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IEEE Journal of Biomedical and Health Informatics

Chenxi Yang, Negar Tavassolian
This work proposes a novel method of pulse transit time measurement. The proximal arterial location data is collected from seismocardiogram (SCG) recordings by placing a MEMS accelerometer on the chest wall. The distal arterial location data is recorded using an acoustic sensor placed inside the ear. The performance of distal location recordings is evaluated by comparing SCG-acoustic and SCG-Photoplethysmogram (PPG) measurements. PPG and acoustic performances under motion noise are also compared. Experimental results suggest comparable performances for the acoustic-based and PPG-based devices...
April 24, 2017: IEEE Journal of Biomedical and Health Informatics
Runtong Zhang, Donghua Chen, Xiaopu Shang, Xiaomin Zhu, Kecheng Liu
Current access control mechanisms of the hospital information system can hardly identify the real access intention of system users. A relaxed access control increases the risk of compromise of patient privacy. To reduce unnecessary access of patient information by hospital staff, this paper proposes a Knowledge-Constrained Role-Based Access Control (KC-RBAC) model in which a variety of medical domain knowledge is considered in access control. Based on the proposed Purpose Tree and knowledge-involved algorithms, the model can dynamically define the boundary of access to the patient information according to the context, which helps protect patient privacy by controlling access...
April 24, 2017: IEEE Journal of Biomedical and Health Informatics
Mimma Nardelli, Alberto Greco, Juan Bolea, Gaetano Valenza, Enzo Pasquale Scilingo, Raquel Bailon
The number of studies about ultra-short cardiovascular time series is increasing because of the demand for mobile applications in telemedicine and e-health monitoring. However, the current literature still needs a proper validation of heartbeat nonlinear dynamics assessment from ultra-short time series. This paper reports on the reliability of the Lagged Poincaré Plot (LPP) parameters - calculated from ultra-short cardiovascular time series. Reliability is studied on simulated as well as on real RR series...
April 18, 2017: IEEE Journal of Biomedical and Health Informatics
Manish Sapkota, Fujun Liu, Yuanpu Xie, Hai Su, Fuyong Xing, Lin Yang
Idiopathic Inflammatory Myopathy (IIM) is a common skeletal muscle disease that relates to weakness and inflammation of muscle. Early diagnosis and prognosis of different types of IIMs will guide the effective treatment. Interpretation of digitized images of the cross section muscle biopsy, which is currently done manually, provides the most reliable diagnostic information. With the increasing volume of images, the management and manual interpretation of the digitized muscle images suffer from low efficiency and high interobserver variabilities...
April 13, 2017: IEEE Journal of Biomedical and Health Informatics
Marco De Pasquale, Travis Moss, Sergio Cerutti, James Calland, Douglas Lake, 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 i) to find an early detection model for hemorrhage by exploring the range of data mining methods that are currently available, and ii) to compare prediction models utilizing continuously measured physiological data from bedside monitors to those using commonly obtained laboratory tests...
April 12, 2017: IEEE Journal of Biomedical and Health Informatics
Pratool Bharti, Anurag Panwar, Ganesh Gopalakrishna, Sriram Chellappan
In a 2012 survey, in the United States alone, there were more than 35; 000 reported suicides with approximately 1; 800 of being psychiatric inpatients. Recent CDC (Centers for Disease Control and Prevention) reports indicate an upward trend in these numbers. In psychiatric facilities, staff perform intermittent or continuous observation of patients manually in order to prevent such tragedies, but studies show that they are insufficient, and also consume staff time and resources. In this paper, we present the Watch-Dog system, to address the problem of detecting self-harming activities when attempted by in-patients in clinical settings...
April 7, 2017: IEEE Journal of Biomedical and Health Informatics
Yue Huang, Han Zheng, Chi Liu, Xinghao Ding, Gustavo 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...
