Instrumental Validity of the Motion Detection Accuracy of a Smartphone-Based Training Game
Bibliographic Data
| ID | 15508342 |
|---|---|
| Authors | Bernhard Guggenberger (0000-0002-2826-2999, FH JOANNEUM University of Applied Sciences, corresponding author), Andreas J Jocham (0000-0002-6627-689X, FH JOANNEUM University of Applied Sciences), Birgit Jocham (FH JOANNEUM University of Applied Sciences), Alexander Nischelwitzer (0000-0003-2282-1777, FH JOANNEUM University of Applied Sciences), Helmut Ritschl (0000-0001-7051-9076, FH JOANNEUM University of Applied Sciences) |
| Year | 2021 |
| Volume | 18 |
| Issue | 16 |
| Pages | 8410-8410 |
| Publication date | 2021-08-09 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph18168410 |
| PMID | 34444160 |
| OpenAlex | W3188356249 |
| Language | EN |
| References cited | 40 |
Demographic changes associated with an expanding and aging population will lead to an increasing number of orthopedic surgeries, such as joint replacements. To support patients' home exercise programs after total hip replacement and completing subsequent inpatient rehabilitation, a low-cost, smartphone-based augmented reality training game (TG) was developed. To evaluate its motion detection accuracy, data from 30 healthy participants were recorded while using the TG. A 3D motion analysis system served as reference. The TG showed differences of 18.03 mm to 24.98 mm along the anatomical axes. Surveying the main movement direction of the implemented exercises (squats, step-ups, side-steps), differences between 10.13 mm to 24.59 mm were measured. In summary, the accuracy of the TG's motion detection is sufficient for use in exergames and to quantify progress in patients' performance. Considering the findings of this study, the presented exer-game approach has potential as a low-cost, easily accessible support for patients in their home exercise program
Motion (physics · Motion analysis · Motion sensors · Physical medicine and rehabilitation · Physical therapy · Population · Simulation · Training (meteorology · Computer Science · Medicine · Prosthetics and Rehabilitation Robotics · Stroke Rehabilitation and Recovery · Total Knee Arthroplasty Outcomes · Artificial Intelligence · Rehabilitation
| Highly cited | No |
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