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IEEE Journal of Biomedical and Health Informatics

Weichao Xu, Zhaoguo Chen, Yun Zhang, Lianglun Cheng
In this paper, we propose a novel concordance coefficient, called order statistics concordance coefficients (OSCOC), to quantify the association among multi-channel biosignals. To uncover its properties, we compare OSCOC with other three similar indices, i.e., average Pearson's product moment correlation coefficient (APPMCC), Kendall's concordance coefficients (KCC), and average Kendall's tau (AKT), under a multivariate normal model (MNM), linear model (LM) and nonlinear model (NM). To further demonstrate its usefulness, we present an example on atrial arrhythmia analysis based on real world multi-channel cardiac signals...
October 11, 2016: IEEE Journal of Biomedical and Health Informatics
Juan Cheng, Xun Chen, Lingxi Xu, Z Jane Wang
Recent studies have demonstrated that heart rate (HR) could be estimated using video data (e.g., exploring human facial regions of interest (ROIs)) under well controlled conditions. However, in practice, the pulse signals may be contaminated by motions and illumination variations. In this paper, tackling the illumination variation challenge, we propose an illuminationrobust framework using joint blind source separation (JBSS) and ensemble empirical mode decomposition (EEMD) to effectively evaluate HR from webcam videos...
October 6, 2016: IEEE Journal of Biomedical and Health Informatics
Christina Orphanidou, Ivana Drobnjak
Data in recordings obtained from ambulatory patients using wearable sensors are often corrupted by motion artefact and are, in general noisier, than data obtained from non-mobile patients. Identifying and ignoring erroneous measurements from these data is very important, if wearable sensors are to be incorporated into clinical practice. In this paper we propose a novel Signal Quality Index (SQI), intended to assess whether reliable heart rates (HR) can be obtained from a single channel of ECG collected from ambulatory patients, using wearable sensors...
October 5, 2016: IEEE Journal of Biomedical and Health Informatics
Yiru Shen, James Salley, Eric Muth, Adam Hoover
This paper describes a study to test the accuracy of a method that tracks wrist motion during eating to detect and count bites. The purpose was to assess its accuracy across demographic (age, gender, ethnicity) and bite (utensil, container, hand used, food type) variables. Data were collected in a cafeteria under normal eating conditions. A total of 271 participants ate a single meal while wearing a watch-like device to track their wrist motion. Video was simultaneously recorded of each participant and subsequently reviewed to determine the ground truth times of bites...
September 21, 2016: IEEE Journal of Biomedical and Health Informatics
Yibing Ma, Zhiguo Jiang, Haopeng Zhang, Fengying Xie, Yushan Zheng, Huaqiang Shi, Yu Zhao
In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate and fast retrieval method for breast histopathological image. Specifically, the method presents local statistical feature of nuclei for morphology and distribution of nuclei, and employs Gabor feature to describe texture information...
September 20, 2016: IEEE Journal of Biomedical and Health Informatics
Silvia Storti, Ilaria Boscolo Galazzo, Sehresh Khan, Paolo Manganotti, Gloria Menegaz
The application of time-varying measures of causality between source time series can be very informative to elucidate the direction of communication among the regions of an epileptic brain. The aim of the study was to identify the dynamic patterns of epileptic networks in focal epilepsy by applying multivariate adaptive directed transfer function (ADTF) analysis and graph-theory to high-density electroencephalographic (hdEEG) recordings. The cortical network was modeled after source reconstruction and topology modulations were detected during interictal spikes...
September 9, 2016: IEEE Journal of Biomedical and Health Informatics
Ellen McGinnis, Ryan McGinnis, Maria Muzik, Jessica Hruschak, Nestor Lopez-Duran, Noel Perkins, Kate Fitzgerald, Katherine Rosenblum
Temporal phases of threat response including Potential Threat (Anxiety), Acute Threat (Startle, Fear), and Post-threat Response Modulation have been identified as underlying markers of anxiety disorders. Objective measures of response during these phases may help identify children at risk for anxiety, however the complexity of current assessment techniques prevent their adoption in many research and clinical contexts. We propose an alternative technology, an inertial measurement unit (IMU), that enables non-invasive measurement of the movements associated with threat response, and test its ability to detect threat response phases in young children at heightened risk for developing anxiety...
