User Evaluation of the MOBOT Rollator Type Robotic Mobility Assistive Device

Abstract

Abstract:In this paper, we report on the evaluation strategy and the results that were obtained from the final end-user evaluation process of an innovative robotic assistive device supporting mobility. More specifically, the paper deals with the evaluation of the MOBOT robotic rollator as regards to the system's overall performance and its individual assistive characteristics and functionalities, as implemented in respect to (i) the provided cognitive assistance, and (ii) the adopted audio-gestural human-robot communication model. User evaluation was designed on the basis of an extensive survey of scales and methodologies widely reported in the relevant literature. The actual evaluation phase exploited the QUEST 2.0, ATDPA-Device Form, and PYTHEIA scales to measure the subjective satisfaction of the users. The PYTHEIA scale, in particular, was structured in order to fill the gaps that were identified during the study of previously existing tools for measuring assistive device user satisfaction. The scale was applied for the first time during the reported evaluation process. An analysis of the results showed that MOBOT was ranked very high by end users in all of the aspects addressed by the three employed assessment scales, thus providing significant evidence for positive acceptance of any industrialized outcome of the current prototype in the assistive robots market.

Artificial Vision Algorithms for Socially Assistive Robot Applications: A Review of the Literature

“…The rest runs in real time. In terms of computer resources, a computer with advanced hardware is used in [ 76 ], as well as robotic platforms such as MOBOT [ 77 ], Hobbit [ 80 ], Roomba [ 81 ], and a customized robot [ 78 ].…”

“…Finally, a signed distance functions (SDF) model is computed to correct and track the body position. Moreover, Koumpouros et al in [ 77 ] presented the MOBOT robot, which is capable of monitoring human performance and postural stability to detect falls and to recognize the human physiological state. The authors used an RGB-D camera for body pose estimation and a LIDAR sensor to detect and avoid obstacles.…”

User Needs and Limitations of Existing Mobility Devices

“…Thecurrentstudyattemptedtorevealmobilityaiduserneedsandlimitationsofthemostcommonly usedmobilityaids.Theuserevaluationofassistivedeviceshasbeenprovedtobeverychallenging (Koumpouros et al, 2017a;Koumpouros et al, 2017b;Efthimiou et al, 2016). A bibliographic surveyfollowedbyarealcasestudyonasmallsizeofthepopulationwithspecificcharacteristics (mobilityaidusers,rehabilitationpatientsorolderadults,independentofanyassociatingdisease).…”

The i-Walk Lightweight Assistive Rollator: First Evaluation Study

“…The average walking velocity is a diagnostic marker for instability and reduced functional ability, as well as a predictor for overall health. Following previous similar studies (Koumpouros et al, 2017;Geravand et al, 2017) patients with an average walking speed less than 0.6 m/s were excluded from the study. The inclusion/exclusion criteria are succinctly presented in Table 1.…”