Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

In the present study, an attempt has been made to experimentally investigate the flexural performance of ten simply supported reinforced concrete gable roof beams, including solid control specimen (i.e., without openings) and nine beams with web openings of different dimensions and configurations. The nine beams with openings have identical reinforcement details. All beams were monotonically loaded to failure under mid-span loading. The main variables were the number of the created openings, the total area of the created openings, and the inclination angle of the posts between openings. Of interest is the load-carrying capacity, cracking resistance and propagation, deformability, failure mode, and strain development that represent the behav

Analyzing plantar pressure trajectories is crucial for assessing foot behavior in dynamic gait stability. We propose the identification of foot symmetry and the detection of deformities by analyzing the trajectories of the center of pressure (CoP) and peak pressure (PP). First, using a foot pressure mapping system, plantar pressure data are acquired during a normal gait cycle. After the data have been acquired, post processing extracts both the CoP and PP trajectories over the spatiotemporal domain of foot motion for each foot independently. For this purpose, we used the optical flow technique which accurately estimates the direction of foot motion. The extracted trajectories of each foot are then segmented into, the medial and lateral regi

This research is presenting a study of optical and structural properties of (Fe2O3)1-x(MgO)x composites synthesized as thin film that can be used as a gas sensor. Pulsed laser deposition technique was used to prepare thin films of (Fe2O3)1-x(MgO)x. The pattern of X-ray diffraction of the composites powder showed the consistency of iron oxide (α-Fe2O3) hematite phase along with the planes (104) and (110) as preferred planes for crystal growth where the intensities of which varied with MgO content. The crystal size of the thin film material was varied in between (26.8-35.1) nm. The diffraction pattern of the pulsed laser deposited thin films was absent from any diffraction peaks. The maximum transparency obtained of hematite

A Schiff base ligand (L) was used as primary ligand and potassium anthranilate (Anth) was used as the secondary ligand in the molar ratio M: L:2Anth to synthesize a new platinum(IV) mixed-ligand complex [Pt(L)(Anth)₂]Cl₂. The Schiff base ligand was synthesized by the condensation of 4-Aminoantipyrine with 4-Hydroxybenzaldehyde and was verified as a bidentate ligand. The UV-visible, FT-IR, 1 H NMR, 13 C NMR, CHN elemental analysis, molar conductance, chloride ion determination and melting point measurements were used to characterize the ligand and the complex. The results of the molar conductance showed that the electrolytic behavior was 1:2, where the two chloride ions were present outside the coordination sphere, while the spectroscopi

Among the many modern skill-enhancing work practices, machine learning is among the mostskill-enhancing practices in the workplace, as it helps students remember more of what they havelearned, hone the technical talents and skills of football players, and make better use of theirmotor skills. The use of machine learning and its practical applications in football could havesignificant benefits by improving talent development and making better use of scientifictechniques. The primary objective of this study was to determine the effectiveness of machinelearning in improving soccer dribbling and passing accuracy in children aged 10-12 years. Thestudy authors hypothesized that soccer players in the Al-Zohour Neighborhood Youth Forumwould greatly