Application of Supervised Principal Motion Analysis to Evaluate Subjectively Easy Sit-to-Stand Motion of Healthy People

Chongyang Qiu,Shogo Okamoto,Yoji Yamada,Yasuhiro Akiyama

doi:10.1109/access.2021.3078202

Chongyang Qiu, Shogo Okamoto + Show 2 more

Open Access

https://doi.org/10.1109/access.2021.3078202

Copy DOI

Abstract

Redundant human motions such as walking or sit-to-stand motions involve time-series data of several variables. Principal motion analysis (PMA) can be adopted to decompose such motions into independent motions, and their linear combinations can be used to approximate the motions. In contrast to the existing PMA methods, which are unsupervised, we applied partial least-squares regression to perform PMA such that the scores for the principal motions were correlated with a continuous objective variable. To validate the practicality of this approach, we investigated the subjectively easy sit-to-stand movement of healthy people. The participants were six healthy young individuals who performed the sit-to-stand movement under 33 different conditions by changing the foot position, hand-grip position, and initial pitch angle of the upper body. The motion data and magnitude of the subjective burden reported for each movement were analyzed. Three principal motions correlated with the subjective burdens were determined and interpreted. The correlation coefficients of the first, second, and third principal motions and the subjective burdens were 0.60, 0.27, and 0.19, respectively. Moreover, the sit-to-stand conditions synthesized by the three principal motions incurred a burden subjectively smaller than or comparable to the burdens in other conditions.

Highlights

B Y analyzing human motions, certain recommendations can be suggested, for example, to ease motion-related pain and reduce the energy consumption
Bartlett’s test can be used to determine the number of principal components for principal component analysis (PCA). This test was incorporated in the present analysis; this approach resulted in a larger number of significant principal motions, i.e., nine, several of which exhibited extremely small correlation coefficients with the subjective burdens
TO SYNTHESIZE SUBJECTIVELY EASY SIT-TO-STAND MOTIONS Based on the relationships between the principal motions and subjective burdens, to determine the sit-to-stand motions with small subjective burdens, we investigated a number of combinations of the three principal motions

Summary

Introduction

B Y analyzing human motions, certain recommendations can be suggested, for example, to ease motion-related pain and reduce the energy consumption. Human motion is dynamic and involves multiple joints; instead of the principal component analysis (PCA), principal motion analysis (PMA) is used to analyze this motion [1]–[5]. Similar to PCA, PMA reduces the dimensions of the parameter spaces without losing the information of the dynamically interlocked multiple degrees of freedom of redundant systems. The set of the correlated time-series of these multiple degrees of freedom is termed as the principal motion or motion synergy. Any sampled motion can be approximated by the linear combinations of several principal motions when the sample set fits the space, with the scores of the principal motions corresponding to the base. PMA represents the time-extension of the PCA, and it is an unsupervised method

Objectives

Methods

Results

Conclusion