Konstantinos Filios

Mr. Konstantinos Filios

University of Piraeus, Piraeus, Attikí, Greece

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
16 June 2022 in Sensors
Verified
Journal Article
Open access
PDF file
Paraskevi TheodorouParaskevi Theodorou
Paraskevi Theodorou
KTKleomenis Tsiligkos
Kleomenis Tsiligkos
Apostolos MelionesApostolos Meliones
Apostolos Meliones
KFKonstantinos Filios
Konstantinos Filios
Navigation assistive technologies have been designed to support the mobility of people who are blind and visually impaired during independent navigation by providing sensory augmentation, spatial information and general awareness of their environment. This paper focuses on the extended Usability and User Experience (UX) evaluation of BlindRouteVision, an outdoor navigation smartphone application that tries to efficiently solve problems related to the pedestrian navigation of visually impaired people without the aid of guides. The proposed system consists of an Android application that interacts with an external high-accuracy GPS sensor tracking pedestrian mobility in real-time, a second external device specifically designed to be mounted on traffic lights for identifying traffic light status and an ultrasonic sensor for detecting near-field obstacles along the route of the blind. Moreover, during outdoor navigation, it can optionally incorporate the use of Public Means of Transport, as well as provide multiple other uses such as dialing a call and notifying the current location in case of an emergency. We present findings from a Usability and UX standpoint of our proposed system conducted in the context of a pilot study, with 30 people having varying degrees of blindness. We also received feedback for improving both the available functionality of our application and the process by which the blind users learn the features of the application. The method of the study involved using standardized questionnaires and semi-structured interviews. The evaluation took place after the participants were exposed to the system’s functionality via specialized user-centered training sessions organized around a training version of the application that involves route simulation. The results indicate an overall positive attitude from the users.

29 December 2022 in Sensors
Verified
Journal Article
Open access
PDF file
PTParaskevi Theodorou
Paraskevi Theodorou
KTKleomenis Tsiligkos
Kleomenis Tsiligkos
Apostolos MelionesApostolos Meliones
Apostolos Meliones
KFKonstantinos Filios
Konstantinos Filios
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.