Name
Abstract | ||
|---|---|---|
•HSMM based approach is proposed to assess human movement during rehabilitation.•The method combines different aspects of both rule and template based approaches.•The reliability of the method is measured with respect to clinician judgment and DTW.•The proposed method shows a significant correlation with the clinical score.•The proposed method outperforms baseline approach as DTW. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jbi.2017.12.012 | Journal of Biomedical Informatics |
Keywords | Field | DocType |
Hidden Markov Models,Rehabilitation,Human motion,RGB-D camera | Rehabilitation,Data mining,Rehabilitation exercise,Dynamic time warping,Computer science,Markov chain,Training program,Correlation,Artificial intelligence,Hidden Markov model,Machine learning,Hidden semi-Markov model | Journal |
Volume | ISSN | Citations |
78 | 1532-0464 | 3 |
PageRank | References | Authors |
0.49 | 13 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Capecci, M. | 1 | 4 | 3.54 |
| Ceravolo, M.G. | 2 | 12 | 2.20 |
| Francesco Ferracuti | 3 | 65 | 12.28 |
| Sabrina Iarlori | 4 | 37 | 4.87 |
| V. Kyrki | 5 | 652 | 61.79 |
| Andrea Monteriu | 6 | 102 | 27.48 |
| luca romeo | 7 | 21 | 9.59 |
| Verdini, F. | 8 | 16 | 4.99 |