Evaluating rehabilitation progress using motion features identified by machine learning
L. Lu, Y. Tan, M. Klaic, M. P. Galea, F. Khan, A. Oliver, I. Mareels, D. Oetomo, E. Zhao
This paper uses machine learning to identify motion features for evaluating rehabilitation progress in stroke patients, finding that movement smoothness is the best measure.
bioRxiv · Apr 15, 2020Bioengineering