Bibliografie tematiche / Motor learning

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Letteratura scientifica selezionata sul tema "Motor learning"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 9 giugno 2025

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Articoli di riviste sul tema "Motor learning"

Yun, Jung-Eun. "Understanding motor learning processing and motor strategies on motor skill learning." Korean Journal of Sports Science 31, no. 5 (October 31, 2022): 389–402. http://dx.doi.org/10.35159/kjss.2022.10.31.5.389.

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NAKAMURA, RYUICHI. "Motor Learning." Journal of exercise physiology 9, no. 3 (1994): 149–56. http://dx.doi.org/10.1589/rika1986.9.149.

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Plisk, Steven Scott. "Motor Learning." Strength and Conditioning Journal 24, no. 3 (June 2002): 77. http://dx.doi.org/10.1519/00126548-200206000-00020.

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Halsband, Ulrike, and Hans-Joachim Freund. "Motor learning." Current Opinion in Neurobiology 3, no. 6 (December 1993): 940–49. http://dx.doi.org/10.1016/0959-4388(93)90166-v.

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Wolpert, Daniel M., and J. Randall Flanagan. "Motor learning." Current Biology 20, no. 11 (June 2010): R467—R472. http://dx.doi.org/10.1016/j.cub.2010.04.035.

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Krakauer, John W., Alkis M. Hadjiosif, Jing Xu, Aaron L. Wong, and Adrian M. Haith. "Motor Learning." Comprehensive Physiology 9, no. 2 (April 2019): 613–63. https://doi.org/10.1002/j.2040-4603.2019.tb00069.x.

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ABSTRACTMotor learning encompasses a wide range of phenomena, ranging from relatively low‐level mechanisms for maintaining calibration of our movements, to making high‐level cognitive decisions about how to act in a novel situation. We survey the major existing approaches to characterizing motor learning at both the behavioral and neural level. In particular, we critically review two long‐standing paradigms used in motor learning research—adaptation and sequence learning. We discuss the extent to which these paradigms can be considered models of motor skill acquisition, defined as the incremental improvement in our ability to rapidly select and then precisely execute appropriate actions, and conclude that they fall short of doing so. We then discuss two classes of emerging research paradigms—learning of arbitrary visuomotor mappings de novo and learning to execute movements with improved acuity—that more effectively address the acquisition of motor skill. Future work will be needed to determine the degree to which laboratory‐based studies of skill, as described in this review, will relate to true expertise, which is likely dependent on the effects of practice on multiple cognitive processes that go beyond traditional sensorimotor neural architecture. © 2019 American Physiological Society. Compr Physiol 9:613‐663, 2019.

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Turner, Mark. "Motor Learning Research." Update: Applications of Research in Music Education 16, no. 2 (April 1998): 12–16. http://dx.doi.org/10.1177/875512339801600204.

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Schenck, Wolfram. "Kinematic motor learning." Connection Science 23, no. 4 (December 2011): 239–83. http://dx.doi.org/10.1080/09540091.2011.625077.

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Miall, Chris. "Modular motor learning." Trends in Cognitive Sciences 6, no. 1 (January 2002): 1–3. http://dx.doi.org/10.1016/s1364-6613(00)01822-2.

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Tse, Diane, and Sandi Spaulding. "Review of Motor Control and Motor Learning." Physical & Occupational Therapy In Geriatrics 15, no. 3 (July 29, 1998): 19–38. http://dx.doi.org/10.1300/j148v15n03_02.

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Tesi sul tema "Motor learning"

Shalabi, Kholood Matouq. "Motor learning and inter-manual transfer of motor learning after a stroke." Thesis, University of Newcastle upon Tyne, 2017. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.768491.

