Sharif Digital Repository

This research presents a robust method for P300 component recognition and classification in EEG signals for a P300 Speller Brain-Computer Interface (BCI). The multiresolution wavelet decomposition technique was used for feature extraction. The feature selection was done using an improved t-test method. For feature classification the Quadratic Discriminant Analysis was employed. No any particular specification is previously assumed in the proposed algorithm and all the constants of the system are optimized to generate the highest accuracy on a validation set. The method is first verified in offline experiments on 'BCI competition 2003' data set IIb and data recorded by Emotiv Neuroheadset and... 

In an effort to identify a useful noninvasive screening tool for cardiovascular diseases (CVD) screening, photoplethysmograph (PPG) signals were acquired and analyzed. These PPG signals were recorded during reactive hyperemia experiments consisting of a 4-minute blood flow blockage of the right arm (RA) brachial artery (BA) using a blood pressure cuff inflator. This procedure is usually done for the assessment of endothelial dysfunction which is a risk factor for developing CVD. In this study, signals of the infrared (IR) and red (R) LED's of the PPG sensor were analyzed. These signals were preprocessed, normalized and slow varying component of the signal (DC values) and the pulsatile... 

Dyslipidemia is considered to be one of the main heart risk factors, affecting the endothelial vascular function, which can be non-invasively investigated by ultrasound flow-mediated dilation (US-FMD). However, US-FMD comes at a high-cost and is operator-dependent. In this paper, the effect of dyslipidemia on the photoplethysmogram (PPG) signal recorded from collateral index fingers is investigated following a previous study where it was shown that results similar to that of US-FMD can be replicated by the PPG. Two groups, consisting of 30 healthy subjects free from any risk factors and 30 subjects who have only dyslipidemia as risk factor were respectively considered. The percent change in... 

Mathematical modeling of the neuro-musculoskeletal system in healthy subjects has been pursued extensively. In post-stroke patients, however, such models are very primitive. Besides improving our general understanding of how stroke affects the limb motions, they can be used to evaluate rehabilitation strategies by computer simulations before clinical evaluations. A planar neuro-musculoskeletal arm model for post-stroke patients is developed. The main idea is to use a set of new coefficients, Muscle Significance Factors (MSF), to incorporate the effects of stroke in the muscle control performance. The model uses the optimal control theory to mimic the performance of the CNS and a two-link... 

This study presents applying recurrence quantification analysis (RQA) on EEG recordings and their subbands: delta, theta, alpha, beta, and gamma for epileptic seizure detection. RQA is adopted since it does not require assumptions about stationarity, length of signal, and noise. The decomposition of the original EEG into its five constituent subbands helps better identification of the dynamical system of EEG signal. This leads to better classification of the database into three groups: Healthy subjects, epileptic subjects during a seizure-free interval (Interictal) and epileptic subjects during a seizure course (Ictal). The proposed algorithm is applied to an epileptic EEG dataset provided... 

Balance impairment is critical for many patient groups such as those with neural and musculoskeletal disorders and also the elderly. Accurate and objective assessment of balance performance has led to the development of several indices based on the measurement of the center of pressure. In this study, a robotic device was designed and fabricated to provide controlled and repeatable mechanical perturbations to the standing platform of the user. The device uses servo-controlled actuators and two parallel mechanisms to provide independent rotations in mediolateral and anterior-posterior directions. The device also provides visual feedback of the center of pressure position to the user.... 

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearestneighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known... 

Research question: Would there be differences in muscle activation between healthy subjects’ (HS) dominant leg and transfemoral amputees’ (TFA) intact-leg/contralateral-limb (IL) during normal transient-state walking speed? Methods: The muscle activation patterns are obtained by calculating the linear envelope of the EMG signals for each group. The activation patterns/temporal changes are compared between-population using statistical parametric mapping (SPM). Results: Individual muscle activity showed significant differences in all muscles except vastus lateralis (VL), semitendinosus (SEM) and tensor fascia latae (TFL) activities. Significance: The information could be used by the therapists...