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For: Jarque-Bou NJ, Scano A, Atzori M, Müller H. Kinematic synergies of hand grasps: a comprehensive study on a large publicly available dataset. J Neuroeng Rehabil 2019;16:63. [PMID: 31138257 DOI: 10.1186/s12984-019-0536-6] [Cited by in Crossref: 33] [Cited by in F6Publishing: 34] [Article Influence: 11.0] [Reference Citation Analysis]
Number Citing Articles
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9 Scano A, Mira RM, d'Avella A. Mixed matrix factorization: a novel algorithm for the extraction of kinematic-muscular synergies. J Neurophysiol 2022. [PMID: 34986023 DOI: 10.1152/jn.00379.2021] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
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11 Liu Y, Zeng B, Zhang T, Jiang L, Liu H, Ming D. Quantitative Investigation of Hand Grasp Functionality: Hand Joint Motion Correlation, Independence, and Grasping Behavior. Appl Bionics Biomech 2021;2021:2787832. [PMID: 34899980 DOI: 10.1155/2021/2787832] [Reference Citation Analysis]
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13 Gracia-Ibáñez V, Rodríguez-Cervantes PJ, Bayarri-Porcar V, Granell P, Vergara M, Sancho-Bru JL. Using Sensorized Gloves and Dimensional Reduction for Hand Function Assessment of Patients with Osteoarthritis. Sensors (Basel) 2021;21:7897. [PMID: 34883898 DOI: 10.3390/s21237897] [Reference Citation Analysis]
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16 Averta G, Barontini F, Catrambone V, Haddadin S, Handjaras G, Held JPO, Hu T, Jakubowitz E, Kanzler CM, Kühn J, Lambercy O, Leo A, Obermeier A, Ricciardi E, Schwarz A, Valenza G, Bicchi A, Bianchi M. U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions. Gigascience 2021;10:giab043. [PMID: 34143875 DOI: 10.1093/gigascience/giab043] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 6.0] [Reference Citation Analysis]
17 Kieliba P, Clode D, Maimon-Mor RO, Makin TR. Robotic hand augmentation drives changes in neural body representation. Sci Robot 2021;6:eabd7935. [PMID: 34043536 DOI: 10.1126/scirobotics.abd7935] [Cited by in Crossref: 38] [Cited by in F6Publishing: 35] [Article Influence: 38.0] [Reference Citation Analysis]
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19 Jarque-Bou NJ, Sancho-Bru JL, Vergara M. Synergy-Based Sensor Reduction for Recording the Whole Hand Kinematics. Sensors (Basel) 2021;21:1049. [PMID: 33557063 DOI: 10.3390/s21041049] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
20 Zabala U, Rodriguez I, Martínez-otzeta JM, Irigoien I, Lazkano E. Quantitative analysis of robot gesticulation behavior. Auton Robot 2021;45:175-89. [DOI: 10.1007/s10514-020-09958-1] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
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22 Li Y, Zhang W, Zhang Q, Zheng N. Transfer Learning-Based Muscle Activity Decoding Scheme by Low-frequency sEMG for Wearable Low-cost Application. IEEE Access 2021;9:22804-15. [DOI: 10.1109/access.2021.3056412] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
23 Atzori M, Rosanda E, Pajardi G, Bassetto F, Muller H. Effect of movement type on the classification of electromyography data for the control of dexterous prosthetic hands. 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob) 2020. [DOI: 10.1109/biorob49111.2020.9224452] [Reference Citation Analysis]
24 Gong D, Hao L, Yu J, Zuo G. Bionic Design of a Dexterous Anthropomorphic Hand Actuated by Antagonistic PAMs. 2020 IEEE International Conference on Real-time Computing and Robotics (RCAR) 2020. [DOI: 10.1109/rcar49640.2020.9303299] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
25 Pale U, Atzori M, Müller H, Scano A. Variability of Muscle Synergies in Hand Grasps: Analysis of Intra- and Inter-Session Data. Sensors (Basel) 2020;20:E4297. [PMID: 32752155 DOI: 10.3390/s20154297] [Cited by in Crossref: 16] [Cited by in F6Publishing: 16] [Article Influence: 8.0] [Reference Citation Analysis]
26 Kuroiwa T, Nimura A, Takahashi Y, Sasaki T, Koyama T, Okawa A, Fujita K. Device Development for Detecting Thumb Opposition Impairment Using Carbon Nanotube-Based Strain Sensors. Sensors (Basel) 2020;20:E3998. [PMID: 32708416 DOI: 10.3390/s20143998] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
27 Kieliba P, Clode D, Maimon-mor RO, Makin TR. Neurocognitive consequences of hand augmentation.. [DOI: 10.1101/2020.06.16.151944] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
28 Gracia-Ibáñez V, Sancho-Bru JL, Vergara M, Jarque-Bou NJ, Roda-Sales A. Sharing of hand kinematic synergies across subjects in daily living activities. Sci Rep 2020;10:6116. [PMID: 32273539 DOI: 10.1038/s41598-020-63092-7] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 4.5] [Reference Citation Analysis]
29 Roda-Sales A, Sancho-Bru JL, Vergara M, Gracia-Ibáñez V, Jarque-Bou NJ. Effect on manual skills of wearing instrumented gloves during manipulation. J Biomech 2020;98:109512. [PMID: 31767287 DOI: 10.1016/j.jbiomech.2019.109512] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 4.5] [Reference Citation Analysis]
30 Singh S, Mandziak A, Barr K, Blackwell AA, Mohajerani MH, Wallace DG, Whishaw IQ. Human string-pulling with and without a string: movement, sensory control, and memory. Exp Brain Res 2019;237:3431-47. [DOI: 10.1007/s00221-019-05684-y] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.7] [Reference Citation Analysis]
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