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Aims: 1) To measure automatically in stroke survivors and neurologically intact adults, learning, inter-manual transfer (ImT) and retention of learning (Ret.) of a task requiring two sequential actions embedded with-in a video game. 2) To assess the effect of age and side of stroke on learning, ImT, and Ret. of a motor task consisting of two sequentially linked actions. Participants: All participants were right hand dominant and included: A) 112 neurologically intact adults comprising: 72 younger adults (41 females), mean±SD age, 27.06±4.8 years, range 20-36 years and 40 older adults (26 females), mean±SD age 66.2±8.4 years, range 52- 86 years. B) 21 previously right-handed stroke survivors (7 females; 9 left hemiparesis), mean±SD age 66.7±9.3 years, range 54-82 years. Methods: We developed a video game that requires the player to perform two sequential actions to complete a task that mimics natural manipulation tasks. The players must first move a spaceship to a meteor (the Lock-in time phase), using isometric forces applied to game controllers using their hand muscles. The player must then track the trajectory of the meteor; (Hold/Track phase). The Lock-in time phase is assessed as the time from target presentation to achieving the target. The Hold/Track phase is assessed as the accuracy of Tracking within the meteor during the hold/Track phase. Performance is measured as the mean accumulative distance of the centre of the space ship from the outer edge of the target during periods when spaceship is outside the target. For both phases indicators, shorter distances represent higher performance. The Lock-in time and Hold/Track data were recorded for pre-training performance for the non-trained hand (nTH), pre-training performance for the trained hand (TH), training trials of the TH, reassessment after training of both the TH and the nTH, and a reassessment of both the TH and the nTH seven days after the baseline assessment. Statistical Analysis: Repeated-measures ANOVA was used; Time was the within-participant factor to examine learning. Two separate analyses were undertaken; to examine initial learning -Time (Pre, and Post Training) and to examine retention/consolidation - Time (Post- Training and Retention at one week). Age (Young, Older), Training Hand (right or left), and Group (neurologically intact or stroke survivors) were the between-participant factor. The dependent variables were Lock-in Time or Track.

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侯江濤 and Kong-to William Hau. "Artificial neural networks, motor programs and motor learning." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31240227.

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Hau, Kong-to William. "Artificial neural networks, motor programs and motor learning /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B2177920X.

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Randall, William Emerson. "One-trial motor learning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0025/MQ51453.pdf.

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Yang, Jeng-Feng. "Motor learning and adaptation the role of motor abundance /." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 216 p, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:3247585.

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Needle, Jamie Luke. "Motor performance and motor learning in adults with dyslexia." Thesis, University of Sheffield, 2006. http://etheses.whiterose.ac.uk/14893/.

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Assessment of motor performance and motor learning in dyslexia is crucial because of its ability to shed light on the underlying biology of the disorder and to discriminate between theoretical approaches. It remains a controversial area due to existing discrepant research findings and interpretations. Three studies are described in this thesis. The first used three sets of experiments to test balance and postural control in single and dual-task conditions. The second study examined the production and timing of responses in a classical eyeblink conditioning paradigm. The final study investigated motor skill acquisition. The results of the three studies were similar in that in dual-task balance, conditioned response timing and motor skill consolidation around half of the dyslexic adults showed substantial deficits compared with a control group. The samples of participants in the three studies overlapped sufficiently for some cross-study comparisons of strengths and weaknesses to be conducted. These showed that it was rare for a participant with dyslexia to show motor impairment in just one of the three domains, with dual task balance and conditioned response timing seeming to be most closely associated. Overall the results provide strong evidence of enduring deficits outside the literacy domain in dyslexia and also highlight the considerable heterogeneity of the disorder. Consequently they lend particular weight to the notion of cerebellar causation. Further studies should be undertaken on a larger scale to scrutinize the consistency of motor impairments in dyslexia and the possibility that those showing motor problems might form a definite subgroup within dyslexia. In the longer term, this work points to a possibility of multiple, independently diagnosable sub-classes of dyslexia, based on specific neurological abnormalities, with their own specific remediation and objective early detection schemes.

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Kaipa, Ramesh. "Evaluation of principles of motor learning in speech and non-speech-motor learning tasks." Thesis, University of Canterbury. Communication Disorders, 2013. http://hdl.handle.net/10092/10349.

