Real-time classification of finger movements using two-channel surface electromyography

The use of a small number of Electromyography (EMG) channels for classifying the finger movement is a challenging task. This paper proposes the recognition system for decoding the individual and combined finger movements using two channels surface EMG. The proposed system utilizes Spectral Regression Discriminant Analysis (SRDA) for dimensionality reduction, Extreme Learning Machine (ELM) for classification and the majority vote for the classification smoothness. The experimental results show that the proposed system was able to classify ten classes of individual and combined finger movements, offline and online with accuracy 97.96 % and 97.07% respectively

Active exoskeleton control systems: State of the art

To get a compliant active exoskeleton controller, the force interaction controllers are mostly used in form of either the impedance or admittance controllers. The impedance or admittance controllers can only work if they are followed by either the force or the position controller respectively. These combinations place the impedance or admittance controller as high-level controller while the force or position controller as low-level controller. From the application point of view, the exoskeleton controllers are equipped by task controllers that can be formed in several ways depend on the aims. This paper presents the review of the control systems in the existing active exoskeleton in the last decade. The exoskeleton control system can be categorized according to the model system, the physical parameters, the hierarchy and the usage. These considerations give different control schemes. The main consideration of exoskeleton control design is how to achieve the best control performances. However, stability and safety are other important issues that have to be considered. © 2012 The Authors

Index finger motion recognition using self-advise support vector machine

Because of the functionality of an index finger, the disability of its motion in the modern age can decrease the person's quality of life. As a part of rehabilitation therapy, the recognition of the index finger motion for rehabilitation purposes should be done properly. This paper proposes a novel recognition system of the index finger motion suing a cutting-edge method and its improvements. The proposed system consists of combination of feature extraction method, a dimensionality reduction and well-known classifier, Support Vector Machine (SVM). An improvement of SVM, Self-advise SVM (SA-SVM), is tested to evaluate and compare its performance with the original one. The experimental result shows that SA-SVM improves the classification performance by on average 0.63 %

Deep feature meta-learners ensemble models for Covid-19 CT scan classification

The infectious nature of the COVID-19 virus demands rapid detection to quarantine the infected to isolate the spread or provide the necessary treatment if required. Analysis of COVID-19-infected chest Computed Tomography Scans (CT scans) have been shown to be successful in detecting the disease, making them essential in radiology assessment and screening of infected patients. Single-model Deep CNN models have been used to extract complex information pertaining to the CT scan images, allowing for in-depth analysis and thereby aiding in the diagnosis of the infection by automatically classifying the chest CT scan images as infected or non-infected. The feature maps obtained from the final convolution layer of the Deep CNN models contain complex and positional encoding of the images’ features. The ensemble modeling of these Deep CNN models has been proved to improve the classification performance, when compared to a single model, by lowering the generalization error, as the ensemble can meta-learn from a broader set of independent features. This paper presents Deep Ensemble Learning models to synergize Deep CNN models by combining these feature maps to create deep feature vectors or deep feature maps that are then trained on meta shallow and deep learners to improve the classification. This paper also proposes a novel Attentive Ensemble Model that utilizes an attention mechanism to focus on significant feature embeddings while learning the Ensemble feature vector. The proposed Attentive Ensemble model provided better generalization, outperforming Deep CNN models and conventional Ensemble learning techniques, as well as Shallow and Deep meta-learning Ensemble CNNs models. Radiologists can use the presented automatic Ensemble classification models to assist identify infected chest CT scans and save lives

AUGMENTED REALITY GAME THERAPY FOR CHILDREN WITH AUTISM SPECTRUM DISORDER

Abstract-This paper presents progress on treating children with Autism Spectrum Disorder (ASD) using Augmented Reality based games. The aim of these games is to enhance social interaction and hand-eye coordination in children with ASD thus easing them into becoming more comfortable around unfamiliar people. Colour detection and tracking and motion tracking concepts in augmented reality have been used to develop games for young children with ASD. The idea is that these games will encourage concentration and imagination from children through repetitive movement and visual feedback

Seepage Analysis Through and Under Hydraulic Structures Applying Finite Volume Method

In this paper, the seepage analysis through and underneath the hydraulic structures is studied at the same time without dividing the structure into parts, and then analyze each part individually. The analysis has been done using the finite volume method using rectangular elements. This method implemented on several types of structures and the comparison of the results is made with the one solved using finite element method. The comparison showed close results. The finite volume method has been implemented on non-rectangular structures. The present work studied the effect of heterogeneous foundations on the uplift pressure and exit gradients at the downstream and comparison with homogenous foundations. Also it studied the evaluation of effect of position and inclination of cut-offs at upstream or downstream of structures on uplift pressure and exit gradients at downstream. In addition, it studied the effect of impervious body inside the structure or foundation on uplift pressure and exit gradients at downstream

Impact of coronavirus disease 2019 (COVID-19) outbreak quarantine, isolation, and lockdown policies on mental health and suicide

