Volume 3: Biomedical and Biotechnology Engineering最新文献_第9页

Machine Learning Classification of Head Impact Sensor Data 头部碰撞传感器数据的机器学习分类

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2019-11-11 DOI: 10.1115/imece2019-12173

Tyler F. Rooks, Andrea S. Dargie, V. Chancey

{"title":"Machine Learning Classification of Head Impact Sensor Data","authors":"Tyler F. Rooks, Andrea S. Dargie, V. Chancey","doi":"10.1115/imece2019-12173","DOIUrl":"https://doi.org/10.1115/imece2019-12173","url":null,"abstract":"\u0000 A shortcoming of using environmental sensors for the surveillance of potentially concussive events is substantial uncertainty regarding whether the event was caused by head acceleration (“head impacts”) or sensor motion (with no head acceleration). The goal of the present study is to develop a machine learning model to classify environmental sensor data obtained in the field and evaluate the performance of the model against the performance of the proprietary classification algorithm used by the environmental sensor. Data were collected from Soldiers attending sparring sessions conducted under a U.S. Army Combatives School course. Data from one sparring session were used to train a decision tree classification algorithm to identify good and bad signals. Data from the remaining sparring sessions were kept as an external validation set. The performance of the proprietary algorithm used by the sensor was also compared to the trained algorithm performance. The trained decision tree was able to correctly classify 95% of events for internal cross-validation and 88% of events for the external validation set. Comparatively, the proprietary algorithm was only able to correctly classify 61% of the events. In general, the trained algorithm was better able to predict when a signal was good or bad compared to the proprietary algorithm. The present study shows it is possible to train a decision tree algorithm using environmental sensor data collected in the field.","PeriodicalId":332737,"journal":{"name":"Volume 3: Biomedical and Biotechnology Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134211733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Cryogenic Material Properties of Polycaprolactone 聚己内酯的低温材料性能

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2019-11-11 DOI: 10.1115/imece2019-10180

A. Sagar, Christopher R. Nehme, A. Saigal, Thomas P. James

{"title":"Cryogenic Material Properties of Polycaprolactone","authors":"A. Sagar, Christopher R. Nehme, A. Saigal, Thomas P. James","doi":"10.1115/imece2019-10180","DOIUrl":"https://doi.org/10.1115/imece2019-10180","url":null,"abstract":"\u0000 In pursuit of research to create a synthetic tissue scaffold by a micropunching process, material properties of Polycaprolactone (PCL) in liquid nitrogen were determined experimentally. Specimens were prepared using injection molding and tested under compression to determine the stress-strain relationship of PCL below its glass transition temperature. Cryogenic conditions were maintained by keeping the PCL specimens submerged in liquid nitrogen throughout the loading cycle. Specimens of two different aspect ratios were used for testing. Yield Strength, Strength Coefficient, and Strain Hardening Exponent were determined for different specimen aspect ratios and extrapolated for the case with zero diameter to length ratio. Material properties were also determined at room temperature and compared against results available in the literature. Results demonstrate that PCL behaves in a brittle manner at cryogenic temperatures with more than ten times increase in Young’s modulus from its value at room temperature. The results were used to predict punching forces for the design of microscale hole punching dies and for validation of a microscale hole punching model that was created with a commercially available finite element software package, DEFORM 3D. The three parameters Yield Strength, Strength Coefficient, and Strain Hardening Exponent used in Ludwik’s equation to model flow stress of PCL in DEFORM 3D were determined to be 94.8 MPa, 210 MPa, and 0.54, respectively.","PeriodicalId":332737,"journal":{"name":"Volume 3: Biomedical and Biotechnology Engineering","volume":"39 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113989501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Bone-Integrated Optical Microlasers for In-Vivo Diagnostic Biomechanical Performances 骨集成光学微激光器用于体内诊断生物力学性能

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2019-11-11 DOI: 10.1115/imece2019-11406

O. Cavazos, M. Manzo, E. Ramírez-Cedillo, H. Siller

{"title":"Bone-Integrated Optical Microlasers for In-Vivo Diagnostic Biomechanical Performances","authors":"O. Cavazos, M. Manzo, E. Ramírez-Cedillo, H. Siller","doi":"10.1115/imece2019-11406","DOIUrl":"https://doi.org/10.1115/imece2019-11406","url":null,"abstract":"\u0000 Bones experience mechanical loads on a daily basis. It is difficult to obtain biomechanical performances in-vivo measurements. When implants are integrated with bones after surgery, especially in aged individuals, their osseointegration can compromise the structural integrity of bones; for this reason, it is important to monitor the evolution of the mechanical properties of bones with some in-vivo diagnostic technique. In this study, we propose to integrate optical microsensing devices into bones. To simulate the working principle, a sensor is integrated with a 3-D printed bone. The sensing element is a dye-doped optical microlaser based on the morphology dependent resonance (MDR) shifts also called the whispering gallery mode phenomenon (WGM). When the microlaser is excited by a light source, the fluorescence from the dye couples with the optical resonances. These optical resonances are very sensitive to any perturbation of the microlasers’s morphology. Therefore, the local strain variation of the bone can be related to the shift of the optical resonances. This in-vivo technique monitors the biomechanical performance of bones with implants and prosthetics.","PeriodicalId":332737,"journal":{"name":"Volume 3: Biomedical and Biotechnology Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133093169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Biomaterial Models Adjustment and Comparison for Ultra-High Molecular Weight Polyethylene in Finite Element Models 生物材料模型的调整与超高分子量聚乙烯在有限元模型中的比较

