In this article, we present an evaluation of user acceptance of our innovative hand-gesture-based touchless sterile system for interaction with and control of a set of 3-dimensional digitized orthodontic study models using the Kinect motion-capture sensor (Microsoft, Redmond, Wash).
Skin detection has gained popularity and importance in the computer vision community. It is an essential step for important vision tasks such as the detection, tracking and recognition of face, segmentation of hand for gesture analysis, person identification, as well as video surveillance and filtering of objectionable web images. All these applications are based on the assumption that the regions of the human skin are already located. In the recent past, numerous techniques for skin colour modeling and recognition have been proposed. The aims of this paper are to compile the published pixel-based skin colour detection techniques to describe their key concepts and try to find out and summarize their advantages, disadvantages and characteristic features.
Storytelling is considered as an interactive social arts that uses word and
gestures to reveal the elements and images of a story while engaging the
listener's imagination. Multimedia based digital storytelling learning
approach provides interesting, interactive, engaging and multisensory
learning experience to children. Children explore new experience and
scenarios as new stories are being told. This study concentrates on
determining the best combination of elements for designing effective digital
storytelling applications specifically for the usage of dyslexic children.
Dyslexic children are known to have a common learning difficulty that can
cause problems with reading, writing, spelling and comprehension. These
applications are design with the objective to help in improving dyslexic
children ability in readings and comprehensions. Four elements were
derived from extensive literature studies. The elements are multimedia
components, multi-sensory instructional approach, emotional design and
games design. The relationship among all the elements were determine
and described in details as it will be used to contribute to the design and
development of the application in further works. The strength of this study
is it models the combinations of technology, psychology and instructional
approach as a support components for developing an effective digital story
telling learning application for dyslexic children.
Skin colour is an important visual cue for face detection, face recogmtlon, hand segmentation for gesture analysis and filtering of objectionable images. In this paper, the adaptive skin color detection model is proposed, based on two bivariate normal distribution models of the skin chromatic subspace, and on image segmentation using an automatic and adaptive multi-thresholding technique. Experimental results on images presenting a wide range of variations in lighting condition and background demonstrate the efficiency of the proposed skin-segmentation algorithm.
Wheelchair has been an important assistive device and the demand are ever rising because of the increasing physically handicapped and old age populations. The recent development in the robotics artificial intelligence extends vast scope for developing the more advanced and intelligent one to overcome limitations of the existing traditional wheelchairs. The prototype smart wheelchair were present on this paper using hardware implementation with the help of simple hand gesture which is comprises of an accelerometer mounted on the hand glove senses the tilt angle of the user hand movements and transmits control signal to the receiver mounted on wheelchair. This will interpret the movement accordingly required by user. The wheelchair control unit is developed by integration of ATMEGA328 microcontroller with Arduino UNO. The wheelchair is developed to allow peoples to move safely and put reliability in accomplishment of some important tasks in daily life.
Loss of the ability to speak or hear exerts psychological and social impacts on the affected persons due to the lack of proper communication. Multiple and systematic scholarly interventions that vary according to context have been implemented to overcome disability-related difficulties. Sign language recognition (SLR) systems based on sensory gloves are significant innovations that aim to procure data on the shape or movement of the human hand. Innovative technology for this matter is mainly restricted and dispersed. The available trends and gaps should be explored in this research approach to provide valuable insights into technological environments. Thus, a review is conducted to create a coherent taxonomy to describe the latest research divided into four main categories: development, framework, other hand gesture recognition, and reviews and surveys. Then, we conduct analyses of the glove systems for SLR device characteristics, develop a roadmap for technology evolution, discuss its limitations, and provide valuable insights into technological environments. This will help researchers to understand the current options and gaps in this area, thus contributing to this line of research.
Recently, the recognition of different facial gestures using facial neuromuscular activities has been proposed for human machine interfacing applications. Facial electromyograms (EMGs) analysis is a complicated field in biomedical signal processing where accuracy and low computational cost are significant concerns. In this paper, a very fast versatile elliptic basis function neural network (VEBFNN) was proposed to classify different facial gestures. The effectiveness of different facial EMG time-domain features was also explored to introduce the most discriminating.
Employee satnfaction surveys can provide the information needed to improved levek of productivity, job and loyalty. Management can identify the factors of job issues and provide solutions to improve the working environment. A cross sectional descriptive study on employee satisfaction among a health care district office’s staff was conducted in Perak in March - April 2006. A total of 19 staff were randomly picked and interviewed in the data collection process. Almost all understand the objectives of the administration unit (94%) and were satisfied with the management leadership’s style (78%- l 00%) . Majority agreed that their relationship with immediate superior and within the group was harmonious and professional (89%) and they preferred an open problem solving method in handling conflict (72 %). The most common type of incentive rewarded by the administration to express gratitude to their staff was certificate (56%); bonus and medal (33%); and informal gesture (28%). Majority (83%) were also satisfied by the method used to disseminate the information in their units. Majority agreed that the working environment in the administration unit were conducive (72%), their ideas were equally considered during decision making sessions (89%) and training opportunities were similarly given to them by the management (72%). This study revealed that employee satisfaction was determined by several factors such as management leadership's style, opportunity to contribute skills and idea; reward and incentive; and conducive king environment.
The medical system is facing the transformations with augmentation in the use of medical information systems, electronic records, smart, wearable devices, and handheld. The central nervous system function is to control the activities of the mind and the human body. Modern speedy development in medical and computational growth in the field of the central nervous system enables practitioners and researchers to extract and visualize insight from these systems. The function of augmented reality is to incorporate virtual and real objects, interactively running in a real-time and real environment. The role of augmented reality in the central nervous system becomes a thought-provoking task. Gesture interaction approach-based augmented reality in the central nervous system has enormous impending for reducing the care cost, quality refining of care, and waste and error reducing. To make this process smooth, it would be effective to present a comprehensive study report of the available state-of-the-art-work for enabling doctors and practitioners to easily use it in the decision making process. This comprehensive study will finally summarise the outputs of the published materials associate to gesture interaction-based augmented reality approach in the central nervous system. This research uses the protocol of systematic literature which systematically collects, analyses, and derives facts from the collected papers. The data collected range from the published materials for 10 years. 78 papers were selected and included papers based on the predefined inclusion, exclusion, and quality criteria. The study supports to identify the studies related to augmented reality in the nervous system, application of augmented reality in the nervous system, technique of augmented reality in the nervous system, and the gesture interaction approaches in the nervous system. The derivations from the studies show that there is certain amount of rise-up in yearly wise articles, and numerous studies exist, related to augmented reality and gestures interaction approaches to different systems of the human body, specifically to the nervous system. This research organises and summarises the existing associated work, which is in the form of published materials, and are related to augmented reality. This research will help the practitioners and researchers to sight most of the existing studies subjected to augmented reality-based gestures interaction approaches for the nervous system and then can eventually be followed as support in future for complex anatomy learning.