{"id":{"repo_id":"uwo","oai_identifier":"oai:uwo.scholaris.ca:20.500.14721/37548"},"canonical_url":"https://search.dev.ndltd.org/etd/uwo/oai:uwo.scholaris.ca:20.500.14721/37548","repository":{"repo_id":"uwo","name":"Western University","base_url":"https://uwo.scholaris.ca/server/oai/request"},"display":{"title":"Understanding real-world and laboratory traumatic brain injury (TBI) using the computational model with brain functional regions","abstract":"Traumatic brain injury (TBI), including mild traumatic brain injury (mTBI) or concussion, is a severe health concern. Many symptoms, such as headache, dizziness, and working memory deficits, are reported to be related to the dysfunction of brain functional regions, but the underlying mechanism remains unknown. Hence, further developing tools and analyses to understand brain dysfunction for better TBI prevention are important. Additionally, such analyses should be conducted for both real-world TBI cases and laboratory studies, as TBI data can only be collected from the real world, and prevention measures, such as helmets, are developed and evaluated in the lab. Accordingly, this biomechanical study addressed four mTBI-related topics: 1) developing a novel pipeline that can segment the brain finite element (FE) into up to 1000 functional brain regions based on an advanced brain functional atlas; 2) using 39 national football legacy (NFL) kinematic curves (including 13 concussive impacts) which were collected and reconstructed from in-field mTBI impacts, the brain strain responses including strain of each functional region and strain-affected connections among brain functional regions were analyzed; 3) helmet protection mechanism was analyzed by investigating the characteristics of the helmet shell and foam under laboratory impacts; 4) effects of skull thickness change due to repeated mTBI impacts on head kinematics-based and brain strain-based responses were also investigated. This study found that: 1) certain brain functional regions consistently experienced high strain among mTBI impacts under various impacts, indicating their contribution to brain damage; 2) the brain strain could affect the functional connectivity of working memory tasks; 3) among the entire impact events, helmet outer shell absorbed the highest amount of strain energy, while helmet foam played an important role in brain strain responses based on factorial analysis; 4) the increase in skull thickness and the change in skull density had the small effect on head kinematics-based and brain strain responses. In brief, novel brain FE models with detailed function regions were developed. Using the new modeling technique, the potential effects of brain functional region strain under both real-world and laboratory settings, as well as repeated-mTBI-relevant skull changes, were analyzed.","abstract_html":"Traumatic brain injury (TBI), including mild traumatic brain injury (mTBI) or concussion, is a severe health concern. Many symptoms, such as headache, dizziness, and working memory deficits, are reported to be related to the dysfunction of brain functional regions, but the underlying mechanism remains unknown. Hence, further developing tools and analyses to understand brain dysfunction for better TBI prevention are important. Additionally, such analyses should be conducted for both real-world TBI cases and laboratory studies, as TBI data can only be collected from the real world, and prevention measures, such as helmets, are developed and evaluated in the lab. Accordingly, this biomechanical study addressed four mTBI-related topics: 1) developing a novel pipeline that can segment the brain finite element (FE) into up to 1000 functional brain regions based on an advanced brain functional atlas; 2) using 39 national football legacy (NFL) kinematic curves (including 13 concussive impacts) which were collected and reconstructed from in-field mTBI impacts, the brain strain responses including strain of each functional region and strain-affected connections among brain functional regions were analyzed; 3) helmet protection mechanism was analyzed by investigating the characteristics of the helmet shell and foam under laboratory impacts; 4) effects of skull thickness change due to repeated mTBI impacts on head kinematics-based and brain strain-based responses were also investigated. This study found that: 1) certain brain functional regions consistently experienced high strain among mTBI impacts under various impacts, indicating their contribution to brain damage; 2) the brain strain could affect the functional connectivity of working memory tasks; 3) among the entire impact events, helmet outer shell absorbed the highest amount of strain energy, while helmet foam played an important role in brain strain responses based on factorial analysis; 4) the increase in skull thickness and the change in skull density had the small effect on head kinematics-based and brain strain responses. In brief, novel brain FE models with detailed function regions were developed. Using the new modeling technique, the potential effects of brain functional region strain under both real-world and laboratory settings, as well as repeated-mTBI-relevant skull changes, were analyzed.","abstract_has_math":false,"creators":["Bian, Kewei"],"institution":"The University of Western Ontario","degree_name":"Ph D","degree_level":null,"degree_discipline":"Mechanical and Materials Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Mao, Haojie"],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-12-06","date_published":"2023-12-06","updated_at":"2026-07-27T21:56:01Z","subjects":["TBI","brain functional regions","brain strain responses","brain strain-based connections","helmet","repeated-mTBI"],"languages":["en_ca"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/20.500.14721/37548","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Mao, Haojie"]},{"key":"dc:creator","label":"Author","values":["Bian, Kewei"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-07-10T21:37:59Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-07-10T21:37:59Z"]},{"key":"dc:date.issued","label":"Date","values":["2023-12-06"]},{"key":"dc:publisher","label":"Institution","values":["The University of Western Ontario"]},{"key":"dc:type","label":"Dc Type","values":["thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical and Materials Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph D"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["TBI","brain functional regions","brain strain responses","brain strain-based connections","helmet","repeated-mTBI"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_ca"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.14721/37548"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The thesis cover page in the PDF document includes references to Western University’s previous institutional repository platform, known as Scholarship@Western, and links to that platform (beginning with ir.lib.uwo.ca). In citing or referring to this thesis, use the DOI or handle from this page instead. Sample citation: Author name, \"Thesis title.