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Deep brain stimulation (DBS) of the subthalamic nucleus reduces the severity of parkinsonian motor symptoms, but the therapeutic mechanisms are not understood. We hypothesize that clinically effective high frequency DBS suppresses disordered neuronal activity in the globus pallidus internus (GPi), a primary output structure of the basal ganglia. In a computational model of the basal ganglia thalamic...
We have recently developed a robust 2D post-beamforming filter for contrast restoration in ultrasound imaging systems using coarsely-sampled array apertures, e.g. high frequency ultrasound (HFUS). The filter can be derived from a discretized 2D impulse response model in the region of interest (ROI). The key to the robustness of the regularized 2D pseudoinverse filter is transforming the operator to...
Therapeutic benefits of subthalamic nucleus (STN) deep brain stimulation (DBS) for motor symptoms of Parkinson's disease (PD) are well-documented. However, the mechanisms underlying motor improvement with DBS remain poorly understood. We tested the hypothesis that STN-DBS-related improvements in voluntary arm movement kinematics are mediated by changes in the velocity and temporal sequencing of proximal...
Transient-evoked otoacoustic emissions (TEOAE) are generated by the cochlea in response to clicks. They are obtained by averaging post-onset acoustic responses which are composed of the stimulus-related meatal response (MR) and the TEOAEs. TEOAEs are typically below normal hearing thresholds and are obstructed by the MR, which is several orders of magnitude higher. For click stimuli, MRs typically...
Electrocardiography is the method of choice for cardiac electrophysiological evaluation. Arrhythmia is one of the most crucial problems in cardiology. So far, many methods have been developed for arrhythmia detection, recognition and classification. A popular method is ECG modeling using a basis function (such as wavelet, hermite or RBF) and classifying the coefficients of the basis functions. We...
Empirical mode decomposition has been shown effective in the analysis of non-stationary and non-linear signals. As an application in wireless life signs monitoring in this paper we use this method in conditioning the signals obtained from the Doppler device. Random physical movements, fidgeting, of the human subject during a measurement can fall on the same frequency of the heart or respiration rate...
Active cardiac stabilization has a role to play in the development of minimally invasive techniques for beating heart surgery. We propose here a new active cardiac stabilization device based on gyroscopic actuation. This system allows to compensate for heart motion in high frequencies and is fully independent and pluggable on conventional stabilizers. The mechanical model and design are described...
In the present paper, an electroencephalography (EEG)-based real-time dynamic neuroimaging system, which was recently developed by the authors, is introduced and its potential applications are presented. The real-time system could monitor spatiotemporal changes of cortical rhythmic activity on a subject's cortical surface, not on the subject's scalp surface, with a high temporal resolution. The developed...
The stationary wavelet packet analysis is exploited for the first time in the design of a self-paced BCI based on mental tasks. The BCI system is custom designed to achieve a zero false positive rate, as false activations highly restricts the applications of BCIs in real life. The EEG signals of four subjects performing five different mental tasks are used as the dataset. The stationary wavelet packets...
Significant research effort has been expended on investigating methods to non-invasively characterize gastrointestinal electrical activity. Despite the clinical success of the 12-lead electrocardiograms (ECG) and the emerging success of inverse methods for characterizing electrical activity of the heart and brain, similar methods have not been successfully transferred to the gastrointestinal field...
Genetic programming is used to generate a solution that can classify localized muscle fatigue from filtered and rectified surface electromyography (sEMG). The GP has two classification phases, the GP training phase and a GP testing phase. In the training phase, the program evolved with multiple components. One component analyzes statistical features extracted from sEMG to chop the signal into blocks...
Active echolocation is a sensory modality possessed by a variety of mammals and is used for the identification, classification and localization of objects. A multi stage model of the bat echolocation process has been used with recordings of rotated disks to plot frequency spectrums of the signals reaching each of the bats' ears. Recordings from objects made within the human audible frequency range...
In this work, it is proposed a technique for the feature extraction of electroencephalographic (EEG) signals for classification of mental tasks which is an important part in the development of Brain Computer Interfaces (BCI). The Empirical Mode Decomposition (EMD) is a method capable to process nonstationary and nonlinear signals as the EEG. This technique was applied in EEG signals of 7 subjects...
This paper presents a low-noise low-power amplifier for implantable device for neural signal acquisition. By operating MOS transistors in the subthreshold region, smaller low-frequency noise and lower power consumption can be achieved. A low power, low-noise common-drain buffer and a low-noise, high-linearity, low pass filter are used for high frequency noise filtering. Post-layout simulation shows...
An electroencephalograph (EEG)-based brain computer interface (BCI) requires rapid and reliable extraction of features in EEG signal. Recently, the rhythmic component extraction (RCE) method has been proposed to extract features of multi-channel EEG. RCE can extract a signal component with a certain frequency from multi-sensor signals. In this paper, we applied RCE to extract a feature corresponding...
High frequency chest compression (HFCC) treatment systems are used to promote mucus transport and mitigate pulmonary system clearance problems to remove sputum from the airways in patients with Cystic Fibrosis (CF) and at risk of developing chronic obstructive pulmonary disease (COPD). Every HFCC system consists of a pump generator, one or two hoses connected to a vest, to deliver the pulsation. There...
A major limitation of current Brain-Computer Interfaces (BCI) based on Motor Imagery (MI) is that they are subject-specific BCI, which require data recording and system training for each new user. This process is time consuming and inconvenient, especially for casual users or portable BCI with limited computational resources. In this paper, we explore the design of a Subject-Independent (SI) MI-based...
Normal human locomotion requires the ability to control a complex, redundant neuromechanical system to repetitively cycle the legs in a stable manner. In a reduced paradigm of locomotion, hopping, we investigated the ability of human subjects to exploit motor redundancy in the legs to coordinate joint torques fluctuations to minimize force fluctuations generated against the ground. Although we saw...
Current density and electrical conductivity imaging research at the University of Toronto is reviewed. Methods for imaging live animals at low frequency are described and contrasted with EIT and other MRI based techniques. New work on imaging at radio frequencies is presented and future work directions are discussed. It is concluded that low frequency methods are mature and ready for application in...
In this work, the Bayesian framework is used for the analysis of fMRI data. The novelty of the proposed approach is the introduction of a spatio-temporal model used to estimate the variance of the noise across the images and the voxels. The proposed approach is based on a spatio-temporal version of generalized linear model (GLM). To estimate the regression parameters of the GLM as well as the variance...
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