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Principles of motor learning (PMLs) refer to a set of concepts which are considered to facilitate the process of motor learning. PMLs can be broadly grouped into principles based on (1) the structure of practice/treatment, and (2) the nature of feedback provided during practice/treatment. Application of PMLs is most evident in studies involving non-speech- motor tasks (e.g., limb movement). However, only a few studies have investigated the application of PMLs in speech-motor tasks. Previous studies relating to speech-motor function have highlighted two primary limitations: (1) Failure to consider whether various PMLs contribute equally to learning in both non-speech and speech-motor tasks, (2) Failure to consider whether PMLs can be effective in a clinical cohort in comparison to a healthy group. The present research was designed to shed light on whether selected PMLs can indeed facilitate learning in both non-speech and speech-motor tasks and also to examine their efficacy in a clinical group with Parkinson’s disease (PD) in comparison to a healthy group. Eighty healthy subjects with no history of sensory, cognitive, or neurological abnormalities, ranging 40-80 years of age, and 16 patients with PD, ranging 58-78 years of age, were recruited as participants for the current study. Four practice conditions and one feedback condition were considered in the training of a speech-motor task and a non-speech- motor task. The four practice conditions were (1) constant practice, (2) variable practice, (3) blocked practice, and (4) random practice. The feedback was a combination of low-frequency, knowledge of results, knowledge of performance, and delayed feedback conditions, and was paired with each of the four practice conditions. The participants in the clinical and non-clinical groups were required to practise a speech and a non-speech-motor learning task. Each participant was randomly and equally assigned to one of the four practice groups. The speech-motor task involved production of a meaningless and temporally modified phrase, and the non-speech-motor task involved practising a 12-note musical sequence using a portable piano keyboard. Each participant was seen on three consecutive days: the first two days served as the acquisition phase and the third day was the retention phase. During the acquisition phase, the participants practised 50 trials of the speech phrase and another 50 trials of the musical tune each day, and each session lasted for 60-90 min. Performance on the speech and non-speech tasks was preceded by an orthographic model of the target phrase/musical sequence displayed on a computer monitor along with an auditory model. The participants were instructed to match their performance to the target phrase/musical sequence exactly. Feedback on performance was provided after every 10th trial. The nature of practice differed among the four practice groups. The participants returned on the third day for the retention phase and produced 10 trials of the target phrase and another 10 trials of the musical sequence. Feedback was not provided during or after the retention trials. These final trials were recorded for later acoustic analyses. The analyses focused on spatial and temporal parameters of the speech and non-speech tasks. Spatial analysis involved evaluating the production accuracy of target phrase/tune by calculating the percentage of phonemes/keystrokes correct (PPC/PKC). The temporal analysis involved calculating the temporal synchrony of the participant productions (speech phrase & tune) during the retention trials with the target phrase and tune, respectively, through the phi correlation. The PPC/PKC and phi correlation values were subjected to a series of mixed model ANOVAs. In the healthy subjects, the results of the spatial learning revealed that the participants learned the speech task better than the non-speech (keyboard) task. In terms of temporal learning, there was no difference in learning between the speech and non-speech tasks. On an overall note, the participants performed better on the spatial domain, rather than on the temporal domain, indicating a spatial-temporal trade-off. Across spatial as well as temporal learning, participants in the constant practice condition learned the speech and non-speech tasks better than participants in the other practice conditions. Another interesting finding was that there was an age effect, with the younger participants demonstrating superior spatial and temporal learning to that of the older participants, except for temporal learning on the keyboard task for which there was no difference. In contrast, the PD group showed no significant differences on spatial or temporal learning between any of the four practice conditions. Furthermore, although the PD patients had poorer performances than the healthy subjects on both the speech and keyboard tasks, they showed very similar pattern of learning across all four practice conditions to that of the healthy subjects. The findings in the current study tend to have potential applications in speech-language therapy, and are as follows: (1) a constant practice regime could be beneficial in developing speech therapy protocols to treat motor-based communication disorders (e.g., dysarthria), (2) speech therapists need to exercise caution in designing speech therapy goals incorporating similar PMLs for younger and older adults, as the application of similar PMLs in younger and older adults may bring about different learning outcomes, (3) and finally, it could be beneficial for patients to practise speech tasks which would require them to focus either on the spatial or temporal aspect, rather than focussing on both the aspects simultaneously.

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Brashers-Krug, Thomas M. (Thomas More). "Consolidation in human motor learning." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11884.

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Jackson, Carl Patrick Thomas. "Motor learning and predictive control." Thesis, University of Nottingham, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.519400.

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Howard, III James Thomas. "Physical guidance in motor learning." Thesis, Queensland University of Technology, 2003. https://eprints.qut.edu.au/15899/1/James_Howard_Thesis.pdf.

