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For: Rehmat N, Zuo J, Meng W, Liu Q, Xie SQ, Liang H. Upper limb rehabilitation using robotic exoskeleton systems: a systematic review. Int J Intell Robot Appl 2018;2:283-95. [DOI: 10.1007/s41315-018-0064-8] [Cited by in Crossref: 32] [Cited by in F6Publishing: 25] [Article Influence: 8.0] [Reference Citation Analysis]
Number Citing Articles
1 Ye Y, Shi Y, Srinivasan D, Du J. Sensation transfer for immersive exoskeleton motor training: Implications of haptics and viewpoints. Automation in Construction 2022;141:104411. [DOI: 10.1016/j.autcon.2022.104411] [Reference Citation Analysis]
2 Meng Q, Xu R, Xie Q, Bostan·mahmutjan, Li S, Yu H. Bionic Design to Reduce Driving Power for a Portable Elbow Exoskeleton Based on Gravity-balancing Coupled Model. J Bionic Eng. [DOI: 10.1007/s42235-022-00249-2] [Reference Citation Analysis]
3 Xu P, Xia D, Li J, Zhou J, Xie L. Execution and perception of upper limb exoskeleton for stroke patients: a systematic review. Intel Serv Robotics. [DOI: 10.1007/s11370-022-00435-5] [Reference Citation Analysis]
4 Baysal CV. An Inverse Dynamics-Based Control Approach for Compliant Control of Pneumatic Artificial Muscles. Actuators 2022;11:111. [DOI: 10.3390/act11040111] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Dragusanu M, Troisi D, Villani A, Prattichizzo D, Malvezzi M. Design and Prototyping of an Underactuated Hand Exoskeleton With Fingers Coupled by a Gear-Based Differential. Front Robot AI 2022;9:862340. [DOI: 10.3389/frobt.2022.862340] [Reference Citation Analysis]
6 Blanco-ortega A, Vázquez-sánchez L, Adam-medina M, Colín-ocampo J, Abúndez-pliego A, Cortés-garcía C, García-beltrán CD. A Robust Controller for Upper Limb Rehabilitation Exoskeleton. Applied Sciences 2022;12:1178. [DOI: 10.3390/app12031178] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
7 Wang H, Lu J. Research on Fractional Order Fuzzy PID Control of the Pneumatic-hydraulic Upper Limb Rehabilitation Training System Based on PSO. Int J Control Autom Syst 2022;20:310-20. [DOI: 10.1007/s12555-020-0847-1] [Reference Citation Analysis]
8 Kim H, Asbeck AT. The Effects of Torque Magnitude and Stiffness in Arm Guidance Through Joint Torque Feedback. IEEE Access 2022;10:5842-54. [DOI: 10.1109/access.2022.3141981] [Reference Citation Analysis]
9 Babič J, Laffranchi M, Tessari F, Verstraten T, Novak D, Šarabon N, Ugurlu B, Peternel L, Torricelli D, Veneman JF. Challenges and solutions for application and wider adoption of wearable robots. Wearable Technol 2021;2. [DOI: 10.1017/wtc.2021.13] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
10 Omrani J, Moghaddam MM. Nonlinear time delay estimation based model reference adaptive impedance control for an upper-limb human-robot interaction. Proc Inst Mech Eng H 2021;:9544119211054919. [PMID: 34720012 DOI: 10.1177/09544119211054919] [Reference Citation Analysis]
11 Carino-Escobar RI, Valdés-Cristerna R, Carrillo-Mora P, Rodriguez-Barragan MA, Hernandez-Arenas C, Quinzaños-Fresnedo J, Arias-Carrión O, Cantillo-Negrete J. Prognosis of stroke upper limb recovery with physiological variables using regression tree ensembles. J Neural Eng 2021;18. [PMID: 33906163 DOI: 10.1088/1741-2552/abfc1e] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
12 Khalid S, Alnajjar F, Gochoo M, Renawi A, Shimoda S. Robotic assistive and rehabilitation devices leading to motor recovery in upper limb: a systematic review. Disabil Rehabil Assist Technol 2021;:1-15. [PMID: 33861684 DOI: 10.1080/17483107.2021.1906960] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