\" (Year). Western University Open Repository. https://doi.org/10.71858/123456."]},{"key":"dc:description.abstract","label":"Abstract","values":["Traumatic brain injury (TBI), including mild traumatic brain injury (mTBI) or concussion, is a severe health concern. Many symptoms, such as headache, dizziness, and working memory deficits, are reported to be related to the dysfunction of brain functional regions, but the underlying mechanism remains unknown. Hence, further developing tools and analyses to understand brain dysfunction for better TBI prevention are important. Additionally, such analyses should be conducted for both real-world TBI cases and laboratory studies, as TBI data can only be collected from the real world, and prevention measures, such as helmets, are developed and evaluated in the lab. Accordingly, this biomechanical study addressed four mTBI-related topics: 1) developing a novel pipeline that can segment the brain finite element (FE) into up to 1000 functional brain regions based on an advanced brain functional atlas; 2) using 39 national football legacy (NFL) kinematic curves (including 13 concussive impacts) which were collected and reconstructed from in-field mTBI impacts, the brain strain responses including strain of each functional region and strain-affected connections among brain functional regions were analyzed; 3) helmet protection mechanism was analyzed by investigating the characteristics of the helmet shell and foam under laboratory impacts; 4) effects of skull thickness change due to repeated mTBI impacts on head kinematics-based and brain strain-based responses were also investigated. This study found that: 1) certain brain functional regions consistently experienced high strain among mTBI impacts under various impacts, indicating their contribution to brain damage; 2) the brain strain could affect the functional connectivity of working memory tasks; 3) among the entire impact events, helmet outer shell absorbed the highest amount of strain energy, while helmet foam played an important role in brain strain responses based on factorial analysis; 4) the increase in skull thickness and the change in skull density had the small effect on head kinematics-based and brain strain responses. In brief, novel brain FE models with detailed function regions were developed. Using the new modeling technique, the potential effects of brain functional region strain under both real-world and laboratory settings, as well as repeated-mTBI-relevant skull changes, were analyzed."]},{"key":"dc:title","label":"Title","values":["Understanding real-world and laboratory traumatic brain injury (TBI) using the computational model with brain functional regions"]}]}],"canonical_facts":{"dc:contributor.advisor":["Mao, Haojie"],"dc:creator":["Bian, Kewei"],"dc:date.accessioned":["2025-07-10T21:37:59Z"],"dc:date.available":["2025-07-10T21:37:59Z"],"dc:date.issued":["2023-12-06"],"dc:description":["The thesis cover page in the PDF document includes references to Western University’s previous institutional repository platform, known as Scholarship@Western, and links to that platform (beginning with ir.lib.uwo.ca). In citing or referring to this thesis, use the DOI or handle from this page instead. Sample citation: Author name, \"Thesis title.\" (Year). Western University Open Repository. https://doi.org/10.71858/123456."],"dc:description.abstract":["Traumatic brain injury (TBI), including mild traumatic brain injury (mTBI) or concussion, is a severe health concern. Many symptoms, such as headache, dizziness, and working memory deficits, are reported to be related to the dysfunction of brain functional regions, but the underlying mechanism remains unknown. Hence, further developing tools and analyses to understand brain dysfunction for better TBI prevention are important. Additionally, such analyses should be conducted for both real-world TBI cases and laboratory studies, as TBI data can only be collected from the real world, and prevention measures, such as helmets, are developed and evaluated in the lab. Accordingly, this biomechanical study addressed four mTBI-related topics: 1) developing a novel pipeline that can segment the brain finite element (FE) into up to 1000 functional brain regions based on an advanced brain functional atlas; 2) using 39 national football legacy (NFL) kinematic curves (including 13 concussive impacts) which were collected and reconstructed from in-field mTBI impacts, the brain strain responses including strain of each functional region and strain-affected connections among brain functional regions were analyzed; 3) helmet protection mechanism was analyzed by investigating the characteristics of the helmet shell and foam under laboratory impacts; 4) effects of skull thickness change due to repeated mTBI impacts on head kinematics-based and brain strain-based responses were also investigated. This study found that: 1) certain brain functional regions consistently experienced high strain among mTBI impacts under various impacts, indicating their contribution to brain damage; 2) the brain strain could affect the functional connectivity of working memory tasks; 3) among the entire impact events, helmet outer shell absorbed the highest amount of strain energy, while helmet foam played an important role in brain strain responses based on factorial analysis; 4) the increase in skull thickness and the change in skull density had the small effect on head kinematics-based and brain strain responses. In brief, novel brain FE models with detailed function regions were developed. Using the new modeling technique, the potential effects of brain functional region strain under both real-world and laboratory settings, as well as repeated-mTBI-relevant skull changes, were analyzed."],"dc:identifier.uri":["https://hdl.handle.net/20.500.14721/37548"],"dc:language.iso":["en_ca"],"dc:publisher":["The University of Western Ontario"],"dc:subject":["TBI","brain functional regions","brain strain responses","brain strain-based connections","helmet","repeated-mTBI"],"dc:title":["Understanding real-world and laboratory traumatic brain injury (TBI) using the computational model with brain functional regions"],"dc:type":["thesis"],"thesis:degree_discipline":["Mechanical and Materials Engineering"],"thesis:degree_name":["Ph D"]},"updated_at":"2026-07-27T21:56:01Z"}