Name
Title | ||
|---|---|---|
Designing Configurable Arm Rehabilitation Games: How Do Different Game Elements Affect User Motion Trajectories? |
Abstract | ||
|---|---|---|
For successful rehabilitation of a patient after a stroke or traumatic brain injury, it is crucial that rehabilitation activities are motivating, provide feedback and have a high rate of repetitions. Advancements in recent technologies provide solutions to address these aspects where needed. Additionally, through the use of gamification, we are able to increase the motivation for participants. However, many of these systems require complex set-ups, which can be a big challenge when conducting rehabilitation in a home-based setting. To address the lack of simple rehabilitation tools for arm function for a home-based application, we previously developed a system, Cellulo for rehabilitation, that is comprised of paper-supported tangible robots that are orchestrated by applications deployed on consumer tablets. These components enable different features that allow for gamification, easy setup, portability, and scalability. To support the configuration of game elements to patients' level of motor skills and strategies, their motor trajectories need to be classified. In this paper, we investigate the classification of different motor trajectories and how game elements impact these in unimpaired, healthy participants. We show that the manipulation of certain game elements do have an impact on motor trajectories, which might indicate that it is possible to adapt the arm remediation of patients by configuring game elements. These results provide a first step towards providing adaptive rehabilitation based upon patients' measured trajectories. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/EMBC.2019.8857508 | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Field | DocType | Volume |
Computer vision,Rehabilitation,Computer science,Motor skill,Human–computer interaction,Medical treatment,Software portability,Artificial intelligence,Robot,Trajectory,Scalability | Conference | 2019 |
ISSN | Citations | PageRank |
1557-170X | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arzu Guneysu Ozgur | 1 | 0 | 1.35 |
| Maximilian Jonas Wessel | 2 | 0 | 0.34 |
| Thibault Asselborn | 3 | 2 | 2.04 |
| Jennifer K. Olsen | 4 | 22 | 11.52 |
| Wafa Johal | 5 | 0 | 1.69 |
| Ayberk Özgür | 6 | 0 | 0.34 |
| Friedhelm C Hummel | 7 | 7 | 1.88 |
| Pierre Dillenbourg | 8 | 1825 | 183.19 |