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https://www.readbyqxmd.com/read/28227887/hip-joint-geometry-effects-on-cartilage-contact-stresses-during-a-gait-cycle
#1
Hui-Hui Wu, Dong Wang, An-Bang Ma, Dong-Yun Gu, Hui-Hui Wu, Dong Wang, An-Bang Ma, Dong-Yun Gu, An-Bang Ma, Dong-Yun Gu, Hui-Hui Wu, Dong Wang
The cartilage surface geometry of natural human hip joint is commonly regarded as sphere. It has been widely applied in computational simulation and hip joint prosthesis design. Some new geometry models have been developed and the sphere assumption has been questioned recently. The objective of this study was to analyze joint geometry effects on cartilage contact stress distribution and investigate contact patterns during a whole gait cycle. Hip surface was reconstructed from CT data of a healthy volunteer...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227751/a-time-domain-frequency-selective-multivariate-granger-causality-approach
#2
Lutz Leistritz, Herbert Witte, Lutz Leistritz, Herbert Witte, Lutz Leistritz, Herbert Witte
The investigation of effective connectivity is one of the major topics in computational neuroscience to understand the interaction between spatially distributed neuronal units of the brain. Thus, a wide variety of methods has been developed during the last decades to investigate functional and effective connectivity in multivariate systems. Their spectrum ranges from model-based to model-free approaches with a clear separation into time and frequency range methods. We present in this simulation study a novel time domain approach based on Granger's principle of predictability, which allows frequency-selective considerations of directed interactions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227594/fall-risk-factors-analysis-based-on-sample-entropy-of-plantar-kinematic-signal-during-stance-phase
#3
Shengyun Liang, Huiyu Jia, Zilong Li, Huiqi Li, Xing Gao, Zuchang Ma, Yingnan Ma, Guoru Zhao, Shengyun Liang, Huiyu Jia, Zilong Li, Huiqi Li, Xing Gao, Zuchang Ma, Yingnan Ma, Guoru Zhao, Shengyun Liang, Huiqi Li, Huiyu Jia, Xing Gao, Zuchang Ma, Guoru Zhao, Yingnan Ma, Zilong Li
Falls are a multi-causal phenomenon with a complex interaction. The aim of our research is to study the effect of multiple variables for potential risk of falls and construct an elderly fall risk assessment model based on demographics data and gait characteristics. A total of 101 subjects, whom belong to Malianwa Street, aged above 50 years old and participated in questionnaire survey. Participants were classified into three groups (high, medium and low risk group) according to the score of elderly fall risk assessment scale...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227445/quantitative-estimation-of-electro-osmosis-force-on-charged-particles-inside-a-borosilicate-resistive-pulse-sensor
#4
Mostafa Ghobadi, Yuqian Zhang, Ankit Rana, Ehsan T Esfahani, Leyla Esfandiari, Mostafa Ghobadi, Yuqian Zhang, Ankit Rana, Ehsan T Esfahani, Leyla Esfandiari, Ehsan T Esfahani, Yuqian Zhang, Ankit Rana, Mostafa Ghobadi
Nano and micron-scale pore sensors have been widely used for biomolecular sensing application due to its sensitive, label-free and potentially cost-effective criteria. Electrophoretic and electroosmosis are major forces which play significant roles on the sensor's performance. In this work, we have developed a mathematical model based on experimental and simulation results of negatively charged particles passing through a 2μm diameter solid-state borosilicate pore under a constant applied electric field. The mathematical model has estimated the ratio of electroosmosis force to electrophoretic force on particles to be 77...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227405/template-based-rodent-brain-extraction-and-atlas-mapping
#5
Weimin Huang, Jiaqi Zhang, Zhiping Lin, Su Huang, Yuping Duan, Zhongkang Lu, Weimin Huang, Jiaqi Zhang, Zhiping Lin, Su Huang, Yuping Duan, Zhongkang Lu, Jiaqi Zhang, Weimin Huang, Yuping Duan, Zhongkang Lu, Zhiping Lin, Su Huang
Accurate rodent brain extraction is the basic step for many translational studies using MR imaging. This paper presents a template based approach with multi-expert refinement to automatic rodent brain extraction. We first build the brain appearance model based on the learning exemplars. Together with the template matching, we encode the rodent brain position into the search space to reliably locate the rodent brain and estimate the rough segmentation. With the initial mask, a level-set segmentation and a mask-based template learning are implemented further to the brain region...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227357/experimental-evaluation-of-the-accuracy-at-the-c-arm-pose-estimation-with-x-ray-images
