Enhancing Effective Teaching and Learning of ICT in the Schools for the Blind in Ghana.

The paper examines role of the Information and Communication Technology (ICT) in Special Education in Ghana. Taking the relevant literature as the guiding principle, the paper addresses the opportunities, barriers and challenges posed by the integration of Assistive Technologies devices in schools for the blind and visually impaired in the teaching and learning process. The paper shows that inadequacies of teachers’ knowledge and skills in Assistive Technologies coupled with lack of these technologies are some of the greatest hindrances to effective teaching in the schools for the Blind in Ghana. Educators and policy makers acknowledge Evidence-Based Teaching as one of the most effective strategies for teaching the blind and the visually impaired.The paper highlights that effective integration of Assistive Technologies into schools will help bridge the digital gap between the blind and the sighted in Ghana

Enhancing Effective Teaching and Learning of ICT in the Schools for the Blind in Ghana

The paper examines role of the Information and Communication Technology (ICT) in Special Education in Ghana. Taking the relevant literature as the guiding principle, the paper addresses the opportunities, barriers and challenges posed by the integration of Assistive Technologies devices in schools for the blind and visually impaired in the teaching and learning process. The paper shows that inadequacies of teachers’ knowledge and skills in Assistive Technologies coupled with lack of these technologies are some of the greatest hindrances to effective teaching in the schools for the Blind in Ghana. Educators and policy makers acknowledge Evidence-Based Teaching as one of the most effective strategies for teaching the blind and the visually impaired.The paper highlights that effective integration of Assistive Technologies into schools will help bridge the digital gap between the blind and the sighted in Ghana

Blindness and visual impairment in Central Europe

Purpose To assess the prevalence and causes of visual impairment and blindness in a Central European country. The findings may have implications for the planning of further research and development of therapies in order to prevent blindness. Setting Department of Ophthalmology, Medical University of Graz, Austria. Design Retrospective, epidemiological study. Methods The database of the Main Confederation of Austrian Social Insurances was searched for patients with visual impairment, legal blindness or deaf-blindness. This database gathers data from patients of all insurance providers in the country who receive care due to visual impairment and blindness. To determine the prevalence of these conditions, the number of all entries recorded in February 2019 was evaluated. Additionally, all new entries between (January 1st,) 2017, and (December 31st,) 2018, were analysed for distinct characteristics, such as sex, the cause of blindness/visual impairment, and age. Since health care allowances can provide a considerable source of income (459.90€-936.90€ per month), good coverage of practically all patients who are blind and visually impaired in the country can be assumed. Results On February 2nd, 2019, 17,730 patients with visual impairments, blindness or deaf-blindness were registered in Austria, resulting in a prevalence of these diagnoses of 0.2% in the country. During the observational period from 2017 to 2018, 4040 persons met the inclusion criteria. Of these, 2877 were female (65.3%), and 1527 were male (34.7%). The mean age was 75.7 ± 18.0 years (median 82). Most patients (n = 3675, 83.4%) were of retirement age, while 729 (16.6%) were working-age adults or minors. In total, an incidence of 25.0 (95% confidence limit (CL) 24.3–25.8) per 100,000 person-years was observed from 2017 to 2018. A higher incidence was observed for females (32.2, 95% CL 31.0–33.3) than for males (17.7, 95% CL 16.8–18.5). Incidences where higher for males in lower age groups (e.g. 10–14 years: rate ratio RR = 2.7, 95% CL 1.1–6.8), and higher for females in higher age groups (e.g. 70–74 years: RR = 0.6, 95% CL 0.5–0.8). In total, the most frequent diagnoses were macular degeneration (1075 persons, 24.4%), other retinal disorders (493 persons, 11.2%) and inherited retinal and choroidal diseases (IRDs) (186 persons, 4.2%). Persons with IRDs were significantly younger compared to persons with macular degeneration or retinal disorders (IRDs: median 57, range 2–96 vs 83, 5–98 and 82, 1–98 years, p<0.001). For persons of retirement age, macular degeneration, other retinal disorders and glaucoma were the three most frequent diagnoses. In contrast, among working-aged adults and children, IRDs were the leading cause of visual impairment and blindness (103 persons, 14.1%). Conclusion These data show that IRDs are the leading cause of blindness and visual impairment in working-aged persons and children in Austria. Thus, these findings suggest to draw attention to enhance further research in the fields of emerging therapies for IRDs.

Outdoor Localization Using BLE RSSI and Accessible Pedestrian Signals for the Visually Impaired at Intersections

One of the major challenges for blind and visually impaired (BVI) people is traveling safely to cross intersections on foot. Many countries are now generating audible signals at crossings for visually impaired people to help with this problem. However, these accessible pedestrian signals can result in confusion for visually impaired people as they do not know which signal must be interpreted for traveling multiple crosses in complex road architecture. To solve this problem, we propose an assistive system called CAS (Crossing Assistance System) which extends the principle of the BLE (Bluetooth Low Energy) RSSI (Received Signal Strength Indicator) signal for outdoor and indoor location tracking and overcomes the intrinsic limitation of outdoor noise to enable us to locate the user effectively. We installed the system on a real-world intersection and collected a set of data for demonstrating the feasibility of outdoor RSSI tracking in a series of two studies. In the first study, our goal was to show the feasibility of using outdoor RSSI on the localization of four zones. We used a k-nearest neighbors (kNN) method and showed it led to 99.8% accuracy. In the second study, we extended our work to a more complex setup with nine zones, evaluated both the kNN and an additional method, a Support Vector Machine (SVM) with various RSSI features for classification. We found that the SVM performed best using the RSSI average, standard deviation, median, interquartile range (IQR) of the RSSI over a 5 s window. The best method can localize people with 97.7% accuracy. We conclude this paper by discussing how our system can impact navigation for BVI users in outdoor and indoor setups and what are the implications of these findings on the design of both wearable and traffic assistive technology for blind pedestrian navigation.

