Sharif Digital Repository

The accuracy of Photoplethysmographic signals is often not adequate due to motional artifacts induced in the recording site. Over recent decades there has been a widespread effort to reduce these artifacts and different methods are used for this aim. Nevertheless there are still some contradictory results reported by different methods about their effectiveness in artifact reduction. In this paper, we aim to compare three of established methods for PPG noise reduction on a unique dataset. Among different reported methods, we have chosen Adaptive Noise Cancellation (ANC), Discrete Wavelet Transform (DWT) and a newly developed method Cycle-by-cycle Fourier Series Analysis (CFSA) for denoising.... 

The brain-computer interfacing (BCI), a platform to extract features and classify different motor movement tasks from noisy and highly correlated electroencephalogram signals, is limited mostly by the complex and power-hungry algorithms. Among different techniques recently devised to tackle this issue, real-time onset detection, due to its negligible delay and minimal power overhead, is the most efficient one. Here, we propose a novel algorithm that outperforms the state-of-the-art design by sixfold in terms of speed, without sacrificing the accuracy for a real-time, hand movement intention detection based on the adaptive wavelet transform with only 1 s detection delay and maximum... 

Brain Computer Interface (BCI) systems, which are based on motor imagery, enable humans to command artificial peripherals by merely thinking about the task. There is a tremendous interest in implementing BCIs on portable platforms, such as Field Programmable Gate Arrays (FPGAS) due to their low-cost, low-power and portability characteristics. This article presents the design and implementation of a Brain Computer Interface (BCI) system based on motor imagery on a Virtex-6 FPGA. In order to design an accurate algorithm, the proposed method avails statistical learning methods such as Mutual Information (MI), Linear Discriminant Analysis (LDA), and Support Vector Machine (SVM). It also uses... 

Brain Computer Interface (BCI) systems, which are based on motor imagery, enable humans to command artificial peripherals by merely thinking about the task. There is a tremendous interest in implementing BCIs on portable platforms, such as Field Programmable Gate Arrays (FPGAS) due to their low-cost, low-power and portability characteristics. This article presents the design and implementation of a Brain Computer Interface (BCI) system based on motor imagery on a Virtex-6 FPGA. In order to design an accurate algorithm, the proposed method avails statistical learning methods such as Mutual Information (MI), Linear Discriminant Analysis (LDA), and Support Vector Machine (SVM). It also uses... 

The correct quantification of porosity is essential in all studies pertaining to porous media. A host of existing works employs a constant, bulk value for porosity, even when the porous sample is attached to a free fluid. Since the volume fraction of the solid matrix near the interface region differs from that in the core, the porosity undergoes a spatial variation. Here we present a novel relation for the porosity as a function of depth below the interface, using the concept of surface roughness applied on the classical definition of open porosity. This relation has been verified by computational modeling as well as non-invasive laser experiments. It has been shown that this depth-dependent... 

Downward fluxes of particulate organic matter (POM) are the major process for sequestering atmospheric CO2 into aquatic sediments for thousands of years. Budget calculations of the biological carbon pump are heavily based on the ratio between carbon export (sedimentation) and remineralization (release to the atmosphere). Current methodologies determine microbial dynamics on POM using closed vessels, which are strongly biased towards heterotrophy due to rapidly changing water chemistry (Bottle Effect). We developed a flow-through rolling tank for long term studies that continuously maintains POM at near in-situ conditions. There, bacterial communities resembled in-situ communities...