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2018-11-09 DOI: 10.1115/IMECE2018-87719

Humberto Corro-Hernández, A. Vidal-Lesso, E. Ledesma, A. Balvantín-García

引用次数: 0

Influence of Non-Newtonian Rheology on Mass Transfer From a Biofluid in Separated and Reattached Flows 非牛顿流变性对分离和再附着流动中生物流体传质的影响

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2018-11-09 DOI: 10.1115/IMECE2018-86809

K. Hammad

引用次数: 0

Investigating the Progression of Alzheimer’s Disease Using Digital Volume Correlation Algorithm and Strain As a Metric 使用数字体积相关算法和应变作为度量来研究阿尔茨海默病的进展

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2018-11-09 DOI: 10.1115/IMECE2018-87563

Annastacia K McCarty, S. Bentil

{"title":"Investigating the Progression of Alzheimer’s Disease Using Digital Volume Correlation Algorithm and Strain As a Metric","authors":"Annastacia K McCarty, S. Bentil","doi":"10.1115/IMECE2018-87563","DOIUrl":"https://doi.org/10.1115/IMECE2018-87563","url":null,"abstract":"In the United States, Alzheimer’s disease (AD) affects one in ten people ages 65 and older. In most patients, the first indication of AD is the inability to remember new information, and symptoms grow to include behavior changes and increasing confusion and suspicions surrounding loved ones and daily events. As the disease progresses, the cortex and hippocampus regions of the brain decrease in size, allowing the fluid-filled ventricles within the brain to increase. New and innovative therapies to delay the onset of the disease and progression of the symptoms are being discovered. For example, the antibody solanezumab is undergoing clinical trials to determine its ability to reduce the levels of beta-amyloid in the brain, a known risk factor of AD. Consequently, the ability to identify patients who could benefit from the therapies will be invaluable. The purpose of this study is to determine if the digital volume correlation (DVC) algorithm can detect and track the onset and progression of AD using magnetic resonance imaging (MRI) scans of the head. DVC measures the deformation and strain of the volumetric MRI dataset by tracking the changes in its grey value pattern. A collection of MRI datasets of a patient’s head, which include scans from a baseline visit and visits at 6 months, 12 months, and every 12 months thereafter, is used in our analysis. A strain is applied to each set of MRI scans prior to implementation of the digital volume correlation algorithm. The DVC algorithm is then applied to the dataset and the resulting error between the expected and calculated strain is computed. A decrease in the contrast of the MRI dataset will correlate to additional error by the algorithm. As a result, an increase in the calculated strain error is anticipated to correlate with an increase in the ventricles in the brain, or progression of the disease, over the time period of interest.","PeriodicalId":332737,"journal":{"name":"Volume 3: Biomedical and Biotechnology Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129025190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pelvic Injury Survival Analysis for a Finite Element Human Body Model Using Multiple Data Sets 基于多数据集的有限元人体模型骨盆损伤生存分析

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2018-11-09 DOI: 10.1115/IMECE2018-88447

C. Weaver, A. Miller, Joel Stitzel

{"title":"Pelvic Injury Survival Analysis for a Finite Element Human Body Model Using Multiple Data Sets","authors":"C. Weaver, A. Miller, Joel Stitzel","doi":"10.1115/IMECE2018-88447","DOIUrl":"https://doi.org/10.1115/IMECE2018-88447","url":null,"abstract":"Finite element (FE) computational human body models (HBMs) have gained popularity over the past several decades as human surrogates for use in blunt injury research. FE HBMs are critical for the analysis of local injury mechanisms. These metrics are challenging to measure experimentally and demonstrate an important advantage of HBMs. The objective of this study is to evaluate the injury risk predictive power of localized metrics to predict the risk of pelvic fracture in a FE HBM.\u0000 The Global Human Body Models Consortium (GHBMC) 50th percentile detailed male model (v4.3) was used for this study. Cross-sectional and cortical bone surface instrumentation was implemented in the GHBMC pelvis. Lateral impact FE simulations were performed using input data from tests performed on post mortem human subjects (PMHS). Predictive power of the FE force and strain outputs on localized fracture risk was evaluated using the receiver operator characteristic (ROC) curve analysis.\u0000 The ROC curve analysis showed moderate predictive power for the superior pubic ramus and sacrum. Additionally, cross-sectional force was compared to a range of percentile outputs of maximum principal, minimum principal, and effective cortical element strains. From this analysis it was determined that cross-sectional force was the best predictor of localized pelvic fracture.","PeriodicalId":332737,"journal":{"name":"Volume 3: Biomedical and Biotechnology Engineering","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115976142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biomedical Devices Using Shape Memory Polymer Foams for Treatment of Intracranial Aneurysms 使用形状记忆聚合物泡沫的生物医学设备治疗颅内动脉瘤

