{"title":"Machine Learning Enabled Wearable Brain Deformation Sensing System","authors":"Sayemul Islam, Albert Kim","doi":"10.1109/SPMB47826.2019.9037843","DOIUrl":null,"url":null,"abstract":"Brain deformation – the primary cause of traumatic brain injury (TBI) – occurs during fall, automobile accident, brain surgery, or explosion (i.e., pressurized airflow) [1] . Mechanical impact causes strain energy that leads to tissue displacement. Researchers have attempted to characterize the brain deformation for diagnosis and prevention of concussion-related TBI [2] . It is especially important to measure microscale deformation because even a few tens of micrometer brain deformation may have direct neuropsychiatric and neuro-degenerative consequences [3] – [6] . Another effort to minimize brain deformation can be found in intracranial surgeries. The deformation is inevitable but can be minimized by designing a better apparatus and using advance stereotactic techniques [7] – [9] . As such, there are a few methods to measure brain deformation today [8] , [10] – [12] . Computational models and imaging technologies (e.g., FEM (finite element method) modeling, magnetic resonance imaging (MRI)) are such examples. However, because the brain is viscoelastic [13] , these technologies lack 1) detailed information regarding micro-scale brain deformation and 2) real-time measurement capability.","PeriodicalId":143197,"journal":{"name":"2019 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPMB47826.2019.9037843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Brain deformation – the primary cause of traumatic brain injury (TBI) – occurs during fall, automobile accident, brain surgery, or explosion (i.e., pressurized airflow) [1] . Mechanical impact causes strain energy that leads to tissue displacement. Researchers have attempted to characterize the brain deformation for diagnosis and prevention of concussion-related TBI [2] . It is especially important to measure microscale deformation because even a few tens of micrometer brain deformation may have direct neuropsychiatric and neuro-degenerative consequences [3] – [6] . Another effort to minimize brain deformation can be found in intracranial surgeries. The deformation is inevitable but can be minimized by designing a better apparatus and using advance stereotactic techniques [7] – [9] . As such, there are a few methods to measure brain deformation today [8] , [10] – [12] . Computational models and imaging technologies (e.g., FEM (finite element method) modeling, magnetic resonance imaging (MRI)) are such examples. However, because the brain is viscoelastic [13] , these technologies lack 1) detailed information regarding micro-scale brain deformation and 2) real-time measurement capability.