{"title":"Modeling of Body Pressure Distribution on Alternative Pressure Mattress","authors":"Masamichi Kosuge, Masaki Takahashi","doi":"10.1109/ICARA56516.2023.10125654","DOIUrl":null,"url":null,"abstract":"Recently, an alternative pressure mattress has been proposed to prevent pressure ulcers. In this study, we aim to design a control system for body pressure distribution using the mattress. This study focuses on modeling the dynamics between the body pressure distribution and the mattress. As modeling based on first principles is challenging, we identify the model from experimental data. However, when high-dimensional data such as body pressure distribution are directly used for identification, the model accuracy can deteriorate. Therefore, we need to determine the suitable model structure or dataset. Herein, we examined how the prediction accuracy of body pressure distribution varies with the dataset and model structure. We also proposed a method for representing the model as the dynamics of the parameters of the Gaussian Mixture Model to suppress the estimated parameters. To the best of our knowledge, this study is the first to propose the body pressure model as dynamics of the parameters of the Gaussian Mixture Model.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"131 10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARA56516.2023.10125654","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Recently, an alternative pressure mattress has been proposed to prevent pressure ulcers. In this study, we aim to design a control system for body pressure distribution using the mattress. This study focuses on modeling the dynamics between the body pressure distribution and the mattress. As modeling based on first principles is challenging, we identify the model from experimental data. However, when high-dimensional data such as body pressure distribution are directly used for identification, the model accuracy can deteriorate. Therefore, we need to determine the suitable model structure or dataset. Herein, we examined how the prediction accuracy of body pressure distribution varies with the dataset and model structure. We also proposed a method for representing the model as the dynamics of the parameters of the Gaussian Mixture Model to suppress the estimated parameters. To the best of our knowledge, this study is the first to propose the body pressure model as dynamics of the parameters of the Gaussian Mixture Model.