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Previous studies of physical guidance (PG - physically constraining error during practice of a motor task) have found it to be ineffective in enhancing motor learning. However, most studies have used a highly constraining form of physical guidance that may have encouraged undue dependency. In addition, previous research has not fully considered the interaction between visual feedback and PG, and many of the studies have failed to use standard delayed retention tests with knowledge of results unavailable (no-KR). The current experiment examine the effects of varying levels of constraint in PG, as well as the interaction of PG and visual guidance (VG), using no-KR retention tests. This study involved 99 subjects divided into nine acquisition trial condition groups, forming from a 3 x 3 factorial design with factors of PG x VG, each presented at levels designated as tight, bandwidth, or none. Subjects undertook a two-dimensional pattern drawing task with no KR, PG, or VG as a pre-test, before completing 100 practice trials under one of the nine conditions. The same test was given as a retention test (immediately after practice) and as a delayed retention test (two days later). A transfer test, using a different pattern, was also administered on the second day. Almost all groups performed better on the immediate transfer test than they had on the pre-test. However, after two days only three groups (PG bandwidth-VG tight, PG none-VG bandwidth, and PG none-VG none) retained this improvement and only two groups (PG bandwidth-VG bandwidth and PG none-VG none) performed significantly better on the transfer task than their pre-test. It is proposed that bandwidth guidance generally promotes learning and that bandwidth physical guidance may enhance proprioceptive cues. Independent of PG and VG effects, KR (an overall error score) also facilitated learning.

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Libri sul tema "Motor learning"

Rothstein, Anne L. Motor learning. Reston, Va: American Alliance for Health, Physical Education, Recreation, and Dance, 1987.

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Rothstein, Anne L. Motor learning. Reston, Va: American Alliance for Health, Physical Education, Recreation, and Dance, 1987.

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Kober, Jens, and Jan Peters. Learning Motor Skills. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03194-1.

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A, Crutchfield Carolyn, and Barnes Marylou R, eds. Motor control and motor learning in rehabilitation. Atlanta, Ga: Stokesville Pub. Co., 1993.

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Latash, Mark L., and Francis Lestienne, eds. Motor Control and Learning. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/0-387-28287-4.

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Shea, Charles H. Motor learning and control. Boston, Mass: Allyn and Bacon, 1993.

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A, Wrisberg Craig, ed. Motor learning and performance. 2nd ed. Champaign, IL: Human Kinetics, 2000.

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A, Wrisberg Craig, ed. Motor learning and performance. 3rd ed. Champaign, IL: Human Kinetics, 2004.

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1948-, Reid Greg, and Collier Douglas Holden 1953-, eds. Motor learning and development. Champaign, IL: Human Kinetics, 2011.

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Wayne, Shebilske, and Worchel Stephen, eds. Motor learning and control. Englewood Cliffs, N.J: Prentice Hall, 1993.

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Capitoli di libri sul tema "Motor learning"

Barreiros, João, and Pedro Passos. "Guiding learning." In Motor Behavior, 236–49. New York: Routledge, 2025. https://doi.org/10.4324/9781003542391-17.

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Wulf, Gabriele. "Motor Learning." In Encyclopedia of the Sciences of Learning, 2348–50. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_869.

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Morgan, Michael M., MacDonald J. Christie, Thomas Steckler, Ben J. Harrison, Christos Pantelis, Christof Baltes, Thomas Mueggler, et al. "Motor Learning." In Encyclopedia of Psychopharmacology, 805. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_3411.

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Goertzel, Ben. "Motor Learning." In The Structure of Intelligence, 141–47. New York, NY: Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4612-4336-6_11.

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Carrière, Beate. "Motor Learning." In The Swiss Ball, 36–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58864-8_3.

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Jingcheng, Li. "Motor Learning." In The ECPH Encyclopedia of Psychology, 1–3. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-6000-2_981-1.

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Maring, Joyce R., and Susan Joy Leach. "Motor Learning." In Teaching and Learning in Physical Therapy, 239–68. 2nd ed. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781003526704-10.

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Barreiros, João, and Pedro Passos. "Memory and learning." In Motor Behavior, 19–37. New York: Routledge, 2025. https://doi.org/10.4324/9781003542391-4.

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Annett, John. "Motor Learning: A Review." In Motor Behavior, 189–212. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-69749-4_6.

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Barreiros, João, and Pedro Passos. "What is motor learning?" In Motor Behavior, 9–18. New York: Routledge, 2025. https://doi.org/10.4324/9781003542391-3.

