Sharif Digital Repository

Surface electromyogram (sEMG) signals, a noninvasive bioelectric signal, can be used for the rehabilitation and control of artificial extremities. Current sEMG pattern-recognition systems suffer from a limited number of patterns that are frequently intensified by the unsuitable accuracy of the instrumentation and analytical system. To solve these problems, we designed a multistep-based sEMG pattern-recognition system where, in each step, a stronger more capable relevant technique with a noticeable improved performance is employed. In this paper, we utilized the sEMG signals to classify and recognize six classes of hand movements. We employed an adaptive neurofuzzy inference system (ANFIS) to... 

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected from the surface of skin has been used in diverse applications. One of its usages is in pattern recognition of hand prosthesis movements. The ability of current prosthesis devices has been generally limited to simple opening and closing tasks, minimizing their efficacy compared to natural hand capabilities. In order to extend the abilities and accuracy of prosthesis arm movements and performance, a novel sEMG pattern recognizing system is proposed. To extract more pertinent information we extracted sEMGs for selected hand movements. These features constitute our main... 

Background: Electromyography (EMG) is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG) can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided... 

In recent years, electromyogram signal (EMG) feature selection, based on wavelet transform, has received considerable attention. This study introduces a new multiwavelet function for surface EMG (sEMG) signal intended for tasks that involve hand movement recognition. To create the new wavelet function, several types of well known mother wavelet were exploited and through their integration the proposed mother wavelet was generated. The proposed wavelet function closely reproduced the characteristics of the EMG signal, while increasing the recognition accuracy of hand movements. We used eight unique classes of hand motions and considered the ability of various mother wavelets and the proposed... 

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected form surface of the skin has been used in diverse applications. One of its usages is exploiting it in a pattern recognition system which evaluates and synthesizes hand prosthesis movements. The ability of current prosthesis has been limited in simple opening and closing that decreases the efficacy of these devices in contrary to natural hand. In order to extend the ability and accuracy of prosthesis arm movements and performance, a novel approach for sEMG pattern recognizing system is proposed. In order to have a relevant comparison, present and recent research for... 

Surface Electromyogram signal collected from the surface of skin is a biopotential signal that may be influenced by different types of noise. This is a considerable drawback in the processing of the sEMG signals. To acquire the clean sEMG that contains useful information, we need to detect and eliminate these unwanted parts of signal. In this work, a new method based on wavelet thresholding technique is presented which provides an acceptable purified sEMG signal. sEMG signals for this study are extracted for various hand movements. We use three hand movements to calculate the near optimal estimation parameters. In this work two types of thresholding techniques, namely Stein unbiased risk... 

Electromyogram signal is a biopotential signal that may be measured on the surface of contracting muscles representing neuromuscular activities. This signal may be utilized in various applications such as clinical diagnosis of diseased neuromuscular systems and as a measurement tool for evaluation of rehabilitation activities. Another recent application is the usage of EMG signal in design and implementation of neural controlled prosthesis hands. For this purpose appropriate features of EMG signal are required such that intended hand movements may be recognized correctly. In this work we considered a new method based on quadratic time-frequency representation namely Wigner-Ville distribution... 

It is well-known that the conventional reproducing kernel particle method (RKPM) is unfavorable when dealing with the derivative type essential boundary conditions [1-3]. To remedy this issue a group of meshless methods in which the derivatives of a function can be incorporated in the formulation of the corresponding interpolation operator will be discussed. Formulation of generalized moving least squares (GMLS) on a domain and GMLS on a finite set of points will be presented. The generalized RKPM will be introduced as the discretized form of GMLS on a domain. Another method that helps to deal with derivative type essential boundary conditions is the gradient RKPM which incorporates the... 

Electromyogram (EMG) signal is an electrical manifestation of muscle contractions. EMG signal collected from surface of the skin, a non-invasive bioelectric signal, can be used in different rehabilitation applications and artificial extremities control. This study has proposed to utilize the surface EMG (SEMG) signal to recognize patterns of hand prosthesis movements. It suggests using an adaptive neuro-fuzzy inference system (ANFIS) to identify motion commands for the control of a prosthetic hand. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP) and least mean square (LMS) is utilized. Also in order to optimize the number of fuzzy rules, a... 

