Search Results (9)

We examined discrimination accuracy of vibrotactile patterns on the upper forearm using a 2 × 3 array of voice coil actuators to generate 100 Hz vibrotactile stimulation. We evaluated participants’ ability to recognize distinct vibrotactile patterns presented both simultaneously (1000 ms) and sequentially (500 ms with a 450 ms interval). Recognition accuracy was significantly higher for sequential (93.24%) than for simultaneous presentation (26.15%). Patterns using 2–3 actuators were recognized more accurately than those using 4–5 actuators. During sequential presentation, there were primacy and recency effects; accuracy was higher for the initial and final stimulations in a sequence. Over time, participants also demonstrated a learning effect, becoming more adept at recognizing and interpreting vibrotactile patterns. This underscores the potential for skill development and emphasizes the value of training for wearable vibrotactile devices. We discuss the implications of these findings for the design of tactile communication devices and wearable technology. Full article

In recent years, research on new technologies for expressing and exchanging information through tactile vibration has been the focus of researches. In this paper, by choosing a suitable coding scheme and a vibrating motor arrangement, we designed a device to express semantic information through vibrotactile. Three types of experiments were designed to test the usability of the encoding scheme and the device. Firstly, the vibration intensity was experimented when designing the encoding scheme, and the results showed that the encoding scheme was better with Braille units of 0.2 and 0.3 vibration intensities. In addition, the learning experiment and sentence recognition accuracy experiment were carried out to verify the usability of the device. The learning experiment results show that subjects were able to memorize Braille characters with an accuracy more than 90%, and to recognize a Chinese character (consisting of two Braille cells) with an average of 90.8% accuracy. The sentence recognition accuracy test experiment results show that the average recognition rate of the three poems used for the test was 93.33%. The device can be used for semantic information expression and touch-reading of Braille, and it can realize the reading experience of paper Braille. Full article

Providing access to and the protection of cultural goods—intangible and tangible heritage—is carried out primarily by institutions such as museums, galleries or local cultural centres where temporary exhibitions are shown. The international community also attempts to protect architectural objects or entire urban layouts, raising their status by inscribing them on the UNESCO World Heritage List. Contemporary museums, however, are not properly prepared to make museum exhibits available to the blind and visually impaired, which is confirmed by both the literature studies on the subject and the occasional solutions that are put in place. The development of various computer graphics technologies allows for the digitisation of cultural heritage objects by 3D scanning. Such a record, after processing, can be used to create virtual museums accessible via computer networks, as well as to make copies of objects by 3D printing. This article presents an example of the use of scanning, modelling and 3D printing to prepare prototypes of copies of museum objects from the Silk Road area, dedicated to blind people and to be recognised by touch. The surface of an object has information about it written in Braille before the copy-making process is initiated. The results of the pilot studies carried out on a group of people with simulated visual impairment and on a person who is blind from birth indicate that 3D models printed on 3D replicators with the fused filament fabrication technology are useful for sharing cultural heritage objects. The models are light—thanks to which they can be freely manipulated, as well as having the appropriate smoothness—which enables the recognition of decorative details present on them, as well as reading texts in Braille. Integrating a copy of an exhibit with a description about it in Braille into one 3D object is an innovative solution that should contribute to a better access to cultural goods for the blind. Full article

According to the World Health Organization, 2.2 billion people globally have some vision impairment. Blind and vision impairment children can undergo poor motor, language, and cognitive evolution, bringing lower levels of educational success. Our proposal aims to design and develop a one-character refreshable braille display that is affordable and easy to use through the Internet of Things (IoT) technology. Reading is essential to acquire knowledge by allowing an affordable form of reading based on braille, a handy tool for teaching and training blind and visually impaired people can be reached. Full article

Recent advances in machine and deep learning algorithms and enhanced computational capabilities have revolutionized healthcare and medicine. Nowadays, research on assistive technology has benefited from such advances in creating visual substitution for visual impairment. Several obstacles exist for people with visual impairment in reading printed text which is normally substituted with a pattern-based display known as Braille. Over the past decade, more wearable and embedded assistive devices and solutions were created for people with visual impairment to facilitate the reading of texts. However, assistive tools for comprehending the embedded meaning in images or objects are still limited. In this paper, we present a Deep Learning approach for people with visual impairment that addresses the aforementioned issue with a voice-based form to represent and illustrate images embedded in printed texts. The proposed system is divided into three phases: collecting input images, extracting features for training the deep learning model, and evaluating performance. The proposed approach leverages deep learning algorithms; namely, Convolutional Neural Network (CNN), Long Short Term Memory (LSTM), for extracting salient features, captioning images, and converting written text to speech. The Convolution Neural Network (CNN) is implemented for detecting features from the printed image and its associated caption. The Long Short-Term Memory (LSTM) network is used as a captioning tool to describe the detected text from images. The identified captions and detected text is converted into voice message to the user via Text-To-Speech API. The proposed CNN-LSTM model is investigated using various network architectures, namely, GoogleNet, AlexNet, ResNet, SqueezeNet, and VGG16. The empirical results conclude that the CNN-LSTM based training model with ResNet architecture achieved the highest prediction accuracy of an image caption of 83%. Full article

