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For: Rodríguez-Fernández A, Lobo-Prat J, Font-Llagunes JM. Systematic review on wearable lower-limb exoskeletons for gait training in neuromuscular impairments. J Neuroeng Rehabil 2021;18:22. [PMID: 33526065 DOI: 10.1186/s12984-021-00815-5] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]
Number Citing Articles
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3 Li H, Yu H, Chen Y, Tang X, Wang D, Meng Q, Du Q. Design of a Minimally Actuated Lower Limb Exoskeleton with Mechanical Joint Coupling. J Bionic Eng. [DOI: 10.1007/s42235-021-00146-0] [Reference Citation Analysis]
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6 Nagano H, Said CM, James L, Sparrow WA, Begg R. Biomechanical Correlates of Falls Risk in Gait Impaired Stroke Survivors. Front Physiol 2022;13:833417. [DOI: 10.3389/fphys.2022.833417] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
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8 Gil-castillo J, Barria P, Aguilar Cárdenas R, Baleta Abarza K, Andrade Gallardo A, Biskupovic Mancilla A, Azorín JM, Moreno JC. A Robot-Assisted Therapy to Increase Muscle Strength in Hemiplegic Gait Rehabilitation. Front Neurorobot 2022;16:837494. [DOI: 10.3389/fnbot.2022.837494] [Reference Citation Analysis]
9 Carleton AG, Sup FC 4th, Modarres-Sadeghi Y. Passive double pendulum in the wake of a cylinder forced to rotate emulates a cyclic human walking gait. Bioinspir Biomim 2022;17. [PMID: 35576923 DOI: 10.1088/1748-3190/ac7022] [Reference Citation Analysis]
10 Zhang L, Lin F, Sun L, Chen C. Comparison of Efficacy of Lokomat and Wearable Exoskeleton-Assisted Gait Training in People With Spinal Cord Injury: A Systematic Review and Network Meta-Analysis. Front Neurol 2022;13:772660. [DOI: 10.3389/fneur.2022.772660] [Reference Citation Analysis]
11 Mahmoudi Khomami A, Najafi F. A survey on soft lower limb cable-driven wearable robots without rigid links and joints. Robotics and Autonomous Systems 2021;144:103846. [DOI: 10.1016/j.robot.2021.103846] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Forte G, Leemhuis E, Favieri F, Casagrande M, Giannini AM, De Gennaro L, Pazzaglia M. Exoskeletons for Mobility after Spinal Cord Injury: A Personalized Embodied Approach. J Pers Med 2022;12:380. [PMID: 35330380 DOI: 10.3390/jpm12030380] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Piccinini L, Cimolin V, Storm F, Di Girolamo G, Biffi E, Galli M, Condoluci C. Quantification of the effects of robotic-assisted gait training on upper and lower body strategy during gait in diplegic children with Cerebral Palsy using summary parameters. Comput Methods Biomech Biomed Engin 2021;:1-8. [PMID: 34121521 DOI: 10.1080/10255842.2021.1938009] [Reference Citation Analysis]
14 Zhang Z, Wang H, Guo S, Wang J, Zhao Y, Tian Q. The Effects of Unpowered Soft Exoskeletons on Preferred Gait Features and Resonant Walking. Machines 2022;10:585. [DOI: 10.3390/machines10070585] [Reference Citation Analysis]
15 Ceccarelli M, Bottin M, Russo M, Rosati G, Laribi MA, Petuya V. Requirements and Solutions for Motion Limb Assistance of COVID-19 Patients. Robotics 2022;11:45. [DOI: 10.3390/robotics11020045] [Reference Citation Analysis]
16 Lora-millan JS, Hidalgo AF, Rocon E. An IMUs-Based Extended Kalman Filter to Estimate Gait Lower Limb Sagittal Kinematics for the Control of Wearable Robotic Devices. IEEE Access 2021;9:144540-54. [DOI: 10.1109/access.2021.3122160] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
