使用内部构建的角计和naïve贝叶斯分类器进行步态信号分类

R. Khnouf, E. Abdulhay, Rawan Al Junaidi, F. Rifai
{"title":"使用内部构建的角计和naïve贝叶斯分类器进行步态信号分类","authors":"R. Khnouf, E. Abdulhay, Rawan Al Junaidi, F. Rifai","doi":"10.1504/IJMEI.2017.10002621","DOIUrl":null,"url":null,"abstract":"This work aims at designing and implementing a knee and an ankle goniometer, both based on potentiometry, and applying the naive Bayes classifier on the signals obtained from the goniometers to differentiate between male and female gait signals, and to also differentiate between healthy and restricted knee gait signals. Gait signals and other parameters were collected from 60 subjects using the goniometers and WEKA was used to classify this data. The designed goniometers were 97.8% accurate and the naive Bayes classifier was highly accurate in categorising the signals with an accuracy of at least 86.7%.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gait signal classification using an in-house built goniometer and naïve Bayes classifier\",\"authors\":\"R. Khnouf, E. Abdulhay, Rawan Al Junaidi, F. Rifai\",\"doi\":\"10.1504/IJMEI.2017.10002621\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work aims at designing and implementing a knee and an ankle goniometer, both based on potentiometry, and applying the naive Bayes classifier on the signals obtained from the goniometers to differentiate between male and female gait signals, and to also differentiate between healthy and restricted knee gait signals. Gait signals and other parameters were collected from 60 subjects using the goniometers and WEKA was used to classify this data. The designed goniometers were 97.8% accurate and the naive Bayes classifier was highly accurate in categorising the signals with an accuracy of at least 86.7%.\",\"PeriodicalId\":193362,\"journal\":{\"name\":\"Int. J. Medical Eng. Informatics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Medical Eng. Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJMEI.2017.10002621\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Medical Eng. Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJMEI.2017.10002621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究旨在设计和实现基于电位计的膝关节和踝关节测角仪,并对测角仪获得的信号应用朴素贝叶斯分类器来区分男性和女性步态信号,以及区分健康和受限的膝关节步态信号。使用测角仪收集60名受试者的步态信号和其他参数,并使用WEKA对这些数据进行分类。设计的测角仪的准确率为97.8%,朴素贝叶斯分类器对信号的分类准确率很高,准确率至少为86.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gait signal classification using an in-house built goniometer and naïve Bayes classifier
This work aims at designing and implementing a knee and an ankle goniometer, both based on potentiometry, and applying the naive Bayes classifier on the signals obtained from the goniometers to differentiate between male and female gait signals, and to also differentiate between healthy and restricted knee gait signals. Gait signals and other parameters were collected from 60 subjects using the goniometers and WEKA was used to classify this data. The designed goniometers were 97.8% accurate and the naive Bayes classifier was highly accurate in categorising the signals with an accuracy of at least 86.7%.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信