August 25, 2016: IEEE Journal of Biomedical and Health Informatics
Jun Shi, Jinjie Wu, Yan Li, Qi Zhang, Shihui Ying
The computer-aided diagnosis for histopathological images has attracted considerable attention. Principal component analysis network (PCANet) is a novel deep learning algorithm for feature learning with the simple network architecture and parameters. In this work, a color pattern random binary hashing based PCANet (C-RBH-PCANet) algorithm is proposed to learn an effective feature representation from color histopathological images. The color norm pattern and angular pattern are extracted from the principal component images of R, G and B color channels after cascaded PCA networks...
August 25, 2016: IEEE Journal of Biomedical and Health Informatics
Jian Wu, Lu Sun, Roozbeh Jafari
A Sign Language Recognition (SLR) system translates signs performed by deaf individuals into text/speech in real time. Inertial measurement unit (IMU) and surface electromyography (sEMG) are both useful modalities to detect hand/arm gestures. They are able to capture signs and the fusion of these two complementary sensor modalities will enhance system performance. In this paper, a wearable system for recognizing American Sign Language (ASL) in real-time is proposed, fusing information from an inertial sensor and sEMG sensors...
August 25, 2016: IEEE Journal of Biomedical and Health Informatics
Mark Hoogendoorn, Thomas Berger, Ava Schulz, Timo Stolz, Peter Szolovits
Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more treatments involve computer-based exercises or electronic conversations between patient and therapist. In this paper, we study predictive modeling using writings of patients under treatment for a social anxiety disorder...
August 17, 2016: IEEE Journal of Biomedical and Health Informatics
Claudio Stamile, Gabriel Kocevar, Francois Cotton, Frederik Maes, Dominique Sappey-Marinier, Sabine Van Huffel
Processing of longitudinal diffusion tensor imaging (DTI) data is a crucial challenge to better understand pathological mechanisms of complex brain diseases such as multiple sclerosis (MS) where white matter (WM) fiber-bundles are variably altered by inflammatory events.
August 3, 2016: IEEE Journal of Biomedical and Health Informatics
Youyi Song, Liang He, Feng Zhou, Siping Chen, Dong Ni, Baiying Lei, Tianfu Wang
Quantitative analysis of bacterial morphotypes in the microscope images plays a vital role in diagnosis of bacterial vaginosis (BV) based on the Nugent score criterion. However, there are two main challenges for this task: (1) It is quite difficult to identify the bacterial regions due to various appearance, faint boundaries, heterogeneous shapes, low contrast with the background, and small bacteria sizes with regards to the image; (2) There are numerous bacteria overlapping with each other, which hinder us to conduct accurate analysis on individual bacterium...
July 27, 2016: IEEE Journal of Biomedical and Health Informatics
Seddigheh Baktash, Mohamad Forouzanfar, Izmail Batkin, Miodrag Bolic, Voicu Groza, Saif Ahmad, Hilmi Dajani
Non-invasive blood pressure (BP) measurement is an important tool for managing hypertension and cardiovascular disease. However, automated non-invasive BP measurement devices, which are usually based on the oscillometric method, do not always provide accurate estimation of BP. It has been found that change in arterial stiffness (AS) is an underlying mechanism of disagreement between an oscillometric BP monitor and a sphygmomanometer. This problem is addressed by incorporating parameters related to AS in the algorithm for BP measurement...