#6
Sabine Thurauf, Florian Vogt, Oliver Hornung, Mario Korner, M Ali Nasseri, Alois Knoll, Sabine Thurauf, Florian Vogt, Oliver Hornung, Mario Korner, M Ali Nasseri, Alois Knoll, Sabine Thurauf, Alois Knoll, Mario Korner, Florian Vogt, Oliver Hornung, M Ali Nasseri
C-arm X-ray systems need a high spatial accuracy for applications like cone beam computed tomography and 2D/3D overlay. One way to achieve the needed precision is a model-based calibration of the C-arm system. For such a calibration a kinematic and dynamic model of the system is constructed whose parameters are computed by pose measurements of the C-arm. Instead of common measurement systems used for a model-based calibration for robots like laser trackers, we use X-ray images of a calibration phantom to measure the C-arm pose...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227312/improving-quality-and-intelligibility-of-speech-using-single-microphone-for-the-broadband-fmri-noise-at-low-snr
#7
Chetan Vahanesa, Chandan K A Reddy, Issa M S Panahi, Chetan Vahanesa, Chandan K A Reddy, Issa M S Panahi, Chetan Vahanesa, Issa M S Panahi, Chandan K A Reddy
Functional Magnetic Resonance Imaging (fMRI) is used in many diagnostic procedures for neurological related disorders. Strong broadband acoustic noise generated during fMRI scan interferes with the speech communication between the physician and the patient. In this paper, we propose a single microphone Speech Enhancement (SE) technique which is based on the supervised machine learning technique and a statistical model based SE technique. The proposed algorithm is robust and computationally efficient and has capability to run in real-time...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227229/ensemble-statistical-and-subspace-clustering-model-for-analysis-of-autism-spectrum-disorder-phenotypes
#8
Khalid Al-Jabery, Tayo Obafemi-Ajayi, Gayla R Olbricht, T Nicole Takahashi, Stephen Kanne, Donald Wunsch, Khalid Al-Jabery, Tayo Obafemi-Ajayi, Gayla R Olbricht, T Nicole Takahashi, Stephen Kanne, Donald Wunsch, Donald Wunsch, Tayo Obafemi-Ajayi, Khalid Al-Jabery, Stephen Kanne, Gayla R Olbricht, T Nicole Takahashi
Heterogeneity in Autism Spectrum Disorder (ASD) is complex including variability in behavioral phenotype as well as clinical, physiologic, and pathologic parameters. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) now diagnoses ASD using a 2-dimensional model based social communication deficits and fixated interests and repetitive behaviors. Sorting out heterogeneity is crucial for study of etiology, diagnosis, treatment and prognosis. In this paper, we present an ensemble model for analyzing ASD phenotypes using several machine learning techniques and a k-dimensional subspace clustering algorithm...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227214/activity-recognition-in-patients-with-lower-limb-impairments-do-we-need-training-data-from-each-patient
#9
Luca Lonini, Aakash Gupta, Konrad Kording, Arun Jayaraman, Luca Lonini, Aakash Gupta, Konrad Kording, Arun Jayaraman, Luca Lonini, Konrad Kording, Arun Jayaraman, Aakash Gupta
Machine learning allows detecting specific physical activities using data from wearable sensors. Such a quantification of patient mobility over time promises to accurately inform clinical decisions for physical rehabilitation. There are two strategies of setting up the machine learning problem: detect one patient's activities using data from the same patient (personal model) or detect their activities using data from other patients (global model), and we currently do not know if personal models are necessary...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227105/quantifying-connectivity-in-a-physiology-based-model-using-adaptive-dynamic-causal-modelling
#10
W Xiang, C Yang, A Karfoul, R Le Bouquin Jeannes, W Xiang, C Yang, A Karfoul, R Le Bouquin Jeannes, A Karfoul, W Xiang, C Yang
This paper proposes an Adaptive Dynamic Causal Modelling based approach to detect and quantify effective connectivity in human brain structures injured by epileptic activities. The identification of the parameters in the physiology based model subtended the Electroencephalographic observations is performed by improving the optimization step in the Expectation Maximization algorithm. Considering unidirectional flow propagation, we show the efficiency of our proposed approach compared to the conventional technique...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227073/a-model-based-method-to-measure-baroreflex-sensitivity
