Sharif Digital Repository

Hypertension precvalence is 24 and 20.5 percent in men and women, respectively. Continuous Blood Pressure monitoring can provide invaluable information about individuals’ health conditions. However, BP is conventionally measured using inconvenient cuff-based instruments, which prevents continuous BP monitoring. This work presents an efficient algorithm, based on the Pulse Arrival Time (PAT), extracted from Electrocardiogram (ECG) and Photopletysmograph (PPG), for the continuous and cuff-less estimation of the Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Mean Arterial Pressure (MAP) values. Methods: The proposed framework estimates the BP values through processing vital... 

The human action recognition is one of the most important concepts of computer vision in recent decades. Most of the two dimensional methods in this field are facing serious challenges such as occlusion and missing the third dimension of data. Development of depth sensors has made easy access to tracking people and 3D positions of human body joints. This Thesis proposes a new method of action recognition that utilizes the position of joints obtained by Kinect sensor. The learning stage uses Fisher Linear Discriminant Analysis (LDA) to construct discriminant feature space. Two types of distances, i.e., Euclidean and Mahalanobis, are used for recognizing the states. Also, Hidden Markov Model... 

The non-stationary nature of brain activity signals and their many inter-subject differences have created many challenges in the practical applications of emotion recognition based on electroencephalogram (EEG) signals, such as brain-computer interfaces. In such a way, the use of traditional classifiers in classifying these signals leads to a significant decrease in accuracy when applying the classifier to a new subject. Domain Adaptation methods seem to be an effective way to solve this problem by minimizing the difference between the EEG signals of different subjects. But in the basic techniques for domain adaptation, looking at all subjects' data in the same look causes the loss of a part... 

In this project, a novel action recognition method, named Fisherposes, is proposed, which is improved by several space-time (spatio-temporal) methods afterwards. The proposed method utilizes skeleton data obtained from Kinect sensor. First, pre-processing is performed in which the scales of bodies are canceled and the skeletons become aligned in order to make the method robust to location, orientation, and scale of people. In Fisherposes method, every action is defined as a sequence of body poses. Using the training samples for the poses, a Fisher subspace is created which we name it Fisherposes. Moreover, a novel distance measuring function, named regularized Mahalanobis distance, is... 

Surface growth is one of subjects that has many applications in industry, and its deep recognition in physics remarkably helps us in understanding of critical systems. There are various approaches for analyzing this phenomenon, one of the most important of which is differential equations.In this approach, with respect to surface properties, a partial differential equation is introduced, and the critical exponents are obtained by solving it. In this thesis, after studying several continuum equations such as: Edwards-Wilkinson, KPZ, and Wolf-Villain equation,we provide numerical solutions of these equations in presence of height dependent noise. The role of noise in stochastic differential... 

Human has different emotions such as happiness, sadness, anger, etc. Recognizing these emotions plays an important role in human-machine interface. Emotion recognition can be divided into approaches, physiological and non-physiological signals. Non-physiological signals include facial expressions, body gesture, and voice, and physiological signals include electroencephalograph (EEG), electrocardiograph (ECG), and functional magnetic resonance imaging (fMRI). EEG signal has been absorbed a lot of attention in emotion recognition because recording of EEG signal is easy and it is non-invasive. Analysis of connectivity and interaction between different areas of the brain can provide useful...