July 27, 2016: IEEE Journal of Biomedical and Health Informatics
Jin-Chern Chiou, Shun-Hsi Hsu, Yu-Te Liao, Yu-Chieh Huang, Guan-Ting Yeh, Cheng-Kai Kuei, Kai-Shiun Dai
This paper presents a wireless on-lens intraocular pressure monitoring system, comprising a capacitance-to-digital converter and a wirelessly powered radio-frequency identification (RFID)-compatible communication system, for sensor control and data communication. The capacitive sensor was embedded on a soft contact lens of 200 μm thickness using commercially available biocompatible lens material, to improve compliance and reduce user discomfort. The sensor chip was shown to achieve effective number of bits greater than 10 over a capacitance range up to 50 pF while consuming only 64-μW power...
September 2016: IEEE Journal of Biomedical and Health Informatics
Jiaqi Gong, Yanjun Qi, Myla D Goldman, John Lach
Inertial body sensors have emerged in recent years as an effective tool for evaluating mobility impairment resulting from various diseases, disorders, and injuries. For example, body sensors have been used in 6-min walk (6 MW) tests for multiple sclerosis (MS) patients to identify gait features useful in the study, diagnosis, and tracking of the disease. However, most studies to date have focused on features localized to the lower or upper extremities and do not provide a holistic assessment of mobility. This paper presents a causality analysis method focused on the coordination between extremities to identify subtle whole-body mobility impairment that may aid disease diagnosis...
September 2016: IEEE Journal of Biomedical and Health Informatics
Hakan Toreyin, Hyeon Ki Jeong, Sinan Hersek, Caitlin N Teague, Omer T Inan
Knee-joint sounds could potentially be used to noninvasively probe the physical and/or physiological changes in the knee associated with rehabilitation following acute injury. In this paper, a system and methods for investigating the consistency of knee-joint sounds during complex motions in silent and loud background settings are presented. The wearable hardware component of the system consists of a microelectromechanical systems microphone and inertial rate sensors interfaced with a field programmable gate array-based real-time processor to capture knee-joint sound and angle information during three types of motion: flexion-extension (FE), sit-to-stand (SS), and walking (W) tasks...
September 2016: IEEE Journal of Biomedical and Health Informatics
Andrea Cherubini, Maria Eugenia Caligiuri, Patrice Peran, Umberto Sabatini, Carlo Cosentino, Francesco Amato
This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2(*) relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge...
September 2016: IEEE Journal of Biomedical and Health Informatics
Hang Zhou, Hassan Rivaz
Brain tissue deforms significantly after opening the dura and during tumor resection, invalidating preoperative imaging data. Ultrasound is a popular imaging modality for providing the neurosurgeon with real-time updated images of brain tissue. Interpretation of postresection ultrasound images is difficult due to large brain shift and tissue resection. Furthermore, several factors degrade the quality of postresection ultrasound images such as the strong reflection of waves at the interface of saline water and brain tissue in resection cavities, air bubbles, and the application of blood-clotting agents around the edges of resection...
September 2016: IEEE Journal of Biomedical and Health Informatics
Zhiyuan Lu, Xiang Chen, Zhongfei Dong, Zhangyan Zhao, Xu Zhang
This paper introduces a pulse oximeter prototype designed for mobile healthcare. In this prototype, a reflection pulse oximeter is embedded into the back cover of a smart handheld device to offer the convenient measurement of both heart rate (HR) and SpO2 (estimation of arterial oxygen saturation) for home or mobile applications. Novel and miniaturized circuit modules including a chopper network and a filtering amplifier were designed to overcome the influence of ambient light and interferences that are caused by embedding the sensor into a flat cover...
September 2016: IEEE Journal of Biomedical and Health Informatics
Malcolm Clarke, Hulya Gokalp, Joanna Fursse, Russell W Jones
This study presents a novel dynamic threshold algorithm that is applied to daily self-measured SpO2 data for management of chronic obstructive pulmonary disease (COPD) patients in remote patient monitoring to improve accuracy of detection of exacerbation. Conventional approaches based on a fixed threshold applied to a single SpO 2 reading to detect deterioration in patient condition are known to have poor accuracy and result in high false alarm rates. This study develops and evaluates use of a dynamic threshold algorithm to reduce false alarm rates...
September 2016: IEEE Journal of Biomedical and Health Informatics
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