#11
Yu Meng, Zhipei Huang, Jiangkang Wu, Xinxia Cai, Yu Meng, Zhipei Huang, Jiangkang Wu, Xinxia Cai, Yu Meng, Jiangkang Wu, Xinxia Cai, Zhipei Huang
This paper proposes a model-based method to quantitatively measure baroreflex sensitivity in autonomic nervous regulation of cardiovascular system. The method measures the continuous blood pressure and heart rate in orthostatic scenario, models dynamics of the baroreflex firing rate, solves parameters by optimization of measured blood pressure and heart rate variations. With this model, we can get the baroreflx sensitivity (BRS) inner indicators to evaluate the status of the autonomic nervous regulation system...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227070/heart-rate-regulation-during-cycle-ergometer-exercise-using-damped-parameter-estimation-method
#12
Ahmadreza Argha, Lin Ye, Steven W Su, Hung Nguyen, Branko G Celler, Ahmadreza Argha, Lin Ye, Steven W Su, Hung Nguyen, Branko G Celler, Steven W Su, Hung Nguyen, Ahmadreza Argha, Lin Ye, Branko G Celler
This paper is devoted to the problem of heart rate regulation using a model-based control strategy and a realtime damped parameter estimation scheme. The controller is a time-varying integral sliding mode controller. A recursive damped parameter estimation method is also developed, by incorporation of a weighting upon the one-step parameter variation, which in contrast to the conventional parameter estimation schemes (e.g. recursive least squares (RLS) method) can avoid the occurrence of the so-called blowup phenomena...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226978/improving-clinical-models-based-on-knowledge-extracted-from-current-datasets-a-new-approach
#13
D Mendes, S Paredes, T Rocha, P Carvalho, J Henriques, J Morais, D Mendes, S Paredes, T Rocha, P Carvalho, J Henriques, J Morais, D Mendes, T Rocha, P Carvalho, J Morais, S Paredes, J Henriques
The Cardiovascular Diseases (CVD) are the leading cause of death in the world, being prevention recognized to be a key intervention able to contradict this reality. In this context, although there are several models and scores currently used in clinical practice to assess the risk of a new cardiovascular event, they present some limitations. The goal of this paper is to improve the CVD risk prediction taking into account the current models as well as information extracted from real and recent datasets. This approach is based on a decision tree scheme in order to assure the clinical interpretability of the model...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226939/model-based-assistance-as-needed-for-robotic-movement-therapy-after-stroke
#14
Hossein Taheri, David J Reinkensmeyer, Eric T Wolbrecht, Hossein Taheri, David J Reinkensmeyer, Eric T Wolbrecht, Eric T Wolbrecht, David J Reinkensmeyer, Hosoein Taheri
This paper extends an adaptive control approach for robotic movement therapy that learns deficiencies in a patient's neuromuscular output and assists accordingly. In this method, adaptation is based on trajectory tracking error and a model of unimpaired motor control forces. The controller presented here adaptively learns and fills the gaps in the patient's ability to generate inertial forces, instead of just static forces, as has been proposed before. To test this method, a two dimensional model of an impaired human arm was used to simulate reaching movements in the horizontal plane...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226884/analysis-of-comfort-and-ergonomics-for-clinical-work-environments
#15
Ali Shafti, Beatriz Urbistondo Lazpita, Oussama Elhage, Helge A Wurdemann, Kaspar Althoefer, Ali Shafti, Beatriz Urbistondo Lazpita, Oussama Elhage, Helge A Wurdemann, Kaspar Althoefer, Helge A Wurdemann, Beatriz Urbistondo Lazpita, Kaspar Althoefer, Ali Shafti, Oussama Elhage
Work related musculoskeletal disorders (WMSD) are a serious risk to workers' health in any work environment, and especially in clinical work places. These disorders are typically the result of prolonged exposure to non-ergonomic postures and the resulting discomfort in the workplace. Thus a continuous assessment of comfort and ergonomics is necessary. There are different techniques available to make such assessments, such as self-reports on perceived discomfort and observational scoring models based on the posture's relevant joint angles...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226770/a-multiscale-model-based-analysis-of-the-multi-tissue-interplay-underlying-blood-glucose-regulation-in-type-i-diabetes
#16
