Review on support vector machine (SVM) classifier for human emotion pattern recognition from EEG signals

This study reviewed the strategy in pattern classification for human emotion recognition system based on Support Vector Machine (SVM) classifier on Electroencephalography (EEG) signal. SVM has been widely used as a classifier and has been reported as having minimum error and produce accurate classification. However, the accuracy is influenced by many factors such as the electrode placement, equipment used, preprocessing techniques and selection of feature extraction methods. There are many types of SVM classifier such as SVM via Radial Basis Function (RBF), Linear Support Vector Machine (LSVM) and Multiclass Least Squares Support Vector Machine (MC-LS-SVM). SVM via RBF states the average accuracy rate of 92.73, 85.41, 93.80 and 67.40% using different features extraction method, respectively. The accuracy using LSVM and MC-LS-SVM classifier are 91.04 and 77.15%, respectively. Although, the accuracy rate influenced by many factors in the experimental works, SVM always shows their function as a great classifier. This study will discuss and summarize a few related works of EEG signals in classifying human emotion using SVM classifier

Hardware Implementation of 32-Bit High-Speed Direct Digital Frequency Synthesizer

The design and implementation of a high-speed direct digital frequency synthesizer are presented. A modified Brent-Kung parallel adder is combined with pipelining technique to improve the speed of the system. A gated clock technique is proposed to reduce the number of registers in the phase accumulator design. The quarter wave symmetry technique is used to store only one quarter of the sine wave. The ROM lookup table (LUT) is partitioned into three 4-bit sub-ROMs based on angular decomposition technique and trigonometric identity. Exploiting the advantages of sine-cosine symmetrical attributes together with XOR logic gates, one sub-ROM block can be removed from the design. These techniques, compressed the ROM into 368 bits. The ROM compressed ratio is 534.2 : 1, with only two adders, two multipliers, and XOR-gates with high frequency resolution of 0.029 Hz. These techniques make the direct digital frequency synthesizer an attractive candidate for wireless communication applications

Optical Interconnect Waveguide in Electronic Circuit

The increasing demand in silicon nano-photonics has encouraged many researchers to put more efforts to explore the feasibility of using optics in the communication medium in order to replace the conventional electrical interconnects (EIs). In this paper, we proposed a SOI- based waveguide in the optical interconnect (OI) link at an operating frequency of 1550nm to work as an interconnection path in a circuit. The performance capability of the OI link was tested using a two-stage CE amplifier to work as the interconnection path from the 1st stage to the 2nd stage amplifier. In term of optical performances, the optical waveguide interconnect managed to achieve a single mode condition for a TE mode and fulfill the receiver sensitivity of a photodiode. While, in term of electrical performance, a two-stage CE amplifier is able to produce a high gain, a wide bandwidth and high slew rate. The proposed implementation of the OIs waveguide is succesfully enhance the performance of the two-stage CE amplifier as well as the analog electronic circuit applications

Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task

The aim of this pilot study was to select the most similar mother wavelet function and the most efficient threshold in order to use with wavelet basis function for the human brain electrical activity during working memory task. A 60 seconds was recorded from the scalp using the Electroencephalography (EEG). 19 electrodes were placed over different sites on the scalp where analyzed for one control subject and one post-stroke patients in the first week of his stroke onset. In this study, forty-five mother wavelet basis functions from orthogonal families with four thresholding methods were used. The selection of mother wavelet functions like Daubechies (db), symlet (sym) and coiflet (coif) and the thresholding methods these are sqtwolog, rigrsure, heursure and minimax are to check mother wavelet functions similarity with the recorded EEG signals during working memory task. The test have been done using four evaluating criteria, namely signal to noise ratio (SNR), peak signal to noise ratio (PSNR) mean square error (MSE) and crosscorelation method (xcorr). Symlet mother wavelet of order 9 (sym9) is the most compatible for all the 19 channels for both EEG datasets that selected to be examined and the best results have been obtained by using the rigrsure thresholding method

EEG markers for early detection and characterization of vascular dementia during working memory tasks

