Gregory R. Roytman, Matthew Budavich, Judith D. Pocius, Jocelyn Faydenko, Dana Muligano, G. Cramer
{"title":"基于压电加速度计和自动信号分析的振动和声震传感","authors":"Gregory R. Roytman, Matthew Budavich, Judith D. Pocius, Jocelyn Faydenko, Dana Muligano, G. Cramer","doi":"10.1115/imece2021-67348","DOIUrl":null,"url":null,"abstract":"\n The vibration and acoustic emissions produced within facet joints of the lumbar spine, known as crepitus, can be a potential biomarker to identify decreased joint functioning and the site of low back pain. Using piezoelectric accelerometers and a silicone “phantom” mechanical model we sought to identify the site of crepitus. Past analyses of these data with human observers have been too time consuming for eventual practical clinical application, and a more expedient algorithmic method of analysis is preferable. In this study the signal filtering and processing functions of MATLAB were harnessed to filter aberrant noise as well as determine the location (level and left or right side) from which crepitus originated during induced crepitus events in the phantom model (n = 30). Development of this automated method refined the definition of facet joint crepitus. The automated method was found to be as reliable and valid as assessment by human observers, and took significantly less time (p = 0.009). Future studies will assess the reliability of the automated method to detect this phenomenon in humans.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vibration and Acoustic Crepitus Sensing Using Piezoelectric Accelerometers and Automated Signal Analysis\",\"authors\":\"Gregory R. Roytman, Matthew Budavich, Judith D. Pocius, Jocelyn Faydenko, Dana Muligano, G. Cramer\",\"doi\":\"10.1115/imece2021-67348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n The vibration and acoustic emissions produced within facet joints of the lumbar spine, known as crepitus, can be a potential biomarker to identify decreased joint functioning and the site of low back pain. Using piezoelectric accelerometers and a silicone “phantom” mechanical model we sought to identify the site of crepitus. Past analyses of these data with human observers have been too time consuming for eventual practical clinical application, and a more expedient algorithmic method of analysis is preferable. In this study the signal filtering and processing functions of MATLAB were harnessed to filter aberrant noise as well as determine the location (level and left or right side) from which crepitus originated during induced crepitus events in the phantom model (n = 30). Development of this automated method refined the definition of facet joint crepitus. The automated method was found to be as reliable and valid as assessment by human observers, and took significantly less time (p = 0.009). Future studies will assess the reliability of the automated method to detect this phenomenon in humans.\",\"PeriodicalId\":314012,\"journal\":{\"name\":\"Volume 5: Biomedical and Biotechnology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 5: Biomedical and Biotechnology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/imece2021-67348\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 5: Biomedical and Biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2021-67348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vibration and Acoustic Crepitus Sensing Using Piezoelectric Accelerometers and Automated Signal Analysis
The vibration and acoustic emissions produced within facet joints of the lumbar spine, known as crepitus, can be a potential biomarker to identify decreased joint functioning and the site of low back pain. Using piezoelectric accelerometers and a silicone “phantom” mechanical model we sought to identify the site of crepitus. Past analyses of these data with human observers have been too time consuming for eventual practical clinical application, and a more expedient algorithmic method of analysis is preferable. In this study the signal filtering and processing functions of MATLAB were harnessed to filter aberrant noise as well as determine the location (level and left or right side) from which crepitus originated during induced crepitus events in the phantom model (n = 30). Development of this automated method refined the definition of facet joint crepitus. The automated method was found to be as reliable and valid as assessment by human observers, and took significantly less time (p = 0.009). Future studies will assess the reliability of the automated method to detect this phenomenon in humans.