Federico Wadehn, Stephan Schaller, Thomas Eissing, Markus Krauss, Lars Kupfer, Federico Wadehn, Stephan Schaller, Thomas Eissing, Markus Krauss, Lars Kupfer, Federico Wadehn, Markus Krauss, Lars Kupfer, Stephan Schaller, Thomas Eissing
A multiscale model for blood glucose regulation in diabetes type I patients is constructed by integrating detailed metabolic network models for fat, liver and muscle cells into a whole body physiologically-based pharmacokinetic/pharmacodynamic (pBPK/PD) model. The blood glucose regulation PBPK/PD model simulates the distribution and metabolization of glucose, insulin and glucagon on an organ and whole body level. The genome-scale metabolic networks in contrast describe intracellular reactions. The developed multiscale model is fitted to insulin, glucagon and glucose measurements of a 48h clinical trial featuring 6 subjects and is subsequently used to simulate (in silico) the influence of geneknockouts and drug-induced enzyme inhibitions on whole body blood glucose levels...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226593/dynamic-cerebral-autoregulation-in-young-athletes-following-concussion
#17
Kyriaki Kostoglou, Alexander D Wright, Jonathan D Smirl, Kelsey Bryk, Paul van Donkelaar, Georgios D Mitsis, Kyriaki Kostoglou, Alexander D Wright, Jonathan D Smirl, Kelsey Bryk, Paul van Donkelaar, Georgios D Mitsis, Paul van Donkelaar, Alexander D Wright, Kyriaki Kostoglou, Jonathan D Smirl, Kelsey Bryk, Georgios D Mitsis
The purpose of this study was to examine cerebral autoregulation (CA) in young athletes experiencing concussion. The subjects were monitored and repeatedly tested 72 hours, 2 weeks and 1 month post-injury. Mean arterial blood pressure (MABP), end-tidal partial pressure of carbon dioxide (PETCO2) and cerebral blood flow velocity (CBFV) in the middle and posterior cerebral arteries were monitored during mental activation paradigms. In order to characterize CA we employed autoregressive models with exogenous inputs (ARX) and impulse response models based on the Laguerre expansion technique (LET)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226577/semi-advised-learning-model-for-skin-cancer-diagnosis-based-on-histopathalogical-images
#18
Ammara Masood, Adel Al-Jumaily, Ammara Masood, Adel Al-Jumaily, Ammara Masood, Adel Al-Jumaily
Computer aided classification of skin cancer images is an active area of research and different classification methods has been proposed so far. However, the supervised classification models based on insufficient labeled training data can badly influence the diagnosis process. To deal with the problem of limited labeled data availability this paper presents a semi advised learning model for automated recognition of skin cancer using histopathalogical images. Deep belief architecture is constructed using unlabeled data by making efficient use of limited labeled data for fine tuning done the classification model...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226483/experimental-evaluation-of-regression-model-based-walking-speed-estimation-using-lower-body-mounted-imu
#19
Shaghayegh Zihajehzadeh, Edward J Park, Shaghayegh Zihajehzadeh, Edward J Park, Shaghayegh Zihajehzadeh, Edward J Park
This study provides a concurrent comparison of regression model-based walking speed estimation accuracy using lower body mounted inertial sensors. The comparison is based on different sets of variables, features, mounting locations and regression methods. An experimental evaluation was performed on 15 healthy subjects during free walking trials. Our results show better accuracy of Gaussian process regression compared to least square regression using Lasso. Among the variables, external acceleration tends to provide improved accuracy...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226470/behavioral-informatics-dynamical-models-for-measuring-and-assessing-behaviors-for-precision-interventions
#20
Misha Pavel, Holly Jimison, Bonnie Spring, Misha Pavel, Holly Jimison, Bonnie Spring, Bonnie Spring, Holly Jimison, Misha Pavel
Poor health-related behaviors represent a major challenge to healthcare due to their significant impact on chronic and acute diseases and their effect on the quality of life. Recent advances in technology have enabled an unprecedented opportunity to assess objectively, unobtrusively and continuously human behavior and have opened the possibility of optimizing individual-tailored, precision interventions within the framework of behavioral informatics. A key prerequisite for this optimization is the ability to assess and predict effects of interventions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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