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Biomedical Engineering and Bioengineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
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- Connectivity analysis of neuroimaging data (3)
- Active hand device (1)
- Algorithms (1)
- Biomedical signal processing (1)
- Brain effective connectivity (1)
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- Dynamic cortical connectivity (1)
- EEG (1)
- EM algorithm (1)
- EMG (1)
- FMRI (1)
- Factor model (1)
- HMM (1)
- Ionic Polymer Metallic Composite (1)
- Kalman filter (1)
- Microsurgery (1)
- Multivariate autoregressive model (1)
- Physiological tremor (1)
- Signal processing (1)
- Speech recognition (1)
- State-space model (1)
- Subsurface imaging (1)
- Tremor modeling (1)
- Vector autoregressive model (1)
- Publication
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Articles 1 - 7 of 7
Full-Text Articles in Biomedical Engineering and Bioengineering
Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla
Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla
Vijayan K. Asari
The human brain’s ability to extract information from multidimensional data modeled by the Nonlinear Line Attractor (NLA), where nodes are connected by polynomial weight sets. Neuron connections in this architecture assumes complete connectivity with all other neurons, thus creating a huge web of connections. We envision that each neuron should be connected to a group of surrounding neurons with weighted connection strengths that reduces with proximity to the neuron. To develop the weighted NLA architecture, we use a Gaussian weighting strategy to model the proximity, which will also reduce the computation times significantly. Once all data has been trained in …
Review Of Emg-Based Speech Recognition, Amean Al_Safi, Liqaa Alhafadhi
Review Of Emg-Based Speech Recognition, Amean Al_Safi, Liqaa Alhafadhi
Amean S Al_Safi
This study represents a review of the main studies in EMG-based speech recognition. Its main goal is to support the researchers in the biomedical field with a survey of the solved and unsolved problem in the direction since it has received a great attention during last decade due to its promise applications such as underwater communication and silent speech recognition. Hence this study is a very good starting point for the researchers interested in this area of research
Estimating Effective Connectivity From Fmri Data Using Factor-Based Subspace Autoregressive Models, Chee-Ming Ting Phd, Abd-Krim Seghouane Phd, Sh-Hussain Salleh Phd, Alias M. Noor Phd
Estimating Effective Connectivity From Fmri Data Using Factor-Based Subspace Autoregressive Models, Chee-Ming Ting Phd, Abd-Krim Seghouane Phd, Sh-Hussain Salleh Phd, Alias M. Noor Phd
Chee-Ming Ting
Estimation Of High-Dimensional Brain Connectivity From Fmri Data Using Factor Modeling, Chee-Ming Ting Phd, Abd-Krim Seghouane, Sh-Hussain Salleh, Alias M. Noor
Estimation Of High-Dimensional Brain Connectivity From Fmri Data Using Factor Modeling, Chee-Ming Ting Phd, Abd-Krim Seghouane, Sh-Hussain Salleh, Alias M. Noor
Chee-Ming Ting
We consider identifying effective connectivity of brain networks from fMRI time series. The standard vector autoregressive (VAR) models fail to give reliable network estimates, typically involving very large number of nodes. This paper adopts a dimensionality reduction approach based on factor modeling, to enable effective and efficient high-dimensional VAR analysis of large network connectivity. We derive a subspace VAR (SVAR) model from the factor model (FM) in which the observations are driven by a lower dimensional subspace of common latent factors, following an autoregressive dynamics. We consider the principal components (PC) method which can produce consistent estimators for the FM, …
Estimating Dynamic Cortical Connectivity From Motor Imagery Eeg Using Kalman Smoother & Em Algorithm, S. Balqis Samdin, Chee-Ming Ting Phd, Sh-Hussain Salleh, Mahyar Hamedi, Alias Mohd Noor
Estimating Dynamic Cortical Connectivity From Motor Imagery Eeg Using Kalman Smoother & Em Algorithm, S. Balqis Samdin, Chee-Ming Ting Phd, Sh-Hussain Salleh, Mahyar Hamedi, Alias Mohd Noor
Chee-Ming Ting
This paper considers identifying effective cortical connectivity from scalp EEG. Recent studies use time-varying multivariate autoregressive (TV-MAR) models to better describe the changing connectivity between cortical regions where the TV coefficients are estimated by Kalman filter (KF) within a state-space framework. We extend this approach by incorporating Kalman smoothing (KS) to improve the KF estimates, and the expectation-maximization (EM) algorithm to infer the unknown model parameters from EEG. We also consider solving the volume conduction problem by modeling the induced instantaneous correlations using a full noise covariate. Simulation results show the superiority of KS in tracking the coefficient changes. We …
Development Of A Novel Handheld Device For Active Compensation Of Physiological Tremor, Abhijit Saxena
Development Of A Novel Handheld Device For Active Compensation Of Physiological Tremor, Abhijit Saxena
Abhijit Saxena
In microsurgery, the human hand imposes certain limitations in accurately positioning the tip of a device such as scalpel. Any errors in the motion of the hand make microsurgical procedures difficult and involuntary motions such as hand tremors can make some procedures significantly difficult to perform. This is particularly true in the case of vitreoretinal microsurgery. The most familiar source of involuntary motion is physiological tremor. Real-time compensation of tremor is, therefore, necessary to assist surgeons to precisely position and manipulate the tool-tip to accurately perform a microsurgery. In this thesis, a novel handheld device (AID) is described for compensation …
Field Programmable Gate Arrays To Accelerate Sub-Surface Imaging Problems, Miriam Leeser
Field Programmable Gate Arrays To Accelerate Sub-Surface Imaging Problems, Miriam Leeser
Miriam Leeser
No abstract provided.