Method for Detecting Validity of Human Body Movement

A non-transitory computer-readable medium having storage content, wherein the storage content causes a computing system to perform automated operations, comprising:

• obtaining a user movement dataset, the user movement dataset comprising a plurality of n-dimensional movement data items corresponding to a human body movement;
• vectorizing the user movement dataset to obtain a plurality of eigenvectors of the user movement dataset;
• and
• inputting the plurality of eigenvectors of the user movement dataset into a validity detection model to determine whether the human body movement corresponding to the user movement dataset is valid;
• wherein the validity detection model comprises a baseline center and a baseline Mahalanobis distance threshold, and wherein determining whether the human body movement corresponding to the user movement dataset is valid comprises:
• determining a proportion, out of the plurality of eigenvectors of the user movement dataset, of eigenvectors having a Mahalanobis distance from the baseline center that does not exceed the baseline Mahalanobis distance threshold;
• and
• determining whether the proportion is greater than a proportion threshold;
• determining that the human body movement corresponding to the user movement dataset is valid in response to the proportion being greater than the proportion threshold;
• determining that the human body movement corresponding to the user movement dataset is invalid in response to the proportion being not greater than the proportion threshold.

A system, comprising:

• one or more processors;
• a wireless communication module configured to obtain a user movement dataset;
• and at least one memory having stored instructions that, when executed by at least one of the one or more processors, cause the system to perform automated operations comprising:
• obtaining a user movement dataset, the user movement dataset comprising a plurality of n-dimensional movement data items corresponding to human body movement;
• vectorizing the user movement dataset to obtain a plurality of eigenvectors of the user movement dataset;
• and
• inputting the plurality of eigenvectors of the user movement dataset into a validity detection model to determine whether the human body movement corresponding to the user movement dataset is valid;
• wherein the validity detection model comprises a baseline center and a baseline Mahalanobis distance threshold, and wherein determining whether the human body movement corresponding to the user movement dataset is valid comprises:
• determining a proportion, out of the plurality of eigenvectors of the user movement dataset, of eigenvectors having a Mahalanobis distance from the baseline center that does not exceed the baseline Mahalanobis distance threshold;
• and
• determining whether the proportion is greater than a proportion threshold;
• determining that the human body movement corresponding to the user movement dataset is valid in response to the proportion being greater than the proportion threshold;
• determining that the human body movement corresponding to the user movement dataset is invalid in response to the proportion being not greater than the proportion threshold.