Use of an Indoor Navigation System by Sighted and Blind Travelers

Experimental Evaluation of Multi-scale Tactile Maps Created with SIM, a Web App for Indoor Map Authoring

In this article, we introduce Semantic Interior Mapology (SIM), a web app that allows anyone to quickly trace the floor plan of a building, generating a vectorized representation that can be automatically converted into a tactile map at the desired scale. The design of SIM is informed by a focus group with seven blind participants. Maps generated by SIM at two different scales have been tested by a user study with 10 participants, who were asked to perform a number of tasks designed to ascertain the spatial knowledge acquired through map exploration. These tasks included cross-map pointing and path finding, and determination of turn direction/walker orientation during imagined path traversal. By and large, participants were able to successfully complete the tasks, suggesting that these types of maps could be useful for pre-journey spatial learning.

Development of a metric to evaluate the ergonomic principles of assistive systems, based on the DIN 92419

The DIN 92419 defines six principles for assistive systems' ergonomic design. There is, however, a lack of measurement tools to evaluate assistive systems considering these principles. Consequently, this study developed a measurement tool for the quantitative evaluation of the fulfilment of each principle for assistive systems. A systematic literature review was performed to identify dimensions belonging to the principles, identify how previous research evaluated these dimensions, and develop a measurement tool for assistive systems. Findings show that scales commonly used for evaluating assistive systems disregard several aspects highlighted as relevant by research, implying the need for considering the DIN 92419 principles. Based on established scales and theoretical findings, a questionnaire, and a checklist for evaluating assistive systems were developed. The work provides a grounding for measuring relevant aspects of assistive systems. Further development is needed to substantiate the reliability and validity of the proposed questionnaire scales and items. Practitioner Summary: Responding to the gap of a holistic measurement tool to evaluate assistive systems, a systematic literature review was performed considering the DIN 92419 principles. This resulted in a comprehensive summary of relevant aspects of assistive systems that were made numerically measurable, which proposes better criteria to assess assistive systems. Abbreviations: IoT: internet of things; RQ: research question; TAM: technology acceptance model; UTAUT: unified theory of acceptance and use of technology; AaaS: adaptivity as a service; SAR: socially assistive robots; SEEV: salience, effort, expectancy, and value; PRISMA: preferred reporting items for systematic reviews and meta-analyses; HMI: human-machine interaction; HRI: human-robot interaction; BCI: brain-computer interface; QUEST: Quebec user evaluation of satisfaction with assistive technology; SUS: system usability scale; NASA-TLX: NASA task load index; ATD PA: assistive technology device predisposition assessment; Wheel Con: wheelchair use confidence scale; CATOM: caregiver assistive technology outcome measure; CBI: caregiver burden inventory; RoSAS: robotic social attributes scale; WheelCon: wheelchair use confidence scale; IMI: intrinsic motivation inventory; ATD PA: assistive technology device predisposition assessment; UEQ: User experience questionnaire; USEUQ: usefulness satisfaction and ease of use questionnaire; USPW: usability scale for power wheelchairs; UES: user engagement scale; SUTAQ: service user technology acceptability questionnaire; QUEAD: questionnaire for the evaluation of physical assistive devices; FATCAT: functional assessment tool for cognitive assistive technology; SE-HRI: human-robot interaction scale; SART: situation awareness rating technique; TSQ;WT: tele-healthcare satisfaction questionnaire-wearable technology; PAIF: participants' assessment of the intervention's feasibility; SWAT: subjective workload assessment technique; MARS-HA: measure of audiologic rehabilitation self-efficacy for hearing aids; IOI-HA: International outcome inventory for hearing aids; FMA: functional mobility assessment; FBIS: familiarity and behavioural intention survey; CSQ: client satisfaction questionnaire; COPM: canadian occupational performance measure; ATCS: assistive technology confidence scale; ACC: acceptance; SSP: safety, security and privacy; OPT: optimisation of resultant internal load; CTRL: controllability; ADAPT: adaptability; P&I: perceptibility and identifiability; AAL: ambient assisted living; VR: virtual reality; AS: assistive system; WEIRD: Western, educated, industrialised, rich, and democratic; HEART: horizontal european activities of rehabilitation technology; AAATE: advancement of assistive technology in Europe's; GATE: global collaboration on assistive technology; ATA-C: assistive technology assessment toolkit.

Blind Users Accessing Their Training Images in Teachable Object Recognizers

Teachable object recognizers provide a solution for a very practical need for blind people - instance level object recognition. They assume one can visually inspect the photos they provide for training, a critical and inaccessible step for those who are blind. In this work, we engineer data descriptors that address this challenge. They indicate in real time whether the object in the photo is cropped or too small, a hand is included, the photos is blurred, and how much photos vary from each other. Our descriptors are built into open source testbed iOS app, called MYCam. In a remote user study in (N = 12) blind participants' homes, we show how descriptors, even when error-prone, support experimentation and have a positive impact in the quality of training set that can translate to model performance though this gain is not uniform. Participants found the app simple to use indicating that they could effectively train it and that the descriptors were useful. However, many found the training being tedious, opening discussions around the need for balance between information, time, and cognitive load.

An Indoor Navigation Methodology for Mobile Devices by Integrating Augmented Reality and Semantic Web

Indoor navigation systems incorporating augmented reality allow users to locate places within buildings and acquire more knowledge about their environment. However, although diverse works have been introduced with varied technologies, infrastructure, and functionalities, a standardization of the procedures for elaborating these systems has not been reached. Moreover, while systems usually handle contextual information of places in proprietary formats, a platform-independent model is desirable, which would encourage its access, updating, and management. This paper proposes a methodology for developing indoor navigation systems based on the integration of Augmented Reality and Semantic Web technologies to present navigation instructions and contextual information about the environment. It comprises four modules to define a spatial model, data management (supported by an ontology), positioning and navigation, and content visualization. A mobile application system was developed for testing the proposal in academic environments, modeling the structure, routes, and places of two buildings from independent institutions. The experiments cover distinct navigation tasks by participants in both scenarios, recording data such as navigation time, position tracking, system functionality, feedback (answering a survey), and a navigation comparison when the system is not used. The results demonstrate the system's feasibility, where the participants show a positive interest in its functionalities.