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IEEE Journal of Biomedical and Health Informatics

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https://www.readbyqxmd.com/read/29300701/speech2health-a-mobile-framework-for-monitoring-dietary-composition-from-spoken-data
#1
Niloofar Hezarjaribi, Sepideh Mazrouee, Hassan Ghasemzadeh
Diet and physical activity are known as important lifestyle factors in self-management and prevention of many chronic diseases. Mobile sensors such as accelerometers have been used to measure physical activity or detect eating time. In many intervention studies, however, stringent monitoring of overall dietary composition and energy intake is needed. Currently, such a monitoring relies on self-reported data by either entering text or taking an image that represents food intake. These approaches suffer from limitations such as low adherence in technology adoption and time sensitivity to the diet intake context...
January 2018: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/29300700/understanding-the-physiological-significance-of-four-inertial-gait-features-in-multiple-sclerosis
#2
Sriram Raju Dandu, Matthew M Engelhard, Asma Qureshi, Jiaqi Gong, John C Lach, Maite Brandt-Pearce, Myla D Goldman
Gait impairment in multiple sclerosis (MS) can result from muscle weakness, physical fatigue, lack of coordination, and other symptoms. Walking speed, as measured by a number of clinician-administered walking tests, is the primary measure of gait impairment used by clinical researchers, but inertial gait features from body-worn sensors have been proven to add clinical value. This paper seeks to understand and differentiate the physiological significance of four such features with proven value in MS to facilitate adoption by clinical researchers and incorporation in gait monitoring and analysis systems...
January 2018: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/29300699/a-self-calibrated-tissue-viability-sensor-for-free-flap-monitoring
#3
Melissa Berthelot, Guang-Zhong Yang, Benny Lo
In fasciocutaneous free flap surgery, close postoperative monitoring is crucial for detecting flap failure, as around 10% of cases require additional surgery due to compromised anastomosis. Different biochemical and biophysical techniques have been developed for continuous flap monitoring, however, they all have shortcoming in terms of reliability, elevated cost, potential risks to the patient, and inability to adapt to the patient's phenotype. A wearable wireless device based on near infrared spectroscopy has been developed for continuous blood flow and perfusion monitoring by quantifying tissue oxygen saturation ()...
January 2018: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/29136608/variation-of-the-korotkoff-stethoscope-sounds-during-blood-pressure-measurement-analysis-using-a-convolutional-neural-network
#4
Fan Pan, Peiyu He, Chengyu Liu, Taiyong Li, Alan Murray, Dingchang Zheng
Korotkoff sounds are known to change their characteristics during blood pressure (BP) measurement, resulting in some uncertainties for systolic and diastolic pressure (SBP and DBP) determinations. The aim of this study was to assess the variation of Korotkoff sounds during BP measurement by examining all stethoscope sounds associated with each heartbeat from above systole to below diastole during linear cuff deflation. Three repeat BP measurements were taken from 140 healthy subjects (age 21 to 73 years; 62 female and 78 male) by a trained observer, giving 420 measurements...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28796626/matrix-and-tensor-completion-on-a-human-activity-recognition-framework
#5
Sofia Savvaki, Grigorios Tsagkatakis, Athanasia Panousopoulou, Panagiotis Tsakalides
Sensor-based activity recognition is encountered in innumerable applications of the arena of pervasive healthcare and plays a crucial role in biomedical research. Nonetheless, the frequent situation of unobserved measurements impairs the ability of machine learning algorithms to efficiently extract context from raw streams of data. In this paper, we study the problem of accurate estimation of missing multimodal inertial data and we propose a classification framework that considers the reconstruction of subsampled data during the test phase...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28796625/collaborative-ehealth-meets-security-privacy-enhancing-patient-profile-management
#6
Rosa Sanchez-Guerrero, Florina Almenarez Mendoza, Daniel Diaz-Sanchez, Patricia Arias Cabarcos, Andres Marin Lopez
Collaborative healthcare environments offer potential benefits, including enhancing the healthcare quality delivered to patients and reducing costs. As a direct consequence, sharing of electronic health records (EHRs) among healthcare providers has experienced a noteworthy growth in the last years, since it enables physicians to remotely monitor patients' health and enables individuals to manage their own health data more easily. However, these scenarios face significant challenges regarding security and privacy of the extremely sensitive information contained in EHRs...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28541230/an-adaptive-particle-weighting-strategy-for-ecg-denoising-using-marginalized-particle-extended-kalman-filter-an-evaluation-in-arrhythmia-contexts
#7
Hamed Danandeh Hesar, Maryam Mohebbi