17 Park JH, Kim HS, Jang SH, Hyun DJ, Park SI, Yoon J, Lim H, Kim MJ. Cardiorespiratory Responses to 10 Weeks of Exoskeleton-Assisted Overground Walking Training in Chronic Nonambulatory Patients with Spinal Cord Injury. Sensors (Basel) 2021;21:5022. [PMID: 34372258 DOI: 10.3390/s21155022] [Reference Citation Analysis]
18 Maggio MG, Naro A, De Luca R, Latella D, Balletta T, Caccamo L, Pioggia G, Bruschetta D, Calabrò RS. Body Representation in Patients with Severe Spinal Cord Injury: A Pilot Study on the Promising Role of Powered Exoskeleton for Gait Training. JPM 2022;12:619. [DOI: 10.3390/jpm12040619] [Reference Citation Analysis]
19 Huang B, Chen W, Liang J, Cheng L, Xiong C. Characterization and Categorization of Various Human Lower Limb Movements Based on Kinematic Synergies. Front Bioeng Biotechnol 2022;9:793746. [DOI: 10.3389/fbioe.2021.793746] [Reference Citation Analysis]
20 Fernández-Vázquez D, Cano-de-la-Cuerda R, Gor-García-Fogeda MD, Molina-Rueda F. Wearable Robotic Gait Training in Persons with Multiple Sclerosis: A Satisfaction Study. Sensors (Basel) 2021;21:4940. [PMID: 34300677 DOI: 10.3390/s21144940] [Reference Citation Analysis]
21 Fang Q, Xu T, Zheng T, Cai H, Zhao J, Zhu Y, Gallardo Alvarado J. A Rehabilitation Training Interactive Method for Lower Limb Exoskeleton Robot. Mathematical Problems in Engineering 2022;2022:1-15. [DOI: 10.1155/2022/2429832] [Reference Citation Analysis]
22 Bulea TC, Sharma N, Sikdar S, Su H. Editorial: Next Generation User-Adaptive Wearable Robots. Front Robot AI 2022;9:920655. [DOI: 10.3389/frobt.2022.920655] [Reference Citation Analysis]
23 Manikkath J, Subramony JA. Toward closed-loop drug delivery: Integrating wearable technologies with transdermal drug delivery systems. Adv Drug Deliv Rev 2021;179:113997. [PMID: 34634396 DOI: 10.1016/j.addr.2021.113997] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
24 Febrer-nafría M, Fregly BJ, Font-llagunes JM. Evaluation of Optimal Control Approaches for Predicting Active Knee-Ankle-Foot-Orthosis Motion for Individuals With Spinal Cord Injury. Front Neurorobot 2022;15:748148. [DOI: 10.3389/fnbot.2021.748148] [Reference Citation Analysis]
25 Calabrò RS, Cassio A, Mazzoli D, Andrenelli E, Bizzarini E, Campanini I, Carmignano SM, Cerulli S, Chisari C, Colombo V, Dalise S, Fundarò C, Gazzotti V, Mazzoleni D, Mazzucchelli M, Melegari C, Merlo A, Stampacchia G, Boldrini P, Mazzoleni S, Posteraro F, Benanti P, Castelli E, Draicchio F, Falabella V, Galeri S, Gimigliano F, Grigioni M, Mazzon S, Molteni F, Petrarca M, Picelli A, Senatore M, Turchetti G, Morone G, Bonaiuti D; Italian Consensus Conference on Robotics in Neurorehabilitation (CICERONE). What does evidence tell us about the use of gait robotic devices in patients with multiple sclerosis? A comprehensive systematic review on functional outcomes and clinical recommendations. Eur J Phys Rehabil Med 2021;57:841-9. [PMID: 34547886 DOI: 10.23736/S1973-9087.21.06915-X] [Reference Citation Analysis]
26 Cumplido C, Delgado E, Ramos J, Puyuelo G, Garcés E, Destarac MA, Plaza A, Hernández M, Gutiérrez A, García E. Gait-assisted exoskeletons for children with cerebral palsy or spinal muscular atrophy: A systematic review. NeuroRehabilitation 2021. [PMID: 34219676 DOI: 10.3233/NRE-210135] [Reference Citation Analysis]
27 Jiang F, Liu H, Li Q, Cao J, Yin X, Dong R, Peng X. Man-Machine Synergy Control for Pneumatically Powered Exoskeleton Based on Surface Electromyogram Signal. Mathematical Problems in Engineering 2022;2022:1-14. [DOI: 10.1155/2022/6897221] [Reference Citation Analysis]