Open Access
| Issue |
E3S Web Conf.
Volume 351, 2022
10th International Conference on Innovation, Modern Applied Science & Environmental Studies (ICIES’2022)
|
|
|---|---|---|
| Article Number | 01042 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/e3sconf/202235101042 | |
| Published online | 24 May 2022 | |
- K. Jain, “Data clustering: 50 years beyond K-means,” Pattern Recognition Letters 31, 8, pp.651–666 https://doi.Org/10.1016/j.patrec.2009.09.011 (2010). [CrossRef] [Google Scholar]
- D. Müllner, Modern hierarchical, agglomerative clustering algorithms. ArXiv abs/1109.2378 (2011) [Google Scholar]
- Berthoz, M. Zaoui, New paradigms, and tests for evaluating and remediating visuospatial deficits in children. Developmental medicine and child neurology 57 Suppl 2,15–20. https://doi.org/10.1111/dmcn.12690 (2015). [CrossRef] [PubMed] [Google Scholar]
- P. Corsi Memory and the Medial Temporal Region of the Brain. Doctoral Thesis in Philosophy, McGill University, Montreal (1972). [Google Scholar]
- Annaki et al., Computational Analysis of Human Navigation Trajectories in a Spatial Memory Locomotor Task. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2021. Lecture Notes in Networks and Systems, 211. Springer, Cham. https://doi.org/10.1007/978-3-030-73882-2_22 (2021). [Google Scholar]
- M. Islas, M. Ângel, and E. Ciampi, Assessment and Impact of Cognitive Impairment in Multiple Sclerosis: An Overview. Biomedicines, 7,122. https://doi.org/10.3390/biomedicines7010022 (2019). [Google Scholar]
- Habas, A. Berthoz, T. Flash, D. Bennequin, Does the Cerebellum Implement or Select Geometries? A Speculative Note. The Cerebellum. 19. 1–7. 10.1007/s12311-019-01095-5 (2020). [Google Scholar]
- A. Berthoz, D. Bennequin. Several geometries for movement generation. In: Geometric and numerical foundations of movements. In: Laumond J.P., Mansard, N., Lasserre J.B., editors. Springer tracts in advanced robotics, 117: Springer. p. 13–42. (2017). [Google Scholar]
- T. Flash, Brain Representations of Motion Generation and Perception: Space-Time Geometries and the Arts. https://doi.org/10.1007/978-3-030-57227-3_1 (2021). [Google Scholar]
- Magnani, & E Defrasne Ait-Said, Geometrical analysis of motion schemes on fencing experts from competition videos. PloS one, 16 (12), e0261888. https://doi.org/10.1371/journal.pone.0261888. (2021). [CrossRef] [PubMed] [Google Scholar]
- B. Nemec, N. Likar, A. Gams, & A. Ude, Humanrobot cooperation with compliance adaptation along the motion trajectory. Autonomous Robots. 42. 10.1007/s10514017-9676-3 (2018). [Google Scholar]
- Q. C. Pham, A General, Fast, and Robust Implementation of the Time-Optimal Path Parameterization Algorithm. IEEE Transactions on Robotics. 30. 10.1109/TRO.2014.2351113 (2013). [Google Scholar]
- H. Hicheur, Q. C. Pham, G. Arechavaleta, J. P. Laumond, A. Berthoz, The formation of trajectories during goal-oriented locomotion in humans. I. A stereotyped behavior. The European journal of neuroscience, 26, 8 2376–2390. https://doi.org/10.1111/j.14609568.2007.05836.x (2007). [CrossRef] [PubMed] [Google Scholar]
- M. A. Bucklin, M. Wu, G. Brown, G. K. E. Gordon, American Society of Biomechanics Journal of Biomechanics Award 2018: Adaptive motor planning of center-of-mass trajectory during goal-directed walking in novel environments. Journal of biomechanics, 94, 5–12. https://doi.org/10.1016/jjbiomech.2019.07.030 (2019). [CrossRef] [PubMed] [Google Scholar]
- F. S. Ribeiro, F. H. Santos, P. B. Albuquerque, How Does Allocation of Emotional Stimuli Impact Working Memory Tasks? An Overview. Advances in cognitive psychology, 15, 2,155–168. https://doi.org/10.5709/acp-0265-y (2019). [CrossRef] [PubMed] [Google Scholar]
- R. Huang, A.A. Nikooyan, B. Xu et al., Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration. Sci Rep 11, 3950 https://doi.org/10.1038/s41598-021-82694-3 (2021). [CrossRef] [PubMed] [Google Scholar]
- K. Nowakowski, P. Carvalho, et al. Human locomotion with reinforcement learning using bioinspired reward reshaping strategies. Medical & biological engineering & computing, 59,1, 243–256. https://doi.org/10.1007/s11517-020-02309-3 (2021). [CrossRef] [PubMed] [Google Scholar]
- V. Belmonti, A. Berthoz, et al., Navigation strategies as revealed by error patterns on the Magic Carpet test in children with cerebral palsy. Frontiers in psychology. 6, 880. https://doi.org/10.3389/fpsyg.20 15.00880 (2015). [CrossRef] [PubMed] [Google Scholar]
- A. Bartonek, L. Piccardi, C. Guariglia, Topographical Working Memory in Children with Cerebral Palsy. Journal of Motor Behavior. 53, 1–9 https://doi.org/10.1080/00222895.2020.1748861 (2020). [Google Scholar]
- M. Tedesco, F. Bianchini, et al., Does the cerebellum contribute to human navigation by processing sequential information? Neuropsychology, 31, 5, 564–574. https://doi.org/10.1037/neu0000354 (2017). [CrossRef] [PubMed] [Google Scholar]
- L. Piccardi et al., The Walking Corsi Test (WalCT): a normative study of topographical working memory in a sample of 4- to 11-year-olds. The Clinical neuropsychologist, 28, 1, 84–96. https://doi.org/10.1080/13854046.2013.863976 (2014). [CrossRef] [PubMed] [Google Scholar]
- A. Castilla, et al., A New Paradigm for the Study of Cognitive Flexibility in Children and Adolescents: The ‘Virtual House Locomotor Maze’ (VHLM). Frontiers in Psychiatry. 12 https://doi.org/10.3389/fpsyt.2021.708378 (2021). [Google Scholar]
- M. Blagojevic, Comparison possibilities of k-means and HAC clustering in the analysis of users’ patterns of behavior. I-Society 2011 (2011). [Google Scholar]
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