A Causal Analysis by Structural Equation Modeling of Sleep Monitoring Sensor Data

• 大石 信弘

  熊本高等専門学校

• 山本 直樹

  熊本高等専門学校

• 石田 明男

  熊本高等専門学校

• 村上 純

  熊本高等専門学校

Bibliographic Information

Other Title

• 睡眠見守りセンサーデータの構造方程式モデリングによる因果分析

Abstract

In this paper, structural equation modeling (SEM) is used to analyze the causal relationship between sleep stages and environmental data. The data used for the analysis is obtained by a care support device used in an elderly care facility. By applying the stepwise method to this data, we were able to find four observation variables that affect sleep stages. The latent variables are then determined by a scree plot. We proposed a causal model in which four observed variables and two latent variables affect sleep levels. Statistical analysis environment R and the lavaan package were used for SEM analysis in this paper. The results show that SEM can be used to build a rational model for the effects of vital signs and environmental conditions on good sleep.

Journal

• Research Reports of National Institute of Technology (KOSEN), Kumamoto College

  Research Reports of National Institute of Technology (KOSEN), Kumamoto College 11 (0), 83-86, 2020

  National Institute of Technology (KOSEN), Kumamoto College

Keywords

• sleep monitoring sensor
• causal analysis
• structural equation modeling
• R language

Details

• CRID: 1390005506397685504
• NII Article ID: 130007966580
• DOI: 10.50835/kumako.11.0_83
• ISSN: 21898553
• ISSN: 18846734
• Text Lang: ja
• Data Source:
  • JaLC
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed