Human Movements Are Shaped by Utilizing Sensory Information: A Stochastic Optimum Model

Mehran Emadi Andani

doi:10.20944/preprints202302.0073.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 2 February 2023 / Approved: 3 February 2023 / Online: 3 February 2023 (10:33:27 CET)

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.

human motor planning; sensory information; statistical model; minimum jerk; motor decomposition

Engineering, Bioengineering

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Human Movements Are Shaped by Utilizing Sensory Information: A Stochastic Optimum Model

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