*2.6. Evaluation Metric*

The performance of the estimation model was mainly evaluated by comparing the root mean square error (*R*) between the estimated value *y*<sup>ˆ</sup>*knee* and the experiment value (EV) *yknee* defined as follows:

$$R = \sqrt{\frac{1}{S} \sum\_{i=1}^{S} \left( \mathfrak{g}\_{kne,i} - \mathfrak{g}\_{kne,i} \right)^{2}} \,\, \, \, \, \tag{6}$$

where *S* is the number of test samples. In this work, *R* is an indicator for the judgement of the estimation models, and the accuracy of the estimation model increases with a decrease of *R*.