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2018-11-09 DOI: 10.1115/IMECE2018-86120

Jingyu Wang, Jishan Luo, Robert Kunkel, Yingtao Liu, B. Bohnstedt, Chung-Hao Lee

引用次数: 2

A Modular Test Platform for Micromechanical Tensile Testing of Soft Biomaterials 软质生物材料微力学拉伸测试的模块化测试平台

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2018-11-09 DOI: 10.1115/IMECE2018-87259

Wilson Eng, Max Kim, A. Ramasubramanian, Sang Joon John Lee

{"title":"A Modular Test Platform for Micromechanical Tensile Testing of Soft Biomaterials","authors":"Wilson Eng, Max Kim, A. Ramasubramanian, Sang Joon John Lee","doi":"10.1115/IMECE2018-87259","DOIUrl":"https://doi.org/10.1115/IMECE2018-87259","url":null,"abstract":"Mechanical properties of biomaterials are difficult to characterize experimentally because many relevant biomaterials such as hydrogels are very pliable and viscoelastic. Furthermore, test specimens such as blood clots retrieved from patients tend to be small in size, requiring fine positioning and sensitive force measurement. Mechanobiological studies require fast data recording, preferably under simultaneous microscope imaging, in order to monitor events such as structural remodeling or localized rupture while strain is being applied. A low-profile tensile tester that applies prescribed displacement up to several millimeters and measures forces with resolution on the order of micronewtons has been designed and tested, using alginate as a representative soft biomaterial. 1.5% alginate (cross-linked with 0.1 M and 0.2 M calcium chloride) has been chosen as a reference material because of its extensive use in tissue engineering and other biomedical applications. Prescribed displacement control with rates between 20 μm/s and 60 μm/s were applied using a commercial low-noise nanopositioner. Force data were recorded using data acquisition and signal conditioning hardware with sampling rates as high as 1 kHz. Elongation up to approximately 10 mm and force in the range of 250 mN were measured. The data were used to extract elastic and viscoelastic parameters for alginate specimens. Another biomaterial, 2% agarose, was also tested to show versatility of the apparatus for slightly stiffer materials. The apparatus is modular such that different load cells ranging in capacity from hundreds of millinewtons to tens of newtons can be used. The apparatus furthermore is compatible with real-time microscope imaging, particle tracing, and programmable positioning sequences.","PeriodicalId":332737,"journal":{"name":"Volume 3: Biomedical and Biotechnology Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134364082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Mechanical Properties of the Human Elbow Bones Measured by Nanoindentation and Microindentation 用纳米压痕和微压痕测量人体肘骨的力学性能

Volume 3: Biomedical and Biotechnology Engineering Pub Date : 2018-11-09 DOI: 10.1115/IMECE2018-87406

Dilpreet K Singh, P. M. Pandey, D. Kalyanasundaram

{"title":"Mechanical Properties of the Human Elbow Bones Measured by Nanoindentation and Microindentation","authors":"Dilpreet K Singh, P. M. Pandey, D. Kalyanasundaram","doi":"10.1115/IMECE2018-87406","DOIUrl":"https://doi.org/10.1115/IMECE2018-87406","url":null,"abstract":"In this article, the nano and microhardness and the elastic modulus of the human elbow bones (humerus, ulna and radius) were studied. The nano properties were studied using load controlled technique with a load of 20 mN, while the micro properties were studied under 1 N load. A total of nine bone samples from three cadavers of ages between 45 and 55 years were tested. The measurements were carried out on both osteonal and interstitial bone in the longitudinal direction. The nanoindentation results indicated higher values for interstitial bone (hardness: 0.74 ± 0.09 GPa, elastic modulus: 19.05 ± 1.92 GPa) than for osteonal bone (hardness: 0.53 ± 0.05 GPa, elastic modulus: 16.66 ± 1.55 GPa). Consistent results were obtained at a depth of penetration between 1.1 μm to 1.5 μm in nanoindentation. In the case of microindentation, the microhardness and elastic modulus of interstitial bone was found to be 0.65 ± 0.07 GPa and 20.60 ± 2.27 GPa. Whereas for osteonal bone it was observed to be 0.60 ± 0.08 GPa and 14.56 ± 1.42 GPa respectively. The depth of penetration varies between the 8 μm to 11 μm for microindentation studies. In both measurement scales, a noticeable difference was observed between the osteonal and interstitial bone properties. As bone is a hierarchical structure, identifying the mechanical properties at the lamellar level helps in understanding the local mechanical environment of basic elements of the bones and predicting the behavior of the bone due to physiological loading.","PeriodicalId":332737,"journal":{"name":"Volume 3: Biomedical and Biotechnology Engineering","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131500101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1