13 Natividad RF, Miller-jackson T, Chen-hua RY. A 2-DOF Shoulder Exosuit Driven by Modular, Pneumatic, Fabric Actuators. IEEE Trans Med Robot Bionics 2021;3:166-78. [DOI: 10.1109/tmrb.2020.3044115] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 Kyrarini M, Lygerakis F, Rajavenkatanarayanan A, Sevastopoulos C, Nambiappan HR, Chaitanya KK, Babu AR, Mathew J, Makedon F. A Survey of Robots in Healthcare. Technologies 2021;9:8. [DOI: 10.3390/technologies9010008] [Cited by in Crossref: 17] [Cited by in F6Publishing: 10] [Article Influence: 17.0] [Reference Citation Analysis]
15 Yamine J, Prini A, Nicora ML, Dinon T, Giberti H, Malosio M. A Planar Parallel Device for Neurorehabilitation. Robotics 2020;9:104. [DOI: 10.3390/robotics9040104] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
16 Yang J, Zhao Z, Du C, Wang W, Peng Q, Qiu J, Wang G. The realization of robotic neurorehabilitation in clinical: use of computational intelligence and future prospects analysis. Expert Rev Med Devices 2020;17:1311-22. [PMID: 33252284 DOI: 10.1080/17434440.2020.1852930] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
17 Zuccon G, Bottin M, Ceccarelli M, Rosati G. Design and Performance of an Elbow Assisting Mechanism. Machines 2020;8:68. [DOI: 10.3390/machines8040068] [Cited by in Crossref: 14] [Cited by in F6Publishing: 8] [Article Influence: 7.0] [Reference Citation Analysis]
18 Qassim HM, Wan Hasan WZ. A Review on Upper Limb Rehabilitation Robots. Applied Sciences 2020;10:6976. [DOI: 10.3390/app10196976] [Cited by in Crossref: 17] [Cited by in F6Publishing: 11] [Article Influence: 8.5] [Reference Citation Analysis]
19 Kim H, Asbeck AT. An elbow exoskeleton for haptic feedback made with a direct drive hobby motor. HardwareX 2020;8:e00153. [DOI: 10.1016/j.ohx.2020.e00153] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
20 Kosaki T, Li S; Department of Systems Engineering, Graduate School of Information Sciences, Hiroshima City University 3-4-1 Ozuka-higashi, Asaminami-ku, Hiroshima 731-3194, Japan. A Water-Hydraulic Upper-Limb Assistive Exoskeleton System with Displacement Estimation. JRM 2020;32:149-56. [DOI: 10.20965/jrm.2020.p0149] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
21 Mounis SYA, Azlan NZ, Sado F. Assist-as-Needed Robotic Rehabilitation Strategy Based on z-Spline Estimated Functional Ability. IEEE Access 2020;8:157557-71. [DOI: 10.1109/access.2020.3019450] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
22 Kapsalyamov A, Hussain S, Jamwal PK. State-of-the-Art Assistive Powered Upper Limb Exoskeletons for Elderly. IEEE Access 2020;8:178991-9001. [DOI: 10.1109/access.2020.3026641] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
23 Iandolo R, Marini F, Semprini M, Laffranchi M, Mugnosso M, Cherif A, De Michieli L, Chiappalone M, Zenzeri J. Perspectives and Challenges in Robotic Neurorehabilitation. Applied Sciences 2019;9:3183. [DOI: 10.3390/app9153183] [Cited by in Crossref: 32] [Cited by in F6Publishing: 9] [Article Influence: 10.7] [Reference Citation Analysis]
24 Xie S, Chakrabarty S, Chang J, Lan C, Huang X, Mcdaid A. Guest Editorial introduction to the Focused section on wearable sensors, actuators, and robots for rehabilitation. Int J Intell Robot Appl 2019;3:1-3. [DOI: 10.1007/s41315-019-00087-2] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
25 Nguyen DN, Dao T, Chau NL, Dang VA. Hybrid Approach of Finite Element Method, Kigring Metamodel, and Multiobjective Genetic Algorithm for Computational Optimization of a Flexure Elbow Joint for Upper-Limb Assistive Device. Complexity 2019;2019:1-13. [DOI: 10.1155/2019/3231914] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]