Article
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Human Movements Are Shaped by Utilizing Sensory Information: A Stochastic Optimum Model
Version 1
: Received: 2 February 2023 / Approved: 3 February 2023 / Online: 3 February 2023 (10:33:27 CET)
How to cite: Emadi Andani, M. Human Movements Are Shaped by Utilizing Sensory Information: A Stochastic Optimum Model. Preprints 2023, 2023020073. https://doi.org/10.20944/preprints202302.0073.v1 Emadi Andani, M. Human Movements Are Shaped by Utilizing Sensory Information: A Stochastic Optimum Model. Preprints 2023, 2023020073. https://doi.org/10.20944/preprints202302.0073.v1
Abstract
Human motor planning combines such interesting aspects as modular organization in motor primitives and characteristics of stochastic optimality. Motor primitives aided in the description of motor skill learning. In this study, for the first time, an interpretation is proposed to explain how motor primitives are shaped in a stochastic optimality process.To this end, sensory information is assumed to be random variables at each moment. Theoretically, the results confirmed that the variability of a movement increased with passing time. As a result, motor planning should be performed in shorter durations to achieve an accurate movement. It means that a task should be divided into several subtasks at various stages of time. Moreover, theoretically, the results confirmed that motor planning is statistically optimal if the movement is planned in minimum jerk space, which is in accordance with what is reported in the literature. Comparing the proposed mathematical model with the results of experimental data in two different types of motor action (i.e., arm reaching movement and sit-to-stand transfer from a chair) confirmed that the proposed model can be considered a framework to investigate the effect of bottom-up information on human motor planning level. Further experiments need to investigate it more deeply.
Keywords
human motor planning; sensory information; statistical model; minimum jerk; motor decomposition
Subject
Engineering, Bioengineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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