This paper introduces an evaluation approach that was applied to clinical data collected from a virtual reality aided motor training program for post-stroke rehabilitation. The goal of the proposed evaluation approach is to diagnose the patient's current status (performance) and detect change in status over time (progression). Three measures, performance time, movement efficiency, and movement speed, were defined to represent kinematic features of reaching. 3-D performance maps and progression maps were generated based on each kinematic measure to visualize a single patient's behavior. The case study revealed the patient's current status as to direction and range of upper extremity reach ability, composed of pitch, yaw and arm length. Further, progression was found and visualized quantitatively over a series of practice sessions. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Yen, S. C., Stewart, J., Mclaughlin, M., Parsons, T., Winstein, C. J., & Rizzo, A. (2007). Evaluation approach for post-stroke rehabilitation via virtual reality aided motor training. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4566 LNCS, pp. 378–387). https://doi.org/10.1007/978-3-540-73333-1_45
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