**5. Conclusions**

We developed a DTW-based algorithm to automatically evaluate user's performance during physical rehabilitation exercises. We chose eight bones vectors of the human skeleton and body orientation as the input features and proposed a simple but innovative method to further convert the DTW matching cost to a meaningful performance score in terms of percentage (0–100%), without training data and experience of experts. The effectiveness of the proposed algorithm was tested through a follow-up experiment with 21 subjects when playing a complex whole-body exercise (Tai Chi) instead of simple repetitive exercises. Results showed that the algorithm scores had a strong positive linear relationship (r = 0.86) with experts' ratings and the calibrated algorithm scores were comparable to the gold standard. These findings suggested that our algorithm could be effectively used for automatic performance evaluation of an older individual when performing home-based physical rehabilitation exercises.

**Author Contributions:** Conceptualization, S.X. Data curation, X.Y. Formal analysis, X.Y. Funding acquisition, S.X. Methodology, X.Y. and S.X. Project administration, S.X. Software, X.Y. Supervision, S.X. Writing—original draft, X.Y. Writing—review & editing, S.X.

**Funding:** The Basic Science Research Program through the National Research Foundation of Korea (NRF-2017R1C1B2006811) and High Risk High Return Project of KAIST (N1017003) funded this research.

**Acknowledgments:** The authors would like to thank Taekyoung Kim for his assistance with experimental data acquisition. The authors also acknowledge the strong support from the Tai Chi experts at Jin-Jeong-Loe Chen Style Tai Chi Academy in Daejeon, South Korea.

**Conflicts of Interest:** The authors declare no conflict of interest.


**Table A1.** Questionnaire for user acceptance evaluation.



*Sensors* **2019** , *19*, 2882