April 6, 2017: IEEE Journal of Biomedical and Health Informatics
Robert M Seepers, Wenjin Wang, Gerard de Haan, Ioannis Sourdis, Christos Strydis
The time interval between consecutive heartbeats (interpulse interval, IPI) has previously been suggested for securing mobile-health (mHealth) solutions. This time interval is known to contain a degree of randomness, permitting the generation of a time- and person-specific identifier. It is commonly assumed that only devices trusted by a person can make physical contact with him/her, and that this physical contact allows each device to generate a similar identifier based on its own cardiac recordings. Under these conditions, the identifiers generated by different trusted devices can facilitate secure authentication...
April 5, 2017: IEEE Journal of Biomedical and Health Informatics
Olli Lahdenoja, Tero Hurnanen, Zuhair Iftikhar, Sami Nieminen, Timo Knuutila, Antti Saraste, Tuomas Kiviniemi, Tuija Vasankari, Juhani Airaksinen, Mikko Pankaala, Tero Koivisto
We present a smartphone-only solution for the detection of Atrial Fibrillation (AFib), which utilizes the builtin accelerometer and gyroscope sensors (Inertial Measurement Unit, IMU) in the detection. Depending on the patient's situation, it is possible to use the developed smartphone application either regularly or occasionally for making a measurement of the subject. The smartphone is placed on the chest of the patient who is adviced to lay down and perform a non-invasive recording, while no external sensors are needed...
April 5, 2017: IEEE Journal of Biomedical and Health Informatics
Md Shamsul Arefin, Jean-Michel Redoute, Mehmet Yuce
This paper presents a wireless capsule microsystem to detect and monitor pH, pressure, and temperature of the gastrointestinal (GI) tract in real-time. This research contributes to the integration of sensors (microfabricated capacitive pH, capacitive pressure, and resistive temperature sensors), frequency modulation and pulse-width modulation based interface IC circuits, microcontroller, and transceiver with meandered conformal antenna for the development of a capsule system. The challenges associated with the system miniaturization, higher sensitivity and resolution of sensors, and lower power consumption of interface circuits are addressed...
April 4, 2017: IEEE Journal of Biomedical and Health Informatics
Recep Avci, James Wilson, Diana Escalona-Vargas, Hari Eswaran
Due to its high spatial and temporal resolution, fetal magnetocardiography (fMCG) measurements have been used for fetal movement (FM) detection in several studies which considered the changes in the amplitude and/or morphology of measured fMCG signals. Using source localization for fMCG measurements, we propose a novel method to fit a magnetic dipole moment to fetal heart signals and investigate the positional changes of magnetic dipole in order to detect FMs. We first split each fMCG recording into 6-second time windows...
April 4, 2017: IEEE Journal of Biomedical and Health Informatics
Eda Akman Aydin, Omer Faruk Bay, Inan Guler
An Asynchronous Brain Computer Interface (A-BCI) determines whether or not a subject is on control state, and produces control commands only in case of subject's being on control state. In this study, we propose a novel P300 based A-BCI algorithm that distinguishes control state and non-control state of users. Furthermore, A-BCI algorithm combined with a dynamic stopping function that enables users to select control command independent from a fixed number of intensification sequence. The proposed P300 based A-BCI algorithm uses classification patterns to determine control state and uses optimal operating point of receiver operating characteristics (ROC) curve for dynamic stopping function...
April 4, 2017: IEEE Journal of Biomedical and Health Informatics
Wei Wang, David Ackland, Jodie McClelland, Kate E Webster, Saman Halgamuge
Quantitative gait analysis is an important tool in objective assessment and management of total knee arthroplasty (TKA) patients. Studies evaluating gait patterns in TKA patients have tended to focus on discrete data such as spatiotemporal information, knee range of motion and peaks in kinematics and kinetics, or consider selected principal components of gait waveforms for analysis. These strategies may not have the capacity to capture small variations in gait patterns associated with each joint across an entire gait cycle, and may ultimately limit the accuracy of gait classification...
March 30, 2017: IEEE Journal of Biomedical and Health Informatics
Weilin Zang, Ye Li
In wireless body area network (WBAN), walking movements can result in rapid channel fluctuations, which severely degrade the performance of transmission power control (TPC) schemes. On the other hand, these channel fluctuations are often periodic and are time-synchronized with the user's gait cycle, since they are all driven from the walking movements. In this paper, we propose a novel gait cycle driven transmission power control (G-TPC) for WBAN. The proposed G-TPC scheme reinforces the existing TPC scheme by exploiting the periodic channel fluctuation in the walking scenario...
