The Augmented Reality Telerehabilitation System for Powered Wheelchair User’s Training

Abstract

Many people worldwide have been experimenting a decrease in their mobility as a result of aging, accidents and degenerative diseases. In many cases, a Powered Wheelchair (PW) is an alternative help. Currently in Brazil, patients can receive a PW from the Unified Health System, following prescription criteria. However, they do not have an appropriate previous training for driving the PW. Consequently, users might suffer accidents since a customized training protocol is not available. Nevertheless, due to financial and/or health limitations, many users are unable to attend a rehabilitation center. To overcome these limitations, we developed an Augmented Reality Telerehabilitation System Architecture based on the Power Mobility Road Test (PMRT) for supporting PW user's training. In this system, the therapists can remotely customize and evaluate training tasks and the user can perform the training in safer conditions. The video stream and data transfer between each environment were made possible through UDP (User Datagram Protocol). To evaluate and present the system architecture potential, a preliminary test was conducted with 3 spinal cord injury participants. They performed 3 basic training protocols defined by a therapist. The following metrics were adopted for evaluation: number of control commands; elapsed time; number of collisions; biosignals. Also, a questionary was used to evaluate system features. Preliminary results demonstrated the specific needs of individuals using a PW thanks to adopted metrics (qualitative and emotional). Results have shown the need for a training system with customizable protocols to fulfill these needs. User's evaluation demonstrates that the combination of AR techniques with PMRT adaptations, increases user's well-being after training sessions. Furthermore, a training experience helps users to overcome their displacement problems, as well as for appointing challenges before large scale use. This system architecture allows further studies on telerehabilitation of PW users training.

Preliminary assessment of a multimodal electric-powered wheelchair simulator for training of activities of daily living

“…In addition, participant performance results were recorded in the form of three main parameters: (a) the time spent performing a specific task; (b) the number of collisions with obstacles during the course; (c) the number of commands given in a specific input control. Based on the literature, these parameters were chosen because they are a relevant indicator of driving ability [9,[36][37][38]. Table 3 presents these results obtained by all participants during the experiments.…”

Holo-SpoK: Affordance-Aware Augmented Reality Control of Legged Manipulators

“…Applications in this domain can be classified into two categories: remote interactions (i.e., teleoperation) [14], where the user sends control commands from outside the robot's location, and proximal interactions, where the user and the robot share the same location. Applications in the latter domain include robot programming [15], trajectory planning [16] and assistive robotics [17]. However, most previous work associates ARbased robot control with low-level instructions, thus limiting human-robot interactions to the users' understanding of the capabilities of the robots.…”

Augmented reality for stroke rehabilitation during COVID-19

“…Later on, many systems have been developed and reported with encouraging results for stroke recovery. The most recent work include the AR-augmented wheelchairs by Daniel et al in 2020 [ 44 ], the Kinect-based training by Adyasha et al [ 41 ] and Au ra et al [ 42 ] in 2019. In Fig.…”