The paper proposes a data model analysis algorithm for human motion function based on short-term behaviour. Thealgorithm uses a functional data analysis (FDA) method to perform Fourier fitting on the motion data and extract the fittedapproximate single period data. Finally, the algorithm depicts the internal change in the motion in the low-dimensionalspace. The study found that the characteristic motion data obtained by the algorithm has smooth characteristics, and therelevant case analysis also verifies the algorithm’s effectiveness.
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