2022 Fiscal Year Research-status Report
Enhancing motor skill learning by manipulating extrinsic and intrinsic components of the motor task
| Project/Area Number |
21K17789
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
Barradas Victor 東京工業大学, 科学技術創成研究院, 特任助教 (70883908)
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Keywords | speed of motor learning / manipulability ellipse / target distribution / muscle co-contraction |
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| Outline of Annual Research Achievements |
The main objective of this project is to identify intrinsic and extrinsic factors that can be exploited to increase the speed of learning a motor task. Following the success of my computational model to enhance the speed of learning in an isometric task, I have now applied the model to a more complex dynamic reaching task. In this task, the factors that influence the speed of learning are the dynamic manipulability ellipse of the arm, and the distribution of arm states during the task. This allows to make predictions about the effect of variables such as arm posture and arm mass in the speed of learning a dynamic task. In parallel, I have also developed a system that allows the directed learning of desired muscle activations via EMG-biofeedback in a virtual polishing task.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
My research is progressing smoothly according to the timeframe that I initially proposed. However, the publication of the results is taking significantly longer than expected due to reasons out of my control. According to the editors of the journals I have submitted to, it has taken an unusually long time to secure reviewers for the peer review process for my studies.
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| Strategy for Future Research Activity |
As defined in the project timeline, the current phase of the project is 2) the kinematic/dynamic phase. I have developed the computational theory for this phase, and now plan to go on to the experimental phase. For the remaining year in the project, I plan to combine the experimental aspect of the kinematic/dynamic phase with the next phase of the project: 3) tool design phase. This is because the computational principles of the model allow to work on both phases in parallel.
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| Causes of Carryover |
Because the funds dedicated to the first year of the project could not be used in that year due to delays in the publication cycle and the global pandemic, they were transferred to the second year. During the second year, most of the funds could be spent as planned. However a relatively small amount remained due to the larger than planned for budget, because of the carryover from the first year. I would like to use this remaining funds to supplement my budget for publications in the third year.
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