Model-based Bayesian frameworks have a common problem in processing electrocardiogram (ECG) signals with sudden morphological changes. This situation often happens in the case of arrhythmias where ECGs do not obey the predefined state models. To solve this problem, in this paper, a model-based Bayesian denoising framework is proposed using marginalized particle-extended Kalman filter (MP-EKF), variational mode decomposition, and a novel fuzzy-based adaptive particle weighting strategy. This strategy helps MP-EKF to perform well even when the morphology of signal does not comply with the predefined dynamic model...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28541229/deeppap-deep-convolutional-networks-for-cervical-cell-classification
#8
Ling Zhang, Le Lu, Isabella Nogues, Ronald M Summers, Shaoxiong Liu, Jianhua Yao
Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a highly effective cell imaging based cancer detection tool, where cells are partitioned into "abnormal" and "normal" categories. However, the success of most traditional classification methods relies on the presence of accurate cell segmentations. Despite sixty years of research in this field, accurate segmentation remains a challenge in the presence of cell clusters and pathologies. Moreover, previous classification methods are only built upon the extraction of hand-crafted features, such as morphology and texture...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28534798/alzheimer-s-disease-diagnosis-using-landmark-based-features-from-longitudinal-structural-mr-images
#9
Jun Zhang, Mingxia Liu, Le An, Yaozong Gao, Dinggang Shen
Structural magnetic resonance imaging (MRI) has been proven to be an effective tool for Alzheimer's disease (AD) diagnosis. While conventional MRI-based AD diagnosis typically uses images acquired at a single time point, a longitudinal study is more sensitive in detecting early pathological changes of AD, making it more favorable for accurate diagnosis. In general, there are two challenges faced in MRI-based diagnosis. First, extracting features from structural MR images requires time-consuming nonlinear registration and tissue segmentation, whereas the longitudinal study with involvement of more scans further exacerbates the computational costs...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28534795/choroid-neovascularization-growth-prediction-with-treatment-based-on-reaction-diffusion-model-in-3-d-oct-images
#10
Shuxia Zhu, Fei Shi, Dehui Xiang, Weifang Zhu, Haoyu Chen, Xinjian Chen
Choroid neovascularization (CNV) is caused by new blood vessels growing in the choroid and penetrating the bruch membrane. It is the major cause of vision disability in many retinal diseases. Though anti-vascular endothelial growth factor injection has proved to be effective for treating CNV, treatment planning is essential to ensure the efficacy while reducing the risk. For this purpose, we propose a CNV growth model based on longitudinal optical coherence tomography (OCT) images. The reaction-diffusion model is applied to simulate the growth and shrinkage of CNV volumes, and is solved by using the finite-element method...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28463207/a-novel-continuous-blood-pressure-estimation-approach-based-on-data-mining-techniques
#11
Fen Miao, Nan Fu, Yuan-Ting Zhang, Xiao-Rong Ding, Xi Hong, Qingyun He, Ye Li
Continuous blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for unobtrusive BP measurement. However, the accuracy of this approach must be improved for it to be viable for a wide range of applications. This study proposes a novel continuous BP estimation approach that combines data mining techniques with a traditional mechanism-driven model. First, 14 features derived from simultaneous electrocardiogram and photoplethysmogram signals were extracted for beat-to-beat BP estimation...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28422699/hemorrhage-prediction-models-in-surgical-intensive-care-bedside-monitoring-data-adds-information-to-lab-values
#12
Marco De Pasquale, Travis J Moss, Sergio Cerutti, James Forrest Calland, Douglas E Lake, J Randall Moorman, Manuela Ferrario
Hemorrhage is a frequent complication in surgery patients; its identification and management have received increasing attention as a target for quality improvement in patient care in the Intensive Care Unit (ICU). The purposes of this work were 1) to find an early detection model for hemorrhage by exploring the range of data mining methods that are currently available, and 2) to compare prediction models utilizing continuously measured physiological data from bedside monitors to those using commonly obtained laboratory tests...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28410112/epithelium-stroma-classification-via-convolutional-neural-networks-and-unsupervised-domain-adaptation-in-histopathological-images
#13
Yue Huang, Han Zheng, Chi Liu, Xinghao Ding, Gustavo K Rohde
Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neural network when there are changes to the image acquisition procedure. However, it is extremely expensive for pathologists to manually label sufficient volumes of data for each pathology study in a professional manner, which results in limitations in real-world applications...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28362596/a-method-of-signal-scrambling-to-secure-data-storage-for-healthcare-applications
#14
Shu-Di Bao, Meng Chen, Guang-Zhong Yang
