classified total scores through receiver operator curves (ROCs). RESULTS The rapid assessment method, comprising two parts with 30 items, demonstrated acceptable reliability with CVR, CVI, and Cronbach's alpha coefficient (α) at 0.75, 0.87, and 0.896, respectively. The EFA on the first part's 22 items identified three factors, confirmed by CFA. The LCA on the second part's eight items revealed that a two-class model best fit the data, with Bayesian information criterion (BIC) = 24249, 17, Akaik information criterion (AIC) = 2179.89, and an entropy R-squared of 0.83, indicating appropriate subject classification based on the model. The RAVEL score was categorized into three levels, with optimal cut points of 55 and 63. CONCLUSIONS In conclusion, the study demonstrated that this method based on visual ergonomics serves as a rapid and reliable tool for assessing visual ergonomic risks of display users in the workplace.
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Affiliation(s)
- Sayed Vahid Esmaeili
- Student Research Committee, Department of Occupational Health and Safety Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
- Student Research Committee, Department of Occupational Health and Safety Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Reza Esmaeili
- Student Research Committee, Department of Occupational Health and Safety Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mahnaz Shakerian
- Department of Occupational Health and Safety Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Habibollah Dehghan
- Department of Occupational Health and Safety Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Saeid Yazdanirad
- School of Health, Shahrekord University of Medical Science, Shahrekord, Iran
| | - Zahra Heidari
- Department of Biostatistics and Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Ehsanollah Habibi
- Department of Occupational Health and Safety Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
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Zhang C, Zhou ZJ, Wang LY, Ran LH, Hu HM, Zhang X, Xu HQ, Shi JP. Robust fatigue markers obtained from muscle synergy analysis. Exp Brain Res 2024; 242:2391-2404. [PMID: 39136723 DOI: 10.1007/s00221-024-06909-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2024] [Accepted: 08/03/2024] [Indexed: 09/26/2024]
Abstract
This study aimed to utilize the nonnegative matrix factorization (NNMF) algorithm for muscle synergy analysis, extracting synergy structures and muscle weightings and mining biomarkers reflecting changes in muscle fatigue from these synergy structures. A leg press exercise to induce fatigue was performed by 11 participants. Surface electromyography (sEMG) data from seven muscles, electrocardiography (ECG) data, Borg CR-10 scale scores, and the z-axis acceleration of the weight block were simultaneously collected. Three indices were derived from the synergy structures: activation phase difference, coactivation area, and coactivation time. The indicators were further validated for single-leg landing. Differences in heart rate (HR) and heart rate variability (HRV) were observed across different fatigue levels, with varying degrees of disparity. The median frequency (MDF) exhibited a consistent decline in the primary working muscle groups. Significant differences were noted in activation phase difference, coactivation area, and coactivation time before and after fatigue onset. Moreover, a significant correlation was found between the activation phase difference and the coactivation area with fatigue intensity. The further application of single-leg landing demonstrated the effectiveness of the coactivation area. These indices can serve as biomarkers reflecting simultaneous alterations in the central nervous system and muscle activity post-exertion.
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Affiliation(s)
- Chen Zhang
- Research Center of Exercise Capacity Assessment and Promotion, School of Sports Science and Physical Education, Northeast Normal University, Changchun, Jilin Province, China
| | - Zi-Jian Zhou
- Research Field of Medical Instruments and Bioinformation Processing, College of Instrumentation & Electrical Engineering, Jilin University, Changchun, Jilin Province, China
| | - Lu-Yi Wang
- Research Center of Exercise Capacity Assessment and Promotion, School of Sports Science and Physical Education, Northeast Normal University, Changchun, Jilin Province, China
| | - Ling-Hua Ran
- Ergonomics Standardization Research Field, China National Institute of Standardization, Beijing, China
- Key Laboratory of Human Factors and Ergonomics for State Market Regulation, China National Institute of Standardization, Beijing, China
| | - Hui-Min Hu
- Ergonomics Standardization Research Field, China National Institute of Standardization, Beijing, China
- Key Laboratory of Human Factors and Ergonomics for State Market Regulation, China National Institute of Standardization, Beijing, China
| | - Xin Zhang
- Ergonomics Standardization Research Field, China National Institute of Standardization, Beijing, China
- Key Laboratory of Human Factors and Ergonomics for State Market Regulation, China National Institute of Standardization, Beijing, China
| | - Hong-Qi Xu
- Research Center of Exercise Capacity Assessment and Promotion, School of Sports Science and Physical Education, Northeast Normal University, Changchun, Jilin Province, China.
