Citation

Theodorou P, Tsiligkos K, Meliones A, Filios C. Sensors (Basel) 2022; 23(1): e367.

Copyright

(Copyright © 2022, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s23010367

PMID

36616964

Abstract

Training blind and visually impaired individuals is an important but often neglected aspect of Assistive Technology solutions (ATs) that can benefit from systems utilizing multiple sensors and hardware devices. Training serves a dual purpose as it not only enables the target group to effectively utilize the ATs but, also, helps in improving their low acceptance rate. In this paper, we present the design, implementation, and validation of a smartphone-based training application. It is a form of immersive system that enables users to learn the features of an outdoor blind pedestrian navigation application and, simultaneously, to help them develop long-term Orientation and Mobility (O&M) skills. The system consists of an Android application leveraging, as data sources, an external high-accuracy GPS sensor for real-time pedestrian mobility tracking, a second custom-made device attached to traffic lights for identifying their status, and an ultra-sonic sensor for detecting near-field obstacles on the navigation path of the users. The training version running as an Android application employs route simulation with audio and haptic feedback, is functionally equivalent to the main application, and was used in the context of specially designed user-centered training sessions. A Usability and User Experience (UX) evaluation revealed the positive attitude of the users towards the training version as well as their satisfaction with the skills acquired during their training sessions (SUS = 69.1, UEQ+ = 1.53). Further confirming the positive attitude was the conduct of a Recursive Neural Network (RNN)-based sentiment analysis on user responses with a score of 3 on a scale from 0 to 4. Finally, we conclude with the lessons learned and the proposal of general design guidelines concerning the observed lack of accessibility and non-universal interfaces.

Language: en

Keywords

mobile sensor-based applications; sentiment analysis; usability; user experience