A CNN-Based Wearable Assistive System for Visually Impaired People Walking Outdoors

In this study, we propose an assistive system for helping visually impaired people walk outdoors. This assistive system contains an embedded system—Jetson AGX Xavier (manufacture by Nvidia in Santa Clara, CA, USA) and a binocular depth camera—ZED 2 (manufacture by Stereolabs in San Francisco, CA, USA). Based on the CNN neural network FAST-SCNN and the depth map obtained by the ZED 2, the image of the environment in front of the visually impaired user is split into seven equal divisions. A walkability confidence value for each division is computed, and a voice prompt is played to guide the user toward the most appropriate direction such that the visually impaired user can navigate a safe path on the sidewalk, avoid any obstacles, or walk on the crosswalk safely. Furthermore, the obstacle in front of the user is identified by the network YOLOv5s proposed by Jocher, G. et al. Finally, we provided the proposed assistive system to a visually impaired person and experimented around an MRT station in Taiwan. The visually impaired person indicated that the proposed system indeed helped him feel safer when walking outdoors. The experiment also verified that the system could effectively guide the visually impaired person walking safely on the sidewalk and crosswalks.

Generation of Gait Events with a FSR Based Cane Handle

Gait analysis has many applications, and specifically can improve the control of prosthesis, exoskeletons, or Functional Electrical Stimulation systems. The use of canes is common to complement the assistance in these cases, and the synergy between upper and lower limbs can be exploited to obtain information about the gait. This is interesting especially in the case of unilateral assistance, for instance in the case of one side lower limb exoskeletons. If the cane is instrumented, it can hold sensors that otherwise should be attached to the body of the impaired user. This can ease the use of the assistive system in daily life as well as its acceptance. Moreover, Force Sensing Resistors (FSRs) are common in gait phase detection systems, and force sensors are also common in user intention detection. Therefore, a cane that incorporates FSRs on the handle can take advantage from the direct interface with the human and provide valuable information to implement real-time control. This is done in this paper, and the results confirm that many events are detected from variables derived from the readings of the FSRs that provide rich information about gait. However, a large inter-subject variability points to the need of tailored control systems.

Long Multi-Stage Training for a Motor-Impaired User in a BCI Competition

In a Mental Imagery Brain-Computer Interface the user has to perform a specific mental task that generates electroencephalography (EEG) components, which can be translated in commands to control a BCI system. The development of a high-performance MI-BCI requires a long training, lasting several weeks or months, in order to improve the ability of the user to manage his/her mental tasks. This works aims to present the design of a MI-BCI combining mental imaginary and cognitive tasks for a severely motor impaired user, involved in the BCI race of the Cybathlon event, a competition of people with severe motor disability. In the BCI-race, the user becomes a pilot in a virtual race game against up to three other pilots, in which each pilot has to control his/her virtual car by his/her mental tasks. We present all the procedures followed to realize an effective MI-BCI, from the user's first contact with a BCI technology to actually controlling a video-game through her EEG. We defined a multi-stage user-centered training protocol in order to successfully control a BCI, even in a stressful situation, such as that of a competition. We put a specific focus on the human aspects that influenced the long training phase of the system and the participation to the competition.

Uitsiton: wearable for mobility of the visually impaired

This article explains the development of the Uitsiton system, capable of detecting obstacles to alert visually impaired users, increasing their mobility and confidence when moving. Uitsiton is made up of a portable electronic device (wearable) and a mobile application (App) that operates under the Android platform. The wearable is integrated into a vest-like garment. It is used to compute the approximate distance between the visually impaired user and the obstacles that they can find in their path. The wearable covers a range of 180 degrees vertically and horizontally with respect to the center of the torso, and reaches a maximum distance of 120 cm. The App works synchronously with the wearable, it receives a series of data corresponding to the measurements of the distance between the user and the obstacle, and it triggers a sound pattern and a vibration pattern according to the proximity of the obstacle.

MAGIC-I as Assistance for the Visually Impaired People

Background: According to the WHO report, around 4.07% of the world's population is visually impaired. About 90% of the visually impaired users live in the lower economic strata. In the fast moving technology, most of the invention misses the need of these people. Mainly the technologies were designed for mainstream people; visually impaired people always find an inability to access it. This inability arises primarily for reasons such as cost, for example, Perkins Brailler costs 80-248 dollars for the simple purpose of Braille input. Another major reason is the hassle of carrying the big equipment. Objective: Keeping all this in mind and making technology as their best friends, MAGIC-1 has been designed. The goal is to provide a solution in terms of an application, which helps the visually impaired user in their daily life activities. Method: The proposed solution assists visually impaired users through smart phone technology. If visually impaired users ever wished to have a touched guide into a smart phone, MAGIC-1 has the solution that consolidates all the important features in their daily activities. Results: The performance of the solution as a whole and its individual features in terms of usability, utility and other metrics, etc. has been tested with sample visually impaired users. Moreover, their performances in term of Errors per Word and Words per Minute have been observed. Conclusion: MAGIC-I, the proposed solution works as an assistant of visually impaired users to overcome their daily struggles and stay more connected to the world. A visually impaired user can communicate via their mobile devices with features like eyes free texting using braille, voice calling etc. They can easily take help in an emergency situation with the options of SOS emergency calling and video assistance.

Capacitive Touch Sensitive Vibro-Haptic Typing Training System for the Visually Impaired

The proposed system implements a vibro-haptic glove device which works in tandem to a customized computer keyboard with capacitive touch sensitivity, facilitating a fast-paced typing method for the visually impaired. A normal keyboard is retro-fitted with a “capacitive sense” membrane that activates on human touch, along with a pair of fingerless haptic gloves with vibrators on each finger and a pair of Bluetooth earphones. The visually impaired user receives audible and haptic cues facilitating learning to type the correct key using the right finger on the computer keyboard. This utilizes the Passive-Haptic-Learning (PHL) paradigm for fast paced multisensory learning. A group of blind students were chosen and trained on this system for one month. There were pre and post training assessments conducted, and their scores compared. The findings showcased positive results.