The novel coronavirus disease (COVID-19) pandemic has made a huge impact on people\u27s physical and mental health, and it remains a cause of death for many all over the world. To prevent the spread of coronavirus infection, different types of public health measures (social isolation, quarantine, lockdowns, and curfews) have been imposed by governments. However, mental health experts warn that the prolonged lockdown, quarantine, or isolation will create a “second pandemic” with severe mental health issues and suicides. The quarantined or isolated people may suffer from various issues such as physical inactivity, mental health, economic and social problems. As with the SARS outbreak in 2003, many suicide cases have been reported in connection with this current COVID-19 pandemic lockdown due to various factors such as social stigma, alcohol withdrawal syndrome, fear of COVID infection, loneliness, and other mental health issues. This paper provides an overview of risk factors that can cause suicide and outlines possible solutions to prevent suicide in this current COVID-19 pandemic

A comparison of characteristics of periodic surface micro/nano structures generated via single laser beam direct writing and particle lens array parallel beam processing

Abstract Changing material surface micro/nanostructures using laser beam texturing is a valuable approach in wide applications such as control of cell/bacterial adhesion and proliferation, solar cells and optical metamaterials. Here, we report a comparison of the characteristics of surface micro/nanostructures produced using single beam laser direct writing and particle lens array parallel laser beam patterning. A Nd:YVO4 nanosecond pulsed laser at the wavelength of 532 nm was used in the laser direct writing method to texture the stainless steel surface submerged in water and in air with different scanning patterns. Changes in surface morphology, wettability, surface chemistry, and optical reflectivity were analyzed. In the particle lens array method, an excimer nanosecond laser at 248 nm wavelength was adopted to produce surface patterns on GeSbTe (GST) film coated on a polycarbonate substrate by splitting and focusing a single laser beam into millions of parallel breams. Single beam laser direct writing shows that the surface of high roughness and oxygen percentage content presented high wettability and low reflectivity characteristics. However, the controllability of the type of surface micro/nanopatterns is limited. The parallel laser beam processing using particle lens array allows rapid production of user designed periodic surface patterns at nanoscale overcoming the optical diffraction limit with a high degree of controllability. Controlling the uniformity of the particle lens array is a challenge

The influence of picosecond laser generated periodic structures on bacterial behaviour

The formation of a biofilm is preceded by bacterial retention and proliferation on a surface. Biofilm development on surfaces can cause numerous issues in terms of fouling and bacterial transmission and contamination. The design and fabrication of surfaces that prevent bacterial retention and biofilm formation may provide a potential solution to reduce bacterial fouling of surfaces. An EdgeWave, Nd:YVO4 picosecond laser was used to generate two periodic surface topographies on 316L stainless steel surfaces with and without fluoroalkylsilane (FAS) treatment. These were characterised using Optical Laser Microscopy (OLM), Scanning Electron Microscopy (SEM), contact angle measurements, and Energy Dispersive X-ray Spectroscopy (EDX). The surface wettability and retention of Escherichia coli bacteria on the laser generated surfaces were analysed over one month. Without chemical treatment, and with increasing the time to one month, the results showed that the wettability of laser treated surfaces was decreased as was subsequent bacterial retention. However, the control surface recorded the lowest number of adhered bacteria. After reducing the surface tension, the number of bacteria retention was decreased on all surfaces and one of laser generated surfaces which presented higher contact angle and lower surface tension components (CA = 132°, ΔGiwi = −85.26, γs = 13.81, γsLW = 13.37, and γs− = 0.13) recorded the minimal number of bacteria retention. The results showed that reducing the surface tension played an important role which reduced bacterial fouling

Ovarian germ cell tumors with rhabdomyosarcomatous components and later development of growing teratoma syndrome: a case report

<p>Abstract</p> <p>Introduction</p> <p>Development of a sarcomatous component in a germ cell tumor is an uncommon phenomenon. Most cases reported have a grim prognosis. Growing teratoma syndrome is also an uncommon phenomenon and occurs in approximately 2% to 7% of non seminomatous germ cell tumors and should be treated surgically.</p> <p>Case presentation</p> <p>We report the case of a 12-year-old Asian girl with an ovarian mixed germ cell tumor containing a rhabdomyosarcomatous component. She was treated with a germ cell tumor chemotherapy regimen and rhabdomyosarcoma-specific chemotherapy. Towards the end of her treatment, she developed a retroperitoneal mass that was increasing in size. It was completely resected, revealing a mature teratoma, consistent with growing teratoma syndrome. She is still in complete remission approximately three years after presentation.</p> <p>Conclusion</p> <p>The presence of rhabdomyosarcoma in a germ cell tumor should be treated by a combined chemotherapy regimen (for germ cell tumor and rhabdomyosarcoma). In addition, development of a mass during or after therapy with normal serum markers should raise the possibility of growing teratoma syndrome that should be treated surgically.</p