| | - Ji-Peng Shi
- Research Center of Exercise Capacity Assessment and Promotion, School of Sports Science and Physical Education, Northeast Normal University, Changchun, Jilin Province, China
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Ji H, Chen Z, Qiao Y, Yan J, Chen G, Luo Q, Cui L, Zong Y, Xie Q, Niu CM. Hemodynamic activity is not parsimoniously tuned to index-of-difficulty in movement with dual requirements on speed-accuracy. Front Hum Neurosci 2024; 18:1398601. [PMID: 39045507 PMCID: PMC11263286 DOI: 10.3389/fnhum.2024.1398601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Accepted: 06/24/2024] [Indexed: 07/25/2024] Open
Abstract
Background Reaching movements are crucial for daily living and rehabilitation, for which Fitts' Law describes a speed-accuracy trade-off that movement time increases with task difficulty. This study aims to investigate whether cortical activation in motor-related areas is directly linked to task difficulty as defined by Fitts' Law. Understanding this relationship provides a physiological basis for parameter selection in therapeutic exercises. Methods Sixteen healthy subjects performed 2D reaching movements using a rehabilitation robot, with their cortical responses detected using functional near-infrared spectroscopy (fNIRS). Task difficulty was manipulated by varying target size and distance, resulting in 3 levels of index-of-difficulty (ID). Kinematic signals were recorded alongside cortical activity to assess the relationship among movement time, task difficulty, and cortical activation. Results Our results showed that movement time increased with ID by 0.2974s/bit across all subjects (conditional r2 = 0.6434, p < 0.0001), and all subjects showed individual trends conforming Fitts' Law (all p < 0.001). Neither activation in BA4 nor in BA6 showed a significant correlation with ID (p > 0.05), while both the target size and distance, as well as the interaction between them, showed a significant relationship with BA4 or BA6 activation (all p < 0.05). Conclusion This study found that although kinematic measures supported Fitts' Law, cortical activity in motor-related areas during reaching movements did not correlate directly with task difficulty as defined by Fitts' Law. Additional factors such as muscle activation may call for different cortical control even when difficulty was identical.
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Affiliation(s)
- Haibiao Ji
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Zhi Chen
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yongjun Qiao
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jin Yan
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Gaoxiang Chen
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qi Luo
- School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China
| | - Lijun Cui
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ya Zong
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qing Xie
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chuanxin M. Niu
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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Sun S, Xu G, Li M, Zhang M, Zhang Y, Liu W, Wang A. Function Electrical Stimulation Effect on Muscle Fatigue Based on Fatigue Characteristic Curves of Dumbbell Weightlifting Training. CYBORG AND BIONIC SYSTEMS 2024; 5:0124. [PMID: 38846791 PMCID: PMC11156462 DOI: 10.34133/cbsystems.0124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/12/2024] [Indexed: 06/09/2024] Open
Abstract
The parameter setting of functional electrical stimulation (FES) is important for active recovery training since it affects muscle health. Among the FES parameters, current amplitude is the most influential factor. To explore the FES effect on the maximum stimulation time, this study establishes a curve between FES current amplitude and the maximum stimulation time based on muscle fatigue. We collect 10 subjects' surface electromyography under dumbbell weightlifting training and analyze the muscle fatigue state by calculating the root mean square (RMS) of power. By analyzing signal RMS, the fatigue characteristic curves under different fatigue levels are obtained. According to the muscle response under FES, the relationship curve between the current amplitude and the maximum stimulation time is established and FES parameters' effect on the maximum stimulation time is obtained. The linear curve provides a reference for FES parameter setting, which can help to set stimulation time safely, thus preventing the muscles from entering an excessive fatigue state and becoming more active to muscle recovery training.
