MOTION EVALUATION METHOD, COMPUTER PROGRAM, AND MOTION EVALUATION SYSTEM
A motion evaluation method includes: a noise removal step of removing noise in time-series data related to a motion of a person; an extraction step of extracting data of an on-set section in which the motion of the person is performed from the time-series data from which the noise has been removed; a compression step of aligning a length of the extracted data of the on-set section for each on-set section and compressing the data of the on-set section through down-sampling processing; and an evaluation step of evaluating the motion of the person on the basis of the compressed data of the on-set section.
1 . A motion evaluation method comprising:
removing noise in time-series data related to a motion of a person;
data of an on-set section in which the motion of the person is performed from the time-series data from which the noise has been removed;
aligning a length of the extracted data of the on-set section for each on-set section and compressing the data of the on-set section through down-sampling processing; and
evaluating the motion of the person on the basis of the compressed data of the on-set section.
2 . The motion evaluation method according to claim 1 , wherein, in the extracting, a section from a start point where the person is assumed to have started the motion to an end point where the person is assumed to have ended the motion is extracted as the on-set section on the time-series data.
3 . The motion evaluation method according to claim 2 , wherein, in the extracting, a value of the time-series data is compared with a value of a certain section immediately before and the on-set section is extracted from the time-series data with a point at which the value of the time-series data increases or decreases by a threshold value or more as the start point and a point that approaches an average value again at a time after the start point as the end point.
4 . The motion evaluation method according to claim 2 3, wherein, in the aligning, with data of a plurality of the on-set sections extracted in the extracting, the length of the data of the on-set section is aligned for each on-set section by matching start points of the data of all the on-set sections with data having the earliest time at the start point and matching end points of the data of all the on-set sections with data having the latest time at the end point.
5 . The motion evaluation method according to claim 1 , wherein, in the evaluating, person is evaluated using a trained model trained to output an evaluation score by inputting the data of the on-set section.
6 . A non-transitory computer readable storage medium that stores a computer program to be executed by the computer to perform:
removing noise in time-series data related to a motion of a person;
extracting data of an on-set section in which the motion of the person is performed from the time-series data from which the noise has been removed;
aligning a length of the extracted data of the on-set section for each on-set section and compressing the data of the on-set section through down-sampling processing; and
evaluating the motion of the person on the basis of the compressed data of the on-set section.
7 . A motion evaluation system comprising:
a sensor configured to acquire time-series data related to a motion of a person;
a noise remover configured to remove noise in the time-series data;
an extractor configured to extract data of an on-set section in which the motion of the person is performed from the time-series data from which the noise has been removed;
a compressor configured to align a length of the extracted data of the on-set section for each on-set section and compress the data of the on-set section through down-sampling processing; and
an evaluator configured to evaluate the motion of the person on the basis of the compressed data of the on-set section.