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Cited by in F6Publishing
For: Passon A, Schauer T, Seel T. Inertial-Robotic Motion Tracking in End-Effector-Based Rehabilitation Robots. Front Robot AI 2020;7:554639. [PMID: 33501318 DOI: 10.3389/frobt.2020.554639] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 Laidig D, Seel T. VQF: Highly accurate IMU orientation estimation with bias estimation and magnetic disturbance rejection. Information Fusion 2023;91:187-204. [DOI: 10.1016/j.inffus.2022.10.014] [Reference Citation Analysis]
2 Zhu Y, Tong X, Yang R, Li Y, Du M, Su C. A Survey on Modeling Mechanism and Control Strategy of Rehabilitation Robots: Recent Trends, Current Challenges, and Future Developments. Int J Control Autom Syst . [DOI: 10.1007/s12555-021-0571-5] [Reference Citation Analysis]
3 Wang X, Fu Y, Ye B, Babineau J, Ding Y, Mihailidis A. Technology-Based Compensation Assessment and Detection of Upper Extremity Activities of Stroke Survivors: Systematic Review. J Med Internet Res 2022;24:e34307. [PMID: 35699982 DOI: 10.2196/34307] [Reference Citation Analysis]
4 Wang X, Fu Y, Ye B, Babineau J, Ding Y, Mihailidis A. Technology-Based Compensation Assessment and Detection of Upper Extremity Activities of Stroke Survivors: Systematic Review (Preprint).. [DOI: 10.2196/preprints.34307] [Reference Citation Analysis]
5 Nguyen G, Maclean J, Stirling L. Quantification of Compensatory Torso Motion in Post-Stroke Patients Using Wearable Inertial Measurement Units. IEEE Sensors J 2021;21:15349-60. [DOI: 10.1109/jsen.2021.3072010] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
6 Laidig D, Caruso M, Cereatti A, Seel T. BROAD—A Benchmark for Robust Inertial Orientation Estimation. Data 2021;6:72. [DOI: 10.3390/data6070072] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]