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The accurate left ventricular boundary detection in echocardiographic images allow cardiologists to study and assess cardiomyopathy in patients. Due to the tedious and time consuming manner of manually tracing the borders, deformable models are generally used for left ventricle segmentations. However, most deformable models require a good initialization, which is usually outlined manually by the user...
In the area of therapeutic ultrasound activated drug delivery, difficulties exist in designing a carrier that responds to ultrasound for triggering and imaging but also provides adequate treatment potential. In this paper, we report on a novel acoustically sensitive microcapsule reservoir that can be activated with therapeutic ultrasound for payload release and can be potentially tracked using imaging...
High frequency ultrasound imaging has realized high resolution in vivo imaging of the biological tissues at a microscopic level. Human skin structure, especially sebaceous glands at the deep part of the dermis, was observed by three-dimensional ultrasound microscopy with the central frequency of 120 MHz. The visco-elasticity and surface sebum level of the observed region were measured by established...
On-chip implementation of Hilbert-Huang transform (HHT) has great impact to analyze the non-linear and non-stationary biomedical signals on wearable or implantable sensors for the real-time applications. Cubic spline interpolation (CSI) consumes the most computation in HHT, and is the key component for the HHT processor. In tradition, CSI in HHT is usually performed after the collection of a large...
The aim of electrocardiogram (ECG) compression is to achieve as much compression as possible while the significant information is preserved in the reconstructed signal. Lossy thresholding-based compressors have shown good performance needing low computational resources. In this work, two compression schemes that include nearly perfect reconstruction cosine modulated filter banks for the signal decomposition...
Deep brain stimulation (DBS) has been demonstrated to effectively improve the motor symptoms of Parkinson's disease. However, the underlying mechanisms are not known. It has been reported that a period of time is required before the full effect on motor symptoms is realized after DBS is initiated and that suppression of symptoms persists after DBS ends under parkinsonian conditions. A computational...
Obesity is a worldwide epidemic and is a cause of many major chronic diseases. In most cases, obesity is a result of an imbalance between food intake and calories burned. Steps toward automated ingestion detection are being made. In order to automate the process of capturing ingestion, a method for detecting, analyzing, and recording sounds related to ingestion is being developed. In this paper, preliminary...
We investigated the possibility of creating a temporal representation of brain activity from fNIRS signals. In an experiment, subjects performed isometric arm movements in four directions, and fNIRS signals were measured over the primary motor area in the left hemisphere of their brain. We estimated the direction of the arm force from the fNIRS signals by using two classifiers: sparse linear regression...
We present an advanced approach towards a semi-autonomous, robotic personal assistant for handicapped people. We developed a multi-functional hybrid brain-robot interface that provides a communication channel between humans and a state-of-the-art humanoid robot, Honda's Humanoid Research Robot. Using cortical signals, recorded, processed and translated by an EEG-based brain-machine interface (BMI),...
This paper presents the control architecture and the first performance evaluation results of a novel and highly-dexterous 18 degrees of freedom (DOF) miniature master/slave teleoperated robotic system called SPRINT (Single-Port la-paRoscopy bimaNual roboT). The system was evaluated in terms of positioning accuracy, repeatability, tracking error during local teleoperation and end-effector payload....
In this paper, a control model is developed to automate the process of navigation in rat-robot-a new type of bio-robot based on BCI(Brain-Computer Interface) technique. Because of the particular difficulties in rat-robot control, we design a novel control model to ‘learn’ and ‘imitate’ the control behavior of human guidance. General Regression Neural Network (GRNN) model is used to analyze the control...
Intensive computer use has been associated with musculoskeletal disorders (MSDs). Although the underlying mechanisms are still not fully understood, muscle fatigue is thought to be a contributing factor. Previous studies have shown that keystroke durations are related to muscle twitch durations and may be used as a surrogate measure of muscle fatigue. Software tools have been developed to measure...
The primary problems of brain-computer interface (BCI) are the low channel capacity and high error rate. Therefore, an assistive motion control method is important for the brain-actuated robot to realize real-time and reliable control. To make the brain-actuated robot respond to the external environments with more flexibility, a shared control method based on fuzzy logic is proposed. Experimental...
Falls in the elderly are a major problem worldwide with enormous associated economic and societal costs. Minimum ground clearance (MGC) is an important gait variable when considering trip-related falls risk. This study aimed to investigate the clinical relevance of inertial sensor derived parameters, previously shown to be related to MGC. Previous research by the authors reported a surrogate method...
We present a novel method for the identification of the dynamics of physiological cardiac cell models. The main aim of the technique is to improve the computational efficiency of large-scale simulations of the electrical activity of the heart. The method identifies the dynamical attractor of a detailed physiological model using statistical learning techniques. In particular, a radial basis function...
A recent functional model of the left ventricle characterizes the ventricle's contractile state with parameters, rather than variables. The ventricle is treated as a pressure generator that is time and volume dependent. The heart's complex dynamics develop from a single equation based on the formation and relaxation of crossbridge bonds within underlying heart muscle. This equation permits the calculation...
In cardiovascular diagnostics, phase-contrast MRI is a valuable technique for measuring blood flow velocities and computing blood pressure values. Unfortunately, both velocity and pressure data typically suffer from the strong image noise of velocity-encoded MRI. In the past, separate approaches of regularization with physical a-priori knowledge and data representation with continuous functions have...
Spike detection from high data rate neural recordings is desired to ease the bandwidth bottleneck of bio-telemetry. An appropriate spike detection method should be able to detect spikes under low signal-to-noise ratio (SNR) while meeting the power and area constraints of implantation. This paper introduces a spike detection system utilizing lifting-based stationary wavelet transform (SWT) that decomposes...
Various research fields, such as brain computer interface, requires online acquisition and analysis of biological data to validate assumptions or to help obtaining insights into the physiological processes of the human body. In this paper we introduce the LivBioSig toolbox for online bio-signals processing and experimentation. This open source and modularized MATLAB toolbox allows performing various...
The evaluation of the carotid artery wall is fundamental for the assessment of cardiovascular risk. This paper presents the general architecture of an automatic strategy, which segments the lumen-intima and media-adventitia borders, classified under a class of Patented AtheroEdge™ systems (Global Biomedical Technologies, Inc, CA, USA). Guidelines to produce accurate and repeatable measurements of...
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