The aim of the this study was to reveal markers using spectral entropy (SpecEn), sample entropy (SampEn) and Hurst Exponent (H) from the electroencephalography (EEG) background activity of 5 vascular dementia (VaD) patients, 15 stroke-related patients with mild cognitive impairment (MCI) and 15 control healthy subjects during a working memory (WM) task. EEG artifacts were removed using independent component analysis technique and wavelet technique. With ANOVA (p < 0.05), SpecEn was used to test the hypothesis of slowing the EEG signal down in both VaD and MCI compared to control subjects, whereas the SampEn and H features were used to test the hypothesis that the irregularity and complexity in both VaD and MCI were reduced in comparison with control subjects. SampEn and H results in reducing the complexity in VaD and MCI patients. Therefore, SampEn could be the EEG marker that associated with VaD detection whereas H could be the marker for stroke-related MCI identification. EEG could be as a valuable marker for inspecting the background activity in the identification of patients with VaD and stroke-related MCI

An Integrated Hybrid Energy Harvester for Autonomous Wireless Sensor Network Nodes

Profiling environmental parameter using a large number of spatially distributed wireless sensor network (WSN) NODEs is an extensive illustration of advanced modern technologies, but high power requirement for WSN NODEs limits the widespread deployment of these technologies. Currently, WSN NODEs are extensively powered up using batteries, but the battery has limitation of lifetime, power density, and environmental concerns. To overcome this issue, energy harvester (EH) is developed and presented in this paper. Solar-based EH has been identified as the most viable source of energy to be harvested for autonomous WSN NODEs. Besides, a novel chemical-based EH is reported as the potential secondary source for harvesting energy because of its uninterrupted availability. By integrating both solar-based EH and chemical-based EH, a hybrid energy harvester (HEH) is developed to power up WSN NODEs. Experimental results from the real-time deployment shows that, besides supporting the daily operation of WSN NODE and Router, the developed HEH is capable of producing a surplus of 971 mA·hr equivalent energy to be stored inside the storage for NODE and 528.24 mA·hr equivalent energy for Router, which is significantly enough for perpetual operation of autonomous WSN NODEs used in environmental parameter profiling

Investigation on optical interconnect(OI) link performance using external modulator

This paper investigates and analyzes an Optical Interconnect (OI) link using external (indirect) modulation technique. A Continuous Wave (CW) light source with a Mach Zehnder (MZ) modulator is used in the transmitter part and a Si-based waveguide is used as a transmission path. Indium Gallium Arsenide (InGaAs) and Germanium (Ge) materials were applied to observe the performance of Avalanche Photodiode (APD) and P-I-N Photodiode (PIN). In order to evaluate the performance of OI link using external (indirect) modulation, the model of OI link was designed and simulated using OptiSPICE tools. Simulation results on the performance of MZ modulator, power degradation of OI link and receiver sensitivity are reported in this paper

Implementation of SOI-Based Rib Waveguide for High-Speed Optical Interconnect

Silicon based photonics have generated strong interest in recent years, mainly in optical waveguide interconnects for microelectronic circuits. This paper presents a single mode condition (SMC) of SOI-based rib waveguide for high-speed Optical Interconnect (OI) implementation at a circuit level. In OptiBPM, a correlation analysis between two parameters, etched rib thickness (r) and effective index (neff) was investigated to identify the effects of width (W) on the rib waveguide. The waveguide performance of the OI links such as output power, propagation loss and propagation delay was recorded based on OptiSPICE simulation. A wavelength (λ) of 1550 nm has the advantages of low power loss and delay which makes it reliable for high-speed OI applications

A simulation study of thickness effect in performance of double lateral gate junctionless transistors

The electrical behaviour of double lateral gate junctionless transistors, regarding to the variation of channel thickness is investigated, through 3-D numerical simulations. The simulation results explicitly show that how the device thickness affect the on and off current and threshold voltage behavior based on variation of the carriers density and recombination rates of the carriers. As the channel thickness is decreased, the amount of bulk neutral channel getting smaller which cause a decrease in the on state current. Meanwhile, the lateral gate influence on the channel is reinforced, which cause a decrease in leakage current in the off state. Threshold voltage is decreased as the channel thickness decreases. However, the recombination rate of carriers increases with decreasing the channel thickness, due to the accumulation of minority carries and shifted to the source side of the channel