March 28, 2017: IEEE Journal of Biomedical and Health Informatics
Stamos Katsigiannis, Naeem Ramzan
In this work, we present DREAMER, a multi-modal database consisting of electroencephalogram (EEG) and electrocardiogram (ECG) signals recorded during affect elicitation by means of audio-visual stimuli. Signals from 23 participants were recorded along with the participants self-assessment of their affective state after each stimuli, in terms of valence, arousal, and dominance. All the signals were captured using portable, wearable, wireless, low-cost and off-the-shelf equipment that has the potential to allow the use of affective computing methods in everyday applications...
March 27, 2017: IEEE Journal of Biomedical and Health Informatics
Wei Yang, Yunbi Liu, Liyan Lin, Zhaoqiang Yun, Zhentai Lu, Qianjin Feng, Wufan Chen
Lung field segmentation in chest radiographs (CXRs) is an essential preprocessing step in automatically analyzing such images. We present a method for lung field segmentation that is built on a high-quality boundary map detected by an efficient modern boundary detector, namely, a structured edge detector (SED). A SED is trained beforehand to detect lung boundaries in CXRs with manually outlined lung fields. Then, an ultrametric contour map (UCM) is transformed from the masked and marked boundary map. Finally, the contours with the highest confidence level in the UCM are extracted as lung contours...
March 27, 2017: IEEE Journal of Biomedical and Health Informatics
Fabian Prasser, Florian Kohlmayer, Helmut Spengler, Klaus Kuhn
The sharing of sensitive personal health data is an important aspect of biomedical research. Methods of data de-identification are often used in this process to trade the granularity of data off against privacy risks. However, traditional approaches, such as HIPAA Safe Harbor or k-anonymization, often fail to provide data with sufficient quality. Alternatively, data can be de-identified only to a degree which still allows to use it as required, e.g. to carry out specific analyses. Controlled environments, which restrict the ways recipients can interact with the data, can then be used to cope with residual risks...
March 23, 2017: IEEE Journal of Biomedical and Health Informatics
Udit Satija, Barathram Ramkumar, M Sabarimalai Manikandan
OBJECTIVE: Automatic detection and classification of noises can play a vital role in the development of robust unsupervised electrocardiogram (ECG) analysis systems. This paper proposes a novel unified framework for automatic detection, localization and classification of single and combined ECG noises. METHODS: The proposed framework consists of the modified ensemble empirical mode decomposition (CEEMD), the shortterm temporal feature extraction, and the decision rules based noise detection and classification...
March 22, 2017: IEEE Journal of Biomedical and Health Informatics
Moataz Eltoukhy, Christopher Kuenze, Jeonghoon Oh, Joseph Signorile
Reduction in balance is an indicator of fall risk, and therefore, an accurate and cost effective balance assessment tool is essential for prescribing effective postural control strategies. This study established the validity of the Kinect v2 sensor in assessing center of mass (CoM) excursion and velocity during single leg balance and voluntary ankle sway tasks among young and elderly subjects. We compared balance outcome measures (anteroposterior (AP) and mediolateral (ML) CoM excursion and velocity and average sway length) to a traditional three-dimensional motion analysis system...
March 22, 2017: IEEE Journal of Biomedical and Health Informatics
Qiangchang Wang, Yuanjie Zheng, Gongping Yang, Weidong Jin, Xinjian Chen, Yilong Yin
We propose a new Multi-scale Rotation-invariant Convolutional Neural Network (MRCNN) model for classifying various lung tissue types on high-resolution computed tomography (HRCT). MRCNN employs Gabor-local binary pattern (Gabor-LBP) which introduces a good property in image analysis - invariance to image scales and rotations. In addition, we offer an approach to deal with the problems caused by imbalanced number of samples between different classes in most of the existing works, accomplished by changing the overlapping size between the adjacent patches...
March 21, 2017: IEEE Journal of Biomedical and Health Informatics
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