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In mobile health applications, non-expert users often perform the required medical measurements without supervision. Therefore, it is important that the mobile device guides them through the correct measurement process and automatically detects potential errors that could impact the readings. Camera oximetry provides a non-invasive measurement of heart rate and blood oxygen saturation using the camera...
Monitoring the progression of maternal uterine activity provides important prognostic information during pregnancy and parturition. Currently used methods, however, are unsuitable for long-term observation of uterine activity. The abdominally measured electrohysterogram (EHG) provides a non-invasive alternative to the existing methods for long-term ambulatory uterine contraction monitoring. A new...
During pregnancy, analysis of the electrohysterogram (EHG), which measures the uterine electrical activity, can provide a fundamental contribution for the assessment of uterine contractions and the diagnosis of preterm labor. However, several aspects concerning uterine physiology and its link with EHG measurements are still unclear. As a consequence, the EHG is not yet part of the clinical practice...
A comprehensive multiscale model of the uterine muscle electrical activity would permit understanding the important link between the genesis and evolution of the action potential at the cell level and the process leading to labor. Understanding this link can open the way to more effective tools for the prediction of labor and prevention of preterm delivery.
Digital cytology plays an increasingly important role in breast cancer diagnosis. However, analysis of cytologic images is a very difficult task. Especially, nuclei segmentation is extremely challenging. In our work on fully automated medical diagnosis system we encountered the problem of densely clustered nuclei. We decided to use a segmentation algorithm that is rather rarely found in the literature...
The emergence of the new, High Efficiency Video Coding (HEVC) standard, combined with wide deployment of 4G wireless networks, will provide significant support toward the adoption of mobile-health (m-health) medical video communication systems in standard clinical practice. For the first time since the emergence of m-health systems and services, medical video communication systems can be deployed...
We develop a large deformations, Finite Elements biomechanical model of a stellate breast tumour, subject to prone to supine (MRI to US) breast deformations. Based on clinical findings, we introduce a volume of increased mammographic density/stiffness around a spiculated tumour, as well as a range of reported mechanical properties, both linear elastic and hyperelastic. This novel model demonstrates...
An algorithm based on the combination of electrocardiography (ECG) and seismocardiogranphy (SCG) is used to detect the start and the end of diastole in diastolic timed vibrations (DTV). The proposed algorithm uses the ECG-R wave as the reference point and detects the aortic valve closure (AC) and mitral valve closure (MC) points of the SCG signal. This algorithm enables DTV to operate very efficiently...
Terrestrial ballistocardiographic (BCG) measurements are typically performed in only one or two axes because of the coupling between the subject and the ground. An appropriate physiological interpretation of these BCG signals therefore assumes that the information in the unmeasured axis is either understood, or able to be ignored. BCG signals from measurements in microgravity can be made in all three...
Although mobile health monitoring where mobile sensors continuously gather, process, and update sensor readings (e.g. vital signals) from patient's sensors is emerging, little effort has been investigated in an energy-efficient management of sensor information gathering and processing. Mobile health monitoring with the focus of energy consumption may instead be holistically analyzed and systematically...
We propose a novel approach for estimating a dense 3D model of neoplasia in colonoscopy using enhanced imaging endoscopy modalities. Estimating a dense 3D model of neoplasia is important to make 3D measurements and to classify the superficial lesions in standard frameworks such as the Paris classification. However, it is challenging to obtain decent dense 3D models using computer vision techniques...
There exist multiple markers for measuring psychological stress, with varying specificities and sensitivities. However, in a real-life setting, there is limited data on how robust these methods may be especially in a relatively mobile context where the signal fidelity maybe limited. Thus any large scale data to inform how these methods perform, using commonly available sensors, based on both context...
This paper proposed an smartphone-based real-time ECG monitoring and recognition system. The ECG signal was acquired by a MSP430FG4618 low-power microprocessor and was converted via a Bluetooth module for wireless transmission to a smartphone. A noise-tolerant ECG heartbeat recognition algorithm based on discrete wavelet transform and higher-order statistics was employed to identify different types...
We have proposed an automated method for three-dimensional (3D) measurement of cerebral cortical thicknesses based on fuzzy membership maps derived from magnetic resonance (MR) images for evaluation of Alzheimer's disease (AD). The cerebral cortical thickness was three-dimensionally measured on each cortical surface voxel by using a localized gradient vector trajectory in a fuzzy membership map. The...
The purpose of this study is to propose an automatic segmentation about each bone (the femur, the tibia, the patellar, and fibular) of the knee in MDCT image. The proposed method was applied for six patients (Age 33 ± 13, four males / tew females). The proposed method segmented the knee joint into each bone by using anatomical structure for the knee joint. The experiments calculate matching rate of...
Thermal infrared imaging has been shown to be useful for diagnosing breast cancer, since it is able to detect small tumors and hence can lead to earlier diagnosis. In this paper, we present a computer-aided diagnosis approach for analysing breast thermograms. We extract image features that describe bilateral differences of the breast regions in the thermogram, and then feed these features to an ensemble...
Neural prosthetics are a promising technology for alleviating paralysis by actuating devices directly from the intention to move. Typical implementations of these devices require a calibration session to define decoding parameters that map recorded neural activity into movement of the device. However, a major factor limiting the clinical deployment of this technology is stability: with fixed decoding...
Because neurons are integrating input signals and translating them into timed output spikes, examining spike timing may reveal information about inputs, such as population activities of excitatory and inhibitory presynaptic neurons. Here we construct a state-space method for estimating not only such extrinsic parameters, but also an intrinsic neuronal parameter such as the membrane time constant from...
Obstructive sleep apnea (OSA) is a common sleep disorder that causes increasing risk of mortality and affects quality of life of approximately 6.62% of the total US population. Timely detection of sleep apnea events is vital for the treatment of OSA. In this paper, we present a novel approach based on extracting the quantifiers of nonlinear dynamic cardio-respiratory coupling from electrocardiogram...
We present a successful application of a soft computing approach based on the multivariate empirical mode decomposition (MEMD) method to EEG epileptic seizures separation. The results of the automatic multivatiate intrinsic mode functions (IMF) clustering allowed us to separate the seizure related spikes and sharp waves. The results of the proposed method have been compared with classical blind separation...
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