Braille is used as a mode of communication all over the world. Technological advancements are transforming the way Braille is read and written. This study developed an English Braille pattern identification system using robust machine learning techniques using the English Braille Grade-1 dataset. English Braille Grade-1 dataset was collected using a touchscreen device from visually impaired students of the National Special Education School Muzaffarabad. For better visualization, the dataset was divided into two classes as class 1 (1–13) (a–m) and class 2 (14–26) (n–z) using 26 Braille English characters. A position-free braille text entry method was used to generate synthetic data. N = 2512 cases were included in the final dataset. Support Vector Machine (SVM), Decision Trees (DT) and K-Nearest Neighbor (KNN) with Reconstruction Independent Component Analysis (RICA) and PCA-based feature extraction methods were used for Braille to English character recognition. Compared to PCA, Random Forest (RF) algorithm and Sequential methods, better results were achieved using the RICA-based feature extraction method. The evaluation metrics used were the True Positive Rate (TPR), True Negative Rate (TNR), Positive Predictive Value (PPV), Negative Predictive Value (NPV), False Positive Rate (FPR), Total Accuracy, Area Under the Receiver Operating Curve (AUC) and F1-Score. A statistical test was also performed to justify the significance of the results. Full article

We hypothesized that age-related changes in sensory function might be reflected by a modulation of the blood flow response associated with tactile sensation. The aim of the present study was to clarify how the blood flow response of the fingers during concentrated finger perception is affected by aging. We measured the tactile-pressure threshold of the distal palmar pad of the index finger and skin blood flow in the finger (SBF) during Braille reading performed under blind conditions in young (n = 27) and older (n = 37) subjects. As a result, the tactile-pressure threshold was higher in older subjects (2.99 ± 0.37 log₁₀ 0.1 mg) than in young subjects (2.76 ± 0.24 log₁₀ 0.1 mg) (p < 0.01). On the other hand, the SBF response was markedly smaller in older subjects (−4.9 ± 7.0%) than in young subjects (−25.8 ± 15.4%) (p < 0.01). Moreover, the peak response arrival times to Braille reading in older and young subjects were 12.5 ± 3.1 s and 8.8 ± 3.6 s, respectively (p < 0.01). A decline in tactile sensitivity occurs with aging. Blood flow responses associated with tactile sensation are also affected by aging, as represented by a decrease in blood flow and a delay in the reaction time. Full article

Assistive braille technology has existed for many years with the purpose of aiding the blind in performing common tasks such as reading, writing, and communicating with others. Such technologies are aimed towards helping those who are visually impaired to better adapt to the visual world. However, an obvious gap exists in current technology when it comes to symmetric two-way communication between the blind and non-blind, as little technology allows non-blind individuals to understand the braille system. This research presents a novel approach to convert images of braille into English text by employing a convolutional neural network (CNN) model and a ratio character segmentation algorithm (RCSA). Further, a new dataset was constructed, containing a total of 26,724 labeled braille images, which consists of 37 braille symbols that correspond to 71 different English characters, including the alphabet, punctuation, and numbers. The performance of the CNN model yielded a prediction accuracy of 98.73% on the test set. The functionality performance of this artificial intelligence (AI) based recognition system could be tested through accessible user interfaces in the future. Full article

Visual impairments cause very limited and low vision, leading to difficulties in processing information such as obstacles, objects, multimedia contents (e.g., video, photographs, and paintings), and reading in outdoor and indoor environments. Therefore, there are assistive devices and aids for visually impaired (VI) people. In general, such devices provide guidance or some supportive information that can be used along with guide dogs, walking canes, and braille devices. However, these devices have functional limitations; for example, they cannot help in the processing of multimedia contents such as images and videos. Additionally, most of the available braille displays for the VI represent the text as a single line with several braille cells. Although these devices are sufficient to read and understand text, they have difficulty in converting multimedia contents or massive text contents to braille. This paper describes a methodology to effectively convert multimedia contents to braille using 2D braille display. Furthermore, this research also proposes the transformation of Digital Accessible Information SYstem (DAISY) and electronic publication (EPUB) formats into 2D braille display. In addition, it introduces interesting research considering efficient communication for the VI. Thus, this study proposes an eBook reader application for DAISY and EPUB formats, which can correctly render and display text, images, audios, and videos on a 2D multiarray braille display. This approach is expected to provide better braille service for the VI when implemented and verified in real-time. Full article