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In order for the functionality of an upper-limb prosthesis to approach that of a real limb it must be able to, accurately and intuitively, convey sensory feedback to the limb user. This paper presents results of the real-time implementation of a `biofidelic' model that describes mechanotransduction in Slowly Adapting Type 1 (SA1) afferent fibers. The model accurately predicts the timing of action...
Web Services and grid-enabled scientific workflows are of paramount importance for the realization of efficient and secure knowledge discovery scenarios. This paper presents a Grid-enabled Genotype-to-Phenotype discovery scenario (GG2P), which is realized by a respective scientific workflow. GG2P supports the seamless integration of SNP genotype data sources, and the discovery of indicative and predictive...
This paper presents a novel theoretical paradigm for epileptic seizure prediction based on a coupled oscillator model of brain dynamics. This model is used to investigate prediction methods capable of tracking the synchronization changes that may lead to a seizure. Previous results indicate that state-space reconstruction of a coupled oscillator model from an EEG-like signal is ill-posed, therefore,...
This work presents the random sampling - high dimensional model representation (RS-HDMR) algorithm for identifying complex bionetwork structures from multivariate data. RS-HDMR describes network interactions through a hierarchy of input-output (IO) functions of increasing dimensionality. Sensitivity analysis based on the calculated RS-HDMR component functions provides a statistically interpretable...
In this paper, we present a framework for neural activity detection using fMRI data, based on both statistical data analysis (data-driven) and graphical information modeling (model-based). The data-driven approaches do rough prediction when an extraordinary amount of neural activities arise. By proper exploration of spatial, temporal, inter-subject correlations, the model-based approaches can provide...
Recent experimental evidence suggests that a fundamental property of the human motor system is that it ldquoslacksrdquo; that is, that it continuously attempts to decrease levels of muscle activation when movement error is small during repetitive motions. This paper reviews several computational models of slacking, and discusses implications of slacking for the design of robotic orthoses. For therapeutic...
The implantable electrical stimulator is usually not suitable for long term use because of its large size and short battery life, besides the magnetic stimulation can not provide deep nerve stimulation. Therefore, this paper developed a method of the electrical stimulation by using the magnetic induction. We implanted a small inductive coil which was connected with nerve electrodes. When the stimulation...
The ability of mitochondria to oxidatively synthesize ATP from ADP and inorganic phosphate is compromised in the failing heart. Specifically, the magnitude of the free energy at which ATP is synthesized in heart failure is diminished compared to control. However the causal mechanisms involved are not clearly understood. Here we used computer simulation to analyze the impact of reduction in three cytoplasmic...
To predict the three dimensional structure of proteins, many computational methods sample the conformational space, generating a large number of candidate structures. Subsequently, such methods rank the generated structures using a variety of model quality assessment programs in order to obtain a small set of structures that are most likely to resemble the unknown experimentally determined structure...
When contracting a muscle using NFES (neural functional electrical stimulation), the stimulus always activates the axons of greater diameter first. Also selective activation of given fascicle inside a nerve is not possible with classical cuff electrode as the recruitment is performed uniformly around the nerve. These limits lead to poorly selective muscle recruitment, inducing fatigue and possible...
In an electromyographic and muscle force (EMG-force) model, the variability and uncertainty of the input muscle parameters increase the difficulty of assessing this type of model. In this study, a Monte Carlo method is used to evaluate the robustness and the sensitivity of an EMG-force model, recently developed by our team, for two groups of simulations (constant and sinusoidal force contractions)...
Constraint-based models of metabolism are becoming available for an increasing number of organisms. These models can be used in combination with existing experimental data to describe the behavior of an organism and to analyze experimental observations in the context of a model. Such a descriptive application of the models can also allow for the integration of various types of data. Additionally,...
The knowledge and prediction of the behavior of electrically activated muscles are important requisites for the movement restoration by FES in spinal cord injured subjects. The whole parameter's identification of a physiological musculoskeletal model for FES is investigated in this work. The model represents the knee and its associated quadriceps muscle. The identification protocol is noninvasive...
The Lung Cancer Survivability Prediction Tool (LCSPT) is a web-based system that predicts the survival possibility of a lung cancer patient based on the status of the patient and the treatments provided. In order to make the LCSPT more accessible and convenient to doctors working in a clinical setting, we have developed a new interface for mobile devices. The display size along with wireless data...
Two distinct approaches to smart home design, namely Distributed Direct Sensing (DDS) and Infrastructure Mediated Sensing (IMS), have distinguishing features and implications resulting from their implementation. These two distinct smart home approaches have not been directly compared pertaining to their technical performance or their acceptance by the end users. It is also unclear what the perceived...
Since the 1950s, we have developed mature theories of modern control theory and computational neuroscience with almost no interaction between these disciplines. With the advent of computationally efficient nonlinear Kalman filtering techniques, along with improved neuroscience models that provide increasingly accurate reconstruction of dynamics in a variety of important normal and disease states in...
Idiosyncratic drug hepatotoxicity is a hepatotoxicity subset that occurs in a very small fraction of human patients, is poorly predicted by standard preclinical models and in clinical trials, and frequently leads to postapproval drug failure. Animal models utilizing bacterial LPS co-administration to induce an inflammatory background and hepatocyte cell culture models utilizing cytokine mix cotreatment...
Current methods for reconstructing biological networks often learn either the topology of large networks or the kinetic parameters of smaller networks with a well-characterized topology. We have recently described a network reconstruction algorithm, the Inferelator 1.0, that given a set of genome-wide measurements as input, simultaneously learns both topology and kinetic-parameters. Specifically,...
A well known and major component of movement control is the feedforward component, also known as the internal model. This model predicts and compensates for expected forces seen during a movement, based on recent experience, so that a well-learned task such as reaching to a target can be executed in a smooth straight manner. It has recently been shown that the state of preparation of planned movements...
Seizure onset prediction in epilepsy is a challenge which is under investigation using many and varied signal processing techniques. Here we present a multi-stage phase synchrony based system that brings to bear the advantages of many techniques in each substage. The 1st stage of the system unmixes continuous long-term (2-4 days) multichannel scalp EEG using spatially constrained Independent Component...
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