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Atti di convegni sul tema "Motor learning"

Xiang, Tian-Yu, Xiao-Hu Zhou, Xiao-Liang Xie, Shi-Qi Liu, Mei-Jiang Gui, Hao Li, De-Xing Huang, and Zeng-Guang Hou. "Cross-Modal Motor Representation Learning." In 2024 International Joint Conference on Neural Networks (IJCNN), 1–8. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650264.

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Langlois, Quentin, and Sébastien Jodogne. "Embeddings for Motor Imagery Classification." In 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/mlsp58920.2024.10734730.

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Nishimura, Kotaro, Yoshikatsu Hayashi, Shiro Yano, and Toshiyuki Kondo. "Motor Learning through Cooperative Motor Experience." In 2018 International Symposium on Micro-NanoMechatronics and Human Science (MHS). IEEE, 2018. http://dx.doi.org/10.1109/mhs.2018.8886965.

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Daniel, Christian, Gerhard Neumann, Oliver Kroemer, and Jan Peters. "Learning sequential motor tasks." In 2013 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2013. http://dx.doi.org/10.1109/icra.2013.6630937.

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Bailly, David, Pierre Andry, and Philippe Gaussier. "Learning anticipatory motor control." In 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL). IEEE, 2012. http://dx.doi.org/10.1109/devlrn.2012.6400850.

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Parmar, Pritesh N., and James L. Patton. "Models of Motor Learning Generalization." In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. http://dx.doi.org/10.1109/embc.2018.8513182.

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Drix, Damien, and Verena V. Hafner. "Learning proprioceptive and motor features." In 2014 Joint IEEE International Conferences on Development and Learning and Epigenetic Robotics (ICDL-Epirob). IEEE, 2014. http://dx.doi.org/10.1109/devlrn.2014.6983010.

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Kober, Jens, and Jan Peters. "Learning motor primitives for robotics." In 2009 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2009. http://dx.doi.org/10.1109/robot.2009.5152577.

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Kirina, Elena, and Iurii Stroganov. "LEARNING OF SUPPORTING-MOTOR SYSTEM." In eLSE 2019. Carol I National Defence University Publishing House, 2019. http://dx.doi.org/10.12753/2066-026x-19-141.

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Desktop application for teaching the structure of the musculoskeletal system. Contains information about all bones and muscles and how to connect them. The application should run on Windows, Linux and MasOS. Visual representation in the form of a 3D model based on Unity. Realistic three-dimensional human model can be rotated and viewed from any angle. Select items by mouse click for detailed information about them. The ability to add your notes and signatures to parts of the system, so you can keep your own notes and make only the necessary information. All information is stored in a database. Latin will help to unify knowledge. Also all names will be given in accordance with international anatomical terminology (FIAT). Provide a function that allows you to select and study the desired system in isolation. For example, show only bones or only muscles. This will help to better understand the structure of individual systems. The application will be useful for both school and University studies. Due to the 3D view can learn and people who do not have a high medical or biological education. In recent decades, many software systems have been developed to systematize information about human anatomy. Using such programs is much more convenient than the usual paper collection. In addition, they can always take with you and quickly find what you need. Interactive interaction facilitates the learning process, provides mobility of access to information, makes it clearer and more understandable. Also, these systems can be used to develop mechanical analogues of the human body, which is currently a popular and promising direction of technology development.

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Bolagond, Vrashabha, Aniruddha Atre, and Amogh Gurumurthy. "Preliminary Design of Permanent Magnet Motor Using Machine Learning Algorithm and Analytical Method." In Automotive Technical Papers. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2024. http://dx.doi.org/10.4271/2024-01-5075.

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<div class="section abstract"><div class="htmlview paragraph">The global attention toward electric vehicles is growing tremendously, mainly because of environmental issues in recent years. There has been a significant increase in the development of hybrid and pure electric vehicles as they are considered as an effective solution for reducing the carbon footprint. There is a lot of research happening, especially in the design of high-performance e-motors for electric powertrain applications. In this paper, the focus is on the permanent magnet synchronous motors (PMSM) due to its higher efficiency and more advantageous torque characteristics compared to other types of motors. This paper presents a procedure for determining the initial design parameters using analytical calculation method for a PMSM, followed by developing machine learning algorithms (XGBoost, random forest, and artificial neural networks) with the available benchmarking data and compare their performance to determine the motor design parameters. A comparison study with the results obtained from analytical calculation and machine learning algorithm is carried out in determining the initial sizing parameters, and we have obtained an accuracy of 80%. We believe that this machine learning algorithm design approach will help in saving the time needed for theoretical design, and with an optimum design solution, can reduce the time and iterations of FEA required while designing an e-motor.</div></div>

