A Review Paper on Smart Glove - Converts Gestures into Speech and Text

Generally people with hearing problem and speech disability use sign language based on hand gestures with specific motion to represent the language, they are communicating. Smart glove is an electronic device that translates sign language into text or speech in order to make the communication feasible between the mute communities with the general public. This glove translates the sign language gestures according to the American Sign Language Standard. This glove has been implemented with the help of flex sensors, accelerometer, microcontroller (Arduino Leonardo) and the Bluetooth chip. It Is a wireless data glove which is normal cloth driving glove fitted with flex sensors along the length of each finger

Hand Gesture Recognition System Using Histogram and Neural Network

In this paper, consider the problem facing by distance between hand and the web cam and corresponding image noise in a Hand gesture recognition for human computer interaction (HCI) using a web cam.In this paper a survey of various recent hand gesture recognition systems background information is presented, along with key issues and major challenges of hand gesture recognition system are presented. In this paper consider histogram and neural network approaches for hand detection. At the end of this paper focus on different hand gesture approaches, algorithm, prototype model, technologies and its applications. The present approaches can be mainly divided into Data-Glove Based, Computer Vision Based approach and Drawing gesture. Hand gesture is a method of non-verbal communication for human beings. Using gesture applications human can interact with computer efficiently without any input devices. DOI: 10.17762/ijritcc2321-8169.160413

Requirement analysis and sensor specifications – First version

In this first version of the deliverable, we make the following contributions: to design the WEKIT capturing platform and the associated experience capturing API, we use a methodology for system engineering that is relevant for different domains such as: aviation, space, and medical and different professions such as: technicians, astronauts, and medical staff. Furthermore, in the methodology, we explore the system engineering process and how it can be used in the project to support the different work packages and more importantly the different deliverables that will follow the current. Next, we provide a mapping of high level functions or tasks (associated with experience transfer from expert to trainee) to low level functions such as: gaze, voice, video, body posture, hand gestures, bio-signals, fatigue levels, and location of the user in the environment. In addition, we link the low level functions to their associated sensors. Moreover, we provide a brief overview of the state-of-the-art sensors in terms of their technical specifications, possible limitations, standards, and platforms. We outline a set of recommendations pertaining to the sensors that are most relevant for the WEKIT project taking into consideration the environmental, technical and human factors described in other deliverables. We recommend Microsoft Hololens (for Augmented reality glasses), MyndBand and Neurosky chipset (for EEG), Microsoft Kinect and Lumo Lift (for body posture tracking), and Leapmotion, Intel RealSense and Myo armband (for hand gesture tracking). For eye tracking, an existing eye-tracking system can be customised to complement the augmented reality glasses, and built-in microphone of the augmented reality glasses can capture the expert’s voice. We propose a modular approach for the design of the WEKIT experience capturing system, and recommend that the capturing system should have sufficient storage or transmission capabilities. Finally, we highlight common issues associated with the use of different sensors. We consider that the set of recommendations can be useful for the design and integration of the WEKIT capturing platform and the WEKIT experience capturing API to expedite the time required to select the combination of sensors which will be used in the first prototype.WEKI

Novos paradigmas de interface de utilizador para aplicações na área da saúde

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)As instituições de saúde vivem atualmente num ambiente de crescente densidade de informação, sendo esta uma área de intensa transferência eletrónica de dados. Como resultado, tem-se recorrido cada vez mais às interfaces de utilizador como forma de auxilio no processamento de dados. Tratando-se de uma questão inovadora, o surgimento de novas tecnologias de informação e comunicação tem sido um motor para o desenvolvimento de novos tipos de interfaces de utilizador. Com o aumento do volume de informação, tem surgido problemas no que diz respeito ao seu processamento. Cada vez mais são exigidos que os serviços sejam prestados com maior eficiência, implicando maior rapidez na obtenção de dados. É neste contexto que surge a necessidade de direcionar os novos avanços no campo da saúde, tendo como linha orientadora a busca de um serviço mais eficiente e com maior qualidade. Neste sentido surge a necessidade de optimização dos processos de acesso e utilização dessa informação, alterando a forma como a informação sobre os utentes é obtida. É, essencialmente, nestes pontos que se foca esta dissertação. Adicionalmente, e do ponto de vista funcional, pode dizer-se que estes desenvolvimentos apresentam características favoráveis à prevenção e ao controlo de infeções hospitalares, reduzindo a necessidade de contato direto entre os objetos, o que leva, à diminuição da propagação das ditas infeções. Com a concretização deste estudo procura-se avaliar as potencialidades do reconhecimento gestual aplicado às interfaces de utilizador, na sua implementação na área específica da saúde. Paralelamente desenvolveu-se um protótipo destinado aos utentes que frequentem as instituições de saúde. Este protótipo teve como objetivo a validação das interfaces de utilizador analisadas, considerando a utilização das tecnologias recentemente introduzidas no mercado. Foi dada especial atenção a interfaces de utilizador sem contato entre dispositivos e utilizadores (e.g. utilizando a tecnologia do Kinect da Microsoft). No final é apresentado um estudo estatístico relativo à avaliação por parte dos utilizadores da interface do protótipo desenvolvido, onde se conclui a funcionalidade da utilização de gestos se revelou intuitiva e de fácil execução.Health institutions are currently living in an environment of increasing information density, being considered an area of intense electronic transfer of data. As a result, there has been an increasing use of the user interfaces in order to aid data processing. Since this is a matter innovative, the emergence of new information and communication technologies has been a catalyst for the development of new types of user interfaces. With the increasing volume of information, problems have arisen with regard to their processing. Increasingly it is being required the services to be delivered with more effectiveness resulting in faster data retrieval. It’s in this context that arises the need to drive new advances in healthcare, having as a guideline the search for a service with more efficient and higher quality. In this way occurs the need to optimize the process of access and use of this information, changing the way that the patient’s information is obtained. This dissertation focuses essentially on these points. Additionally it can be said that these developments have characteristics favourable to the prevention and control of hospital infections, reducing the need for direct contact with the objects, which leads to decreased spread of infections said. This study aim to evaluate the potential of gesture recognition applied to the user interfaces implemented specifically in the healthcare area. Alongside it was developed a prototype intended to the patients that usually attend to healthcare institutions. The goal of this prototype is to validate the user interfaces proposals, considering the use of technology recently introduced on the market. It was given special attention to user interfaces without contact between users and devices (e.g. using the technology of the Microsoft Kinect). At the end it is presented a statistical study on the evaluation of the user interface prototype by users, in which it is proved that the functionality of using gestures is intuitive and easy to perform