{"title":"A Statistical Method for Footprints Analysis based on Large-scale High-density Piezoresistive Films","authors":"Bo Wang, Chengxiang Liu, Peng Shang","doi":"10.1145/3502060.3502148","DOIUrl":null,"url":null,"abstract":"Footprints can provide much valuable information for fall prediction, the diagnosis of many diseases and rehabilitation therapy. This paper aims to propose a statistical method for footprints analysis based on a large-scale high-density piezoresistive film to replace the manual work of obtaining the main parameters of footprint data. Firstly, data acquisition devices are developed to obtain the plantar pressure distribution by measuring the voltage changes caused by the applied pressure on the piezoresistive films. Subsequently, a specific software is developed to receive the data from the designed signal acquisition devices through the serial port and visualize the footprints, and a statistical method is proposed to distinguish between left footprint and right footprint and to obtain the direction of the footprints and the step length. Eventually, a series of experiments are conducted to obtain the accuracy of the proposed method used for different people's feet and with different walking speeds.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"602 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Symposium on Biomedical Engineering and Computational Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3502060.3502148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Footprints can provide much valuable information for fall prediction, the diagnosis of many diseases and rehabilitation therapy. This paper aims to propose a statistical method for footprints analysis based on a large-scale high-density piezoresistive film to replace the manual work of obtaining the main parameters of footprint data. Firstly, data acquisition devices are developed to obtain the plantar pressure distribution by measuring the voltage changes caused by the applied pressure on the piezoresistive films. Subsequently, a specific software is developed to receive the data from the designed signal acquisition devices through the serial port and visualize the footprints, and a statistical method is proposed to distinguish between left footprint and right footprint and to obtain the direction of the footprints and the step length. Eventually, a series of experiments are conducted to obtain the accuracy of the proposed method used for different people's feet and with different walking speeds.