C14H11ClN2O, triclinic P1̄ (no. 2), a = 9.380(2) Å, b = 17.238(4) Å, c = 17.735(5) A&ring, α = 118.456(4)°, β = 98.935(5)°, γ = 92.811(5)°, V = 2465.5 Å3, Z = 8, Rgt(F) = 0.104, wRref(F 2) = 0.205, T = 200 K. © by Oldenbourg Wissenschaftsverlag  

The interpretation of brain signals has consistently been a captivating subject for rehabilitation specialists. This interest prompts the development of interfaces that facilitate the interface between human cognition and an external device. These interfaces are commonly regarded as brain-computer interfaces (BCIs). However, a significant limitation of many existing BCI systems is their inadequate computational efficiency, which hinders their practical applicability in real-world scenarios. In this study, we present a channel-selection-based electroencephalogram (EEG) analyzing method, which enhances the BCIs to be used in real-time applications. To be specific, this method enables real-time... 

Red mud (RM) is generated as a by-product during the production of alumina from bauxite ore. In this study, RM packing in a column is used as a catalyst for carbon–carbon double bond formation via Knoevenagel condensation. The reactants are added to the top of the column and then eluted with solvent. The products are collected in high yields and short time. RM packed in a column eliminates a catalyst separation step from the reaction mixture in this work. © 2007 Taylor & Francis Group, LLC  

A series of 3-cyano-2-pyridone derivatives were synthesized by one-pot four-component condensation reaction involving a benzaldehyde derivative, alkyl cyanoacetate, acyclic or cyclic ketones, and ammonium acetate in reflux condition. The X-ray structure of the products 5a and 5d confirm symmetric dimers via hydrogen bonding interactions between individual pyridine molecules showing, in addition, also π-π stacking interactions  

Red mud (RM) which emerges as a by-product from the alumina producing process has been used as an efficient catalyst for one-pot direct synthesis of nitrile compounds from aldehydes and hydroxylamine hydrochloride under microwave irradiation. ©ARKAT USA, Inc  

Pemphigus vulgaris is an autoimmune disease, in which the role of Th17 cytokines needs to be further explored. This study was performed to assess serum levels of three interleukins (IL) required for Th17 differentiation (IL-β, IL-6 and IL-23) and two specific Th17 cytokines (IL- 17 and IL-22) in a group of patients with pemphigus vulgaris, at baseline, 3 weeks and 6 months after of treatment. Correlations between anti-desmogleins and cytokines with disease severity as well as the influence of therapy on the above factors were assessed. Forty-three first-admitted pemphigus vulgaris patients with the active disease entered the study, but only 31 completed the study. Forty-five healthy... 

The demand for advanced materials such as silicon carbide particles reinforced copper matrix composites (Cu-SiC) is increasing due to the stringent design requirement in the electronic packaging, mechanical relays, welding electrodes, electrical contacts, contactors, switches, and circuit breaks industries. High interest in Cu-SiC composites is highlighted by combining high thermal and electrical conductivity with mechanical strength, mouldability, and low production cost. Two decades of intensive research have provided a wealth of new scientific knowledge on the intrinsic and extrinsic effects of SiC reinforcement vis-à-vis mechanical, tribological, thermal, and electrical properties of... 

In the present work, the effect of graphene oxide (GO) nanosheets on the antibacterial activity of CuO nanowire arrays under visible light irradiation is shown. A combined thermal oxidation/electrophoretic deposition technique was employed to prepare three-dimensional networks of graphene oxide nanosheets hybridized with vertically aligned CuO nanowires. With the help of standard antibacterial assays and X-ray photoelectron spectroscopy, it is shown that the light-activated antibacterial response of the hybrid material against gram-negative Escherichia coli is significantly improved as the oxide functional groups of the GO nanosheets are reduced. In order to explore the physicochemical...