Mesh Network of eHealth Intelligent Agents for Visually Impaired and Blind People

Smart assistive devices for blind and visually impaired (B&VI) people are of high interest today since wearable IoT hardware became available for a wide range of users. In the first project, the Raspberry Pi 3 B board measures a distance to the nearest obstacle via ultrasonic sensor HC-SR04 and recognizes human faces by Pi camera, OpenCV library, and Adam Geitgey module. Objects are found by Bluetooth devices of classes 1-3 and iBeacons. Intelligent eHealth agents cooperate with one another in a smart city mesh network via MQTT and BLE protocols. In the second project, B&VIs are supported to play golf. Golf flagsticks have sound marking devices with a buzzer, NodeMcu Lua ESP8266 ESP-12 WiFi board, and WiFi remote control. In the third project, an assistive device supports the orientation of B&VIs by measuring the distance to obstacles via Arduino Uno and HC-SR04. The distance is pronounced through headphones. In the fourth project, the soft-/hardware complex uses Raspberry Pi 3 B and Bytereal iBeacon fingerprinting to uniquely identify the B&VI location at industrial facilities.

Strategies of planning online scientific projects for blind and visually impaired students

The paper describes distance learning opportunities for blind and visually impaired students. The research aims at analyzing various tools and techniques that are necessary for their participation in online scientific projects and conferences. Methodology includes analysis of pedagogical studies, the survey carried out during International Conference for Students at Samara State Technical University, examination of educational activities performed for blind and visually impaired students all over the world, in particular the experience of American Foundation for the Blind. The findings show that distance learning programmes for blind and visually impaired people are becoming popular in many countries, but in Russia there are only a few of them. The authors prove the necessity of doing research in this sphere. It is recommended that more distance learning opportunities are created for such students at Russian universities. The analysis shows that it is even easier to plan the inclusion of blind and visually impaired students in the online scientific events that are not new and have already been held for wider public. The authors conclude that it is essential to adapt the existing system of distance learning using special tools and techniques, which are described in the article. These are accessible platforms, software used with assistive technologies, keyboard controls, audio description, smartphone apps, etc. Special emphasis is laid upon planning webinars for blind and low vision participants. This research can serve as a guide for making online scientific events accessible for all people.

Features of Primary Ocular Disability in the Krasnodar Region in 2016–2018

Purpose: to study the state and dynamics of changes in primary ocular disability in the period 2016–2018 by nosological forms. A complete retrospective study was made based on the data of the MSE (medical and social expertise) Bureau’s reporting documents. The following indicators of primary disability (per 10 thousand population) were registered from 2016 till 2018: among the adult population (18 years and older) 69,0–70,7–68,6 respectively; among the able-bodied population 42,8–44,1–41,1 respectively; among the population of retirement age — 125,1–126,4–124,6 accordingly. In the structure of primary disability of the adult population by severity for the period 2016–2018, the dynamics recorded an increase in the proportion of 1 group and 3 group with a decrease in the share of disability of 2 group. In the nosological structure of primary disability of the adult population in 2016–2017–2018, eye diseases account for 3 %, 3 % and 3.2 %, respectively, of all first recognized as disabled. There has been an increase in first-time applicants to the MSE Bureau. In the nosological structure of primary disability, the percentage of glaucoma patients over the past period is 47–33–32.5 % of the total number of primary disability for eye diseases, which determines the 1st rank. There is a progressive increase in the number of people with disabilities due to glaucoma of group 1 and group 2 throughout the study period. In the nosological structure of primary disability for 2016–2018 the percentage of patients with retinal diseases is 25–23–23.8 % of the total number of primary disability for eye diseases, which corresponds to the 2nd rank. There is a progressive increase in the number of disabled people in group 2. A low proportion of persons of working age in the structure of primary ocular disability was noted. A consistently high share of primary disability and a progressive increase in severe disability combined with an increase in persons of retirement age in the Krasnodar region forms an unfavorable forecast for an increase in the number of blind and visually impaired residents of the region.

Intelligence Eye for Blinds and Visually Impaired by Using Region-Based Convolutional Neural Network (R-CNN)

Intelligence Eye is an Android based mobile application developed to help blind and visually impaired users to detect light and objects. Intelligence Eye used Region-based Convolutional Neural Networks (R-CNN) to recognize objects in the object recognition module and a vibration feedback is provided according to the light value in the light detection module. A voice guidance is provided in the application to guide the users and announce the result of the object recognition. TensorFlow Lite is used to train the neural network model for object recognition in conjunction with extensible markup language (XML) and Java in Android Studio for the programming language. For future works, improvements can be made to enhance the functionality of the Intelligence Eye application by increasing the object detection capacity in the object recognition module, add menu settings for vibration intensity in light detection module and support multiple languages for the voice guidance.