![[feed]](/style/images/feed-icon-14x14.png){kind=icon}
|
PDF (Original Article)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB | |
![[img]](http://edoc.mdc-berlin.de/style/images/fileicons/other.png) |
Other (Supplementary Materials)
288kB |
| Item Type: | Article |
|---|---|
| Title: | RGB-Depth camera-based assessment of motor capacity: normative data for six standardized motor tasks |
| Creators Name: | Röhling, H.M. and Otte, K. and Rekers, S. and Finke, C. and Rust, R. and Dorsch, E.M. and Behnia, B. and Paul, F. and Schmitz-Hübsch, T. |
| Abstract: | BACKGROUND: Instrumental motion analysis constitutes a promising development in the assessment of motor function in clinical populations affected by movement disorders. To foster implementation and facilitate interpretation of respective outcomes, we aimed to establish normative data of healthy subjects for a markerless RGB-Depth camera-based motion analysis system and to illustrate their use. METHODS: We recorded 133 healthy adults (56% female) aged 20 to 60 years with an RGB-Depth camera-based motion analysis system. Forty-three spatiotemporal parameters were extracted from six short, standardized motor tasks—including three gait tasks, stepping in place, standing-up and sitting down, and a postural control task. Associations with confounding factors, height, weight, age, and sex were modelled using a predictive linear regression approach. A z-score normalization approach was provided to improve usability of the data. RESULTS: We reported descriptive statistics for each spatiotemporal parameter (mean, standard deviation, coefficient of variation, quartiles). Robust confounding associations emerged for step length and step width in comfortable speed gait only. Accessible normative data usage was lastly exemplified with recordings from one randomly selected individual with multiple sclerosis. CONCLUSION: We provided normative data for an RGB depth camera-based motion analysis system covering broad aspects of motor capacity. |
| Keywords: | Instrumental Motion Analysis, Normative Data, RGB-Depth Camera, Microsoft Kinect v2, Gait Analysis, Tandem Gait, Postural Control, Stepping in Place, Standing Up and Sitting Down |
| Source: | International Journal of Environmental Research and Public Health |
| ISSN: | 1660-4601 |
| Publisher: | MDPI |
| Volume: | 19 |
| Number: | 24 |
| Page Range: | 16989 |
| Date: | 17 December 2022 |
| Official Publication: | https://doi.org/10.3390/ijerph192416989 |
| PubMed: | View item in PubMed |
Repository Staff Only: item control page
Download Statistics
Download Statistics