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Affiliation(s)
- Shihao Sun
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering,
Hebei University of Technology, 300132 Tianjin, China
- Hebei Key Laboratory of Bioelectromagnetics and Neuroengineering, 300132 Tianjin, China
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health,
Hebei University of Technology, 300132 Tianjin, China
- School of Electrical Engineering,
Hebei University of Technology, 300132 Tianjin, China
| | - Guizhi Xu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering,
Hebei University of Technology, 300132 Tianjin, China
- Hebei Key Laboratory of Bioelectromagnetics and Neuroengineering, 300132 Tianjin, China
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health,
Hebei University of Technology, 300132 Tianjin, China
- School of Electrical Engineering,
Hebei University of Technology, 300132 Tianjin, China
| | - Mengfan Li
- Hebei Key Laboratory of Bioelectromagnetics and Neuroengineering, 300132 Tianjin, China
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health,
Hebei University of Technology, 300132 Tianjin, China
- School of Health Sciences and Biomedical Engineering,
Hebei University of Technology, 300132 Tianjin, China
| | - Mingyu Zhang
- Hebei Key Laboratory of Bioelectromagnetics and Neuroengineering, 300132 Tianjin, China
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health,
Hebei University of Technology, 300132 Tianjin, China
- School of Health Sciences and Biomedical Engineering,
Hebei University of Technology, 300132 Tianjin, China
| | - Yuxin Zhang
- Hebei Key Laboratory of Bioelectromagnetics and Neuroengineering, 300132 Tianjin, China
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health,
Hebei University of Technology, 300132 Tianjin, China
- School of Health Sciences and Biomedical Engineering,
Hebei University of Technology, 300132 Tianjin, China
| | - Wentao Liu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering,
Hebei University of Technology, 300132 Tianjin, China
- Hebei Key Laboratory of Bioelectromagnetics and Neuroengineering, 300132 Tianjin, China
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health,
Hebei University of Technology, 300132 Tianjin, China
- School of Electrical Engineering,
Hebei University of Technology, 300132 Tianjin, China
| | - Alan Wang
- Auckland Bioengineering Institute,
University of Auckland, Auckland, New Zealand
- Centre for Brain Research, Faculty of Medical and Health Sciences,
University of Auckland, Auckland, New Zealand
- Centre for Medical Imaging, Faculty of Medical and Health Sciences,
University of Auckland, Auckland, New Zealand
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Xiao Z, Li C, Wang X, Guo J, Tian Q. Muscle Strength Identification Based on Isokinetic Testing and Spine Musculoskeletal Modeling. CYBORG AND BIONIC SYSTEMS 2024; 5:0113. [PMID: 39040710 PMCID: PMC11261815 DOI: 10.34133/cbsystems.0113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 03/15/2024] [Indexed: 07/24/2024] Open
Abstract
Subject-specific spinal musculoskeletal modeling can help understand the spinal loading mechanism during human locomotion. However, existing literature lacks methods to identify the maximum isometric strength of individual spinal muscles. In this study, a muscle strength identification method combining isokinetic testing and musculoskeletal simulations was proposed, and the influence of muscle synergy and intra-abdominal pressure (IAP) on identified spinal muscle strength was further discussed. A multibody dynamic model of the spinal musculoskeletal system was established and controlled by a feedback controller. Muscle strength parameters were adjusted based on the measured isokinetic moments, and muscle synergy vectors and the IAP piston model were further introduced. The results of five healthy subjects showed that the proposed method successfully identified the subject-specific spinal flexor/extensor strength. Considering the synergistic activations of antagonist muscles improved the correlation between the simulated and measured spinal moments, and the introduction of IAP slightly increased the identified spinal extensor strength. The established method is beneficial for understanding spinal loading distributions for athletes and patients with sarcopenia.
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Affiliation(s)
- Zuming Xiao
- MOE Key Laboratory of Dynamics and Control of Flight Vehicle, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China
| | - Chang Li
- Professional and Technical Innovation Center for Exercise Diagnosis and Evaluation, Shenyang Sport University, Shenyang, China
| | - Xin Wang
- Professional and Technical Innovation Center for Exercise Diagnosis and Evaluation, Shenyang Sport University, Shenyang, China
| | - Jianqiao Guo
- MOE Key Laboratory of Dynamics and Control of Flight Vehicle, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China
| | - Qiang Tian
- MOE Key Laboratory of Dynamics and Control of Flight Vehicle, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China
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Park JH. Effects of Personalized Cognitive Training Using Mental Workload Monitoring on Executive Function in Older Adults With Mild Cognitive Impairment. BRAIN & NEUROREHABILITATION 2023; 16:e21. [PMID: 38047099 PMCID: PMC10689865 DOI: 10.12786/bn.2023.16.e21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 08/07/2023] [Accepted: 08/22/2023] [Indexed: 12/05/2023] Open
Abstract
Although a variety of cognitive training has been performed, its optimally personalized delivery is still unknown. This study established the mental workload classification model using a convolutional neural network based on functional near-infrared spectroscopy-derived data. The dorsolateral prefrontal cortex (DLPFC) while thirty individuals with mild cognitive impairment (MCI) performed spatial working memory testing was found to be a considerable indicator to classify 3 levels of mental workload with an accuracy of over 86%. In the next step, forty subjects with MCI were randomly allocated into the experimental group (EG) that received cognitive training with mental workload-based difficulty adjustment or the control group (CG) that received conventional cognitive training. To compare both groups, the Trail Making Test Part B (TMT-B) and hemodynamic responses in the DLPFC during the TMT-B were measured. After the 16 training sessions, the EG subjects achieved a greater improvement in the TMT-B than the CG subjects (p < 0.05). Also, the EG subject showed a significantly lower DLPFC activity during the TMT-B than the CG subject (p < 0.05). In sum, the EG subjects better performed executive function with lower energy from the DLPFC. These findings imply that the importance of mental workload monitoring to provide personalized cognitive training.
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Affiliation(s)
- Jin-Hyuck Park
- Department of Occupational Therapy, Soonchunhyang University, Asan, Korea
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