Many people around the world suffer from losing the ability to talk and hear with different levels of disabilities, caused by either a car or a work accident or some diseases. After losing communication, these people cannot do normal functions of normal life. Along with the aforementioned disabilities, those people may also have psychological effects. This paper introduces a technique to realize multiple sign language translation using a sensors-based glove and an Android smartphone for speech impaired people to communicate normally with people. The design of the hand talking system (HTS) was implemented with a minimum possible number of sensors and a capable sewing controller (Lilypad). The proposed HTS includes flex sensors, Arduino, smartphone, and accelerometer. The HTS uses an Android application programmed to store multi-language in the SQLite database and enables the user to interact with the system. The system provides talking with a letter formed words, or using the most frequently used words in daily communication by hand gesture. The HTS has achieved high accuracy obtained for American Sign Language and Arabic Sing Language which are about 98.26% and 99.33% respectively with an average accuracy of 98.795 for both Sign Languages.
A wheelchair control system based on Gyroscope of wearable tool can serve the disabled, especially in helping them move freely. The recent evolution of new technology means that unassisted, free movement has become possible. For this purpose, human–machine interface hands-free command of an electric-powered wheelchair can be achieved. In this paper, an electroencephalogram instrument, namely the EMOTIV Insight, was implemented in a human–computer interface to acquire the user’s head motion signals. The system can be operated based on the user’s head motions to carry out motion orders and control the motor of the wheelchair. The proposed system consists of an EMOTIV Insight brain-based gyroscope to sense head tilt, a DC motor driver to control wheelchair speed and directions, an eclectic-powered wheelchair, microcontroller, and laptop. We implemented the system in practice and tested it on smooth and rough surfaces in indoor/outdoor settings. The experimental results were greatly encouraging: disabled users were able to drive the wheelchair without any limitations. We obtained a significant average response time of 2 seconds. In addition, the system had accuracy, sensitivity, and specificity of 99%, 99.16%, and 98.83%, respectively.
The electroretinogram (ERG) is an electrophysiological recording method that measures the retinal electrical potential. The electrical reaction is quantified by electrical interaction of the indicator electrode with the cornea or at various levels inside the retina. However, such ERG systems suffer from certain limitations and challenges, such as high cost, low a/b-wave amplitude, and the outcomes do not provide any information about patients. In this work, we designed and implemented a real-time prototype for an ERG system for measuring eye waves via diode-transistor logic (DTL)- electrode and AD624AD-model. In addition, a graphical user interface (GUI) via virtual instrument engineering workbench (LabVIEW) was used. The developed system achieved high amplitude for ERG a/b-waves of about 100 and 700 mV. In terms of a/b-waves in the system, the findings show that this study has good results for optimizing the measurement of ERG signals. The method showed satisfactory accuracy of about 92.5% for 10 participants aged 20-60 years and comprising both genders
<p>There are many direct and indirect methods of measuring the volumetric ratioof red blood cells relative to sample size and total blood, but the manual carcinogenic method remains the most stable and least expensive method despite the possibility of human error.The ratio percent of the packed red blood cell volume to the total volume of the blood sample is known as the packed cell volume (PCV). Our efforts were directed at finding a precise and economic method for PCV determination. There by, we designed a simple device consisting of a digital camera that is connected to a computer which uses a specific MATLAB program to process the blood images. As a result,the image can be read and the PCV can be calculated using a special code system. This new measuring system provides the capabilities and advantagesto frequently comment on measured PCV with normal or abnormal, in comparison with normal values of PCV, which are stored in the computer. Our measurement method provides accurate results compared to the ruler results to alleviate the effort of clearing the hepatitis C virus from the blood (PCV). This system enables a swift and simple sample analysis and PCV identification.</p>
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