A body sensor network that consists of wearable and/or implantable biosensors has been an important front-end for collecting personal health records. It is expected that the full integration of outside-hospital personal health information and hospital electronic health records will further promote preventative health services as well as global health. However, the integration and sharing of health information is bound to bring with it security and privacy issues. With extensive development of healthcare applications, security and privacy issues are becoming increasingly important...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28333647/automatic-choroidal-layer-segmentation-using-markov-random-field-and-level-set-method
#15
Chuang Wang, Ya Xing Wang, Yongmin Li
The choroid is an important vascular layer that supplies oxygen and nourishment to the retina. The changes in thickness of the choroid have been hypothesized to relate to a number of retinal diseases in the pathophysiology. In this paper, an automatic method is proposed for segmenting the choroidal layer from macular images by using the level set framework. The three-dimensional nonlinear anisotropic diffusion filter is used to remove all the optical coherence tomography (OCT) imaging artifacts including the speckle noise and to enhance the contrast...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28320682/deformable-registration-based-super-resolution-for-isotropic-reconstruction-of-4-d-mri-volumes
#16
Geetha Soujanya V N Chilla, Cher Heng Tan, Chueh Loo Poh
Multi-plane super-resolution (SR) has been widely employed for resolution improvement of MR images. However, this has mostly been limited to MRI acquisitions with rigid motion. In cases of non-rigid motion, volumes are usually pre-registered using deformable registration methods before SR reconstruction. The pre-registered images are then used as input for the SR reconstruction. Since deformable registration involves smoothening of the inputs, using pre-registered inputs could lead to loss in information in SR reconstructions...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28287993/prediction-of-adverse-events-in-patients-undergoing-major-cardiovascular-procedures
#17
Bobak J Mortazavi, Nihar Desai, Jing Zhang, Andreas Coppi, Fred Warner, Harlan M Krumholz, Sahand Negahban
Electronic health records (EHR) provide opportunities to leverage vast arrays of data to help prevent adverse events, improve patient outcomes, and reduce hospital costs. This paper develops a postoperative complications prediction system by extracting data from the EHR and creating features. The analytic engine then provides model accuracy, calibration, feature ranking, and personalized feature responses. This allows clinicians to interpret the likelihood of an adverse event occurring, general causes for these events, and the contributing factors for each specific patient...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28278486/differences-between-gait-on-stairs-and-flat-surfaces-in-relation-to-fall-risk-and-future-falls
#18
Kejia Wang, Kim Delbaere, Matthew A D Brodie, Nigel H Lovell, Lauren Kark, Stephen R Lord, Stephen J Redmond
We used body-worn inertial sensors to quantify differences in semi-free-living gait between stairs and on normal flat ground in older adults, and investigated the utility of assessing gait on these terrains for predicting the occurrence of multiple falls. Eighty-two community-dwelling older adults wore two inertial sensors, on the lower back and the right ankle, during several bouts of walking on flat surfaces and up and down stairs, in between rests and activities of daily living. Derived from the vertical acceleration at the lower back, step rate was calculated from the signal's fundamental frequency...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28114042/validation-of-an-adaptive-transfer-function-method-to-estimate-the-aortic-pressure-waveform
#19
Yang Yao, Lisheng Xu, Yingxian Sun, Qiang Fu, Shuran Zhou, Dianning He, Yahui Zhang, Liang Guo, Dingchang Zheng
Aortic pulse wave reflects cardiovascular status, but, unlike the peripheral pulse wave, is difficult to be measured reliably using noninvasive techniques. Thus, the estimation of aortic pulse wave from peripheral ones is of great significance. This study proposed an adaptive transfer function (ATF) method to estimate the aortic pulse wave from the brachial pulse wave. Aortic and brachial pulse waves were derived from 26 patients who underwent cardiac catheterization. Generalized transfer functions (GTF) were derived based on the autoregressive exogenous model...
November 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28113335/segmentation-and-characterization-of-chewing-bouts-by-monitoring-temporalis-muscle-using-smart-glasses-with-piezoelectric-sensor
#20
Muhammad Farooq, Edward Sazonov
Several methods have been proposed for automatic and objective monitoring of food intake, but their performance suffers in the presence of speech and motion artifacts. This paper presents a novel sensor system and algorithms for detection and characterization of chewing bouts from a piezoelectric strain sensor placed on the temporalis muscle. The proposed data acquisition device was incorporated into the temple of eyeglasses. The system was tested by ten participants in two part experiments, one under controlled laboratory conditions and the other in unrestricted free-living...
November 2017: IEEE Journal of Biomedical and Health Informatics
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