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Rapporti di organizzazioni sul tema "Motor learning"

Hudson, Kesha N., and Michael T. Willoughby. The Multiple Benefits of Motor Competence Skills in Early Childhood. RTI Press, August 2021. http://dx.doi.org/10.3768/rtipress.2021.rb.0027.2108.

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Recent findings from the Kids Activity and Learning Study complement North Carolina’s multidimensional approach to promoting school readiness by emphasizing the integrated nature of motor and cognitive development in early childhood. Children whose motor skills improved the most over the course of an academic year also tended to demonstrate the biggest gains in executive function and numeracy skills. Children who participated in adaptive, group-based motor skill activities demonstrated gains in motor competence, executive function, and numeracy skills. Incorporating motor activities into established classroom practices has the potential to facilitate multiple aspects of children’s development and promote school readiness. The brief includes specific recommendations for early childhood educators.

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Nickerson, Jeffrey, Kalle Lyytinen, and John L. King. Automated Vehicles: A Human/Machine Co-learning Perspective. SAE International, April 2022. http://dx.doi.org/10.4271/epr2022009.

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Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement.

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Jelsma, Dorothee, Reza Abdollahipour, Farhad Ghadiri, Fatemeh Alaei, Miriam Paloma Nieto, Zdenek Svoboda, Miguel Villa de Gregorio, Paola Violasdotter Nilsson, Dido Green, and Kamila Banatova. Evidence-based practice interventions for children and young people with Developmental Coordination Disorder - A scoping review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, February 2023. http://dx.doi.org/10.37766/inplasy2023.2.0028.

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Review question / Objective: The aim of this review was to identify, qualify, evaluate and synthesise interventions used for children and young people with Developmental Coordination Disorder. The PCC was used to develop the review question: Population – children and young people with disorders of motor coordination aged to 25 years, not due to neurological disease or disorder eg. Cerebral Palsy. Concept - any method aimed to improve/treat/intervene in areas of motor learning, motor control, motor coordination or motor skill. Context - information on methods of delivery of interventions to consider context and cultural factors influencing delivery as well as details of intervention timing and outcomes. Primary Question: What interventions are being used for children and young people with DCD? Secondary Questions: How are these interventions being implemented? What outcomes are evident?

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Thompson, Richard F. A Biological Neural Network Analysis of Learning and Memory: The Cerebellum and Sensory Motor Conditioning. Fort Belvoir, VA: Defense Technical Information Center, November 1995. http://dx.doi.org/10.21236/ada304568.

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Jie, Li-Juan, Melanie Kleynen, Guus Rothuizen, Elmar Kal, Andreas Rothgangel, and Susy Braun. Overview of effects of motor learning strategies in neurological and geriatric populations: a systematic mapping review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, March 2024. http://dx.doi.org/10.37766/inplasy2024.3.0056.

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Arhin, Stephen, Babin Manandhar, and Adam Gatiba. Influence of Pavement Conditions on Commercial Motor Vehicle Crashes. Mineta Transportation Institute, December 2023. http://dx.doi.org/10.31979/mti.2023.2343.

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Commercial motor vehicle (CMV) safety is a major concern in the United States, including the District of Columbia (DC), where CMVs make up 15% of traffic. This research uses a comprehensive approach, combining statistical analysis and machine learning techniques, to investigate the impact of road pavement conditions on CMV accidents. The study integrates traffic crash data from the Traffic Accident Reporting and Analysis Systems Version 2.0 (TARAS2) database with pavement condition data provided by the District Department of Transportation (DDOT). Data spanning from 2016 to 2020 was collected and analyzed, focusing on CMV routes in DC. The analysis employs binary logistic regression to explore relationships between injury occurrence after a CMV crash and multiple independent variables. Additionally, Artificial Neural Network (ANN) models were developed to classify CMV crash injury severity. Importantly, the inclusion of pavement condition variables (International Roughness Index and Pavement Condition Index) substantially enhanced the accuracy of the logistic regression model, increasing predictability from 0.8% to 41%. The study also demonstrates the potential of Artificial Neural Network models in predicting CMV crash injury severity, achieving an accuracy of 60% and an F-measure of 0.52. These results highlight the importance of considering road pavement conditions in road safety policies and interventions. The study provides valuable insights for policymakers and stakeholders aiming to enhance road safety for CMVs in the District of Columbia and showcases the potential of machine learning techniques in understanding the complex interplay between road conditions and CMV crash occurrences.

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ji, yuqin, hao tian, qiang ye, zhuoyan ye, and zeyu zheng. Effectiveness of exercise intervention on improving fundamental motor skills in children with autism spectrum disorder: A systematic review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2022. http://dx.doi.org/10.37766/inplasy2022.12.0013.

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Review question / Objective: This systematic review and meta-analysis aimed to synthesize available randomized controlled trial studies concerning the effects of exercise interventions on fundamental motor skills in children with autism spectrum disorder. Condition being studied: Autism Spectrum Disorder (ASD) is a complicated and highly prevalent neuro-developmental disorder characterized by deficits in social communication, restricted interests, and repetitive behaviors. The CDC reported that the prevalence of ASD was estimated to be 1 in 59 in the United States by 2020. Along with typical symptoms, a couple of studies have indicated that individuals with ASD encounter a variety of challenges, including sleep disturbance, obesity, executive function deficits, physical inactivity, and motor dysfunctions. Fundamental motor skills (FMS) are the unnaturally occurring basic motor learning model of the human body, which are the building blocks for advanced specialized motor skills and for children and adolescents to participate in sports, games, or other context-specific physical activity.FMS falls into three different categories: (a) locomotor skills (e.g., running and hopping), (b) object control skills (e.g., catching and throwing), and balance or stability skills (e.g., balancing and twisting).

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Kulhandjian, Hovannes. AI-based Pedestrian Detection and Avoidance at Night using an IR Camera, Radar, and a Video Camera. Mineta Transportation Institute, November 2022. http://dx.doi.org/10.31979/mti.2022.2127.

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In 2019, the United States experienced more than 6,500 pedestrian fatalities involving motor vehicles which resulted in a 67% rise in nighttime pedestrian fatalities and only a 10% rise in daytime pedestrian fatalities. In an effort to reduce fatalities, this research developed a pedestrian detection and alert system through the application of a visual camera, infrared camera, and radar sensors combined with machine learning. The research team designed the system concept to achieve a high level of accuracy in pedestrian detection and avoidance during both the day and at night to avoid potentially fatal accidents involving pedestrians crossing a street. The working prototype of pedestrian detection and collision avoidance can be installed in present-day vehicles, with the visible camera used to detect pedestrians during the day and the infrared camera to detect pedestrians primarily during the night as well as at high glare from the sun during the day. The radar sensor is also used to detect the presence of a pedestrian and calculate their range and direction of motion relative to the vehicle. Through data fusion and deep learning, the ability to quickly analyze and classify a pedestrian’s presence at all times in a real-time monitoring system is achieved. The system can also be extended to cyclist and animal detection and avoidance, and could be deployed in an autonomous vehicle to assist in automatic braking systems (ABS).

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Slone, Scott, Marissa Torres, Alexander Stott, Ethan Thomas, and Robert Ibey. CRREL Environmental Wind Tunnel upgrades and the Snowstorm Library. Engineer Research and Development Center (U.S.), January 2024. http://dx.doi.org/10.21079/11681/48077.

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Environmental wind tunnels are ideal for basic research and applied physical modeling of atmospheric conditions and turbulent wind flow. The Cold Regions Research and Engineering Laboratory's own Environmental Wind Tunnel (EWT)—an open-circuit suction wind tunnel—has been historically used for snowdrift modeling. Recently the EWT has gone through several upgrades, namely the three-axis chassis motors, variable frequency drive, and probe and data acquisition systems. The upgraded wind tunnel was used to simulate various snowstorm conditions to produce a library of images for training machine learning models. Various objects and backgrounds were tested in snowy test conditions and no-snow control conditions, producing a total of 1.4 million training images. This training library can lead to improved machine learning models for image-cleanup and noise-reduction purposes for Army operations in snowy environments.

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