## 4 Results and Discussion
### Performance Comparisons Using the Evaluation Metrics  
Table 4 shows the performance comparison results for the accuracy of the _HbA1c_ estimates between the previous study [14] using three wavelengths and this study using only two wavelengths. We can see that in the _HbA1c_ estimation, even though only two wavelengths were used, the performance was comparable to (though slightly worse than) that of the previous study when only ratio calibrations were applied, and when value  
Figure 8: Scatter plot and Bland–Altman analysis for the estimated \(SpO_{2}\) values after ratio calibration. Figure 7: EGA and Bland–Altman analysis for _HbA1c_ with the whole finger model (considering both ratio and value calibrations). (_HbA1c_) calibration was applied in addition to ratio calibrations, the performance was almost equal to or slightly better compared to that of the previous study [14]. Table 5 shows the EGA-based comparison between the previous study [14] for estimating _HbA1c_ using three wavelengths and this study using only two wavelengths. The number inside the table indicates the number of points (%values inside bracket) in the corresponding zone. For the whole finger model, the performances of Proposed1 and Proposed2 were similar. However, for the blood vessel model, the performance of Proposed2 was slightly better, with 80% of the data points inside Zone A. Compared with the previous study [14], the Proposed2 method performed better. Table 6 summarizes the Bland-Altman-analysis-based comparison between the previous study [14] for estimating _HbA1c_ using three wavelengths and this study using only two wavelengths. We can see that the limits of agreement for the proposed methods are not very different compared to those of the previous method [14]. The 95% limits of agreement should contain the difference between the estimates and the reference for 95% of the measurements. In the previous study [14], considering the whole finger model, only one data point was found outside this limit. Similarly, in the proposed method here, there was only one data point outside the limit. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Metric**} & \multicolumn{2}{c}{**Limit of Agreement (95\%;**} & \multicolumn{1}{c}{**Data Points Out of Limit**} \\  & & **1.96 SD** & & **of Agreement** \\ \hline Blood vessel [14] & \(-0.03\pm 0.458\) & \(-0.93\) to \(0.87\) & \(0\) \\ Whole finger [14] & \(-0.06\pm 0.326\) & \(-0.70\) to \(0.57\) & \(1\) \\ Blood vessel (Proposed1) & \(-0.16\pm 0.961\) & \(-1.12\) to \(0.80\) & \(0\) \\ Whole finger (Proposed1) & \(-0.072\pm 0.926\) & \(-1.00\) to \(0.85\) & \(0\) \\ Blood vessel (Proposed2) & \(-0.029\pm 0.859\) & \(-0.89\) to \(0.83\) & \(1\) \\ Whole finger (Proposed2) & \(-0.0066\pm 0.862\) & \(-0.86\) to \(0.87\) & \(1\) \\ \hline \end{tabular}  
* Proposed1: using ratio calibrations only; Proposed2: using both ratio calibrations and value (_HbA1c_) calibrations.  
\end{table} 
Table 6: Bland-Altman-analysis-based comparison between this study and the previous study for estimating _HbA1c_. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**MethodMetric**} & \multirow{2}{*}{**MSE**} & \multirow{2}{*}{**ME**} & \multirow{2}{*}{**MAD**} & \multirow{2}{*}{**RMSE**} & \multirow{2}{*}{**Pearson’s r**} \\ \hline Blood vessel [14] & \(0.211\) & \(-0.031\) & \(0.375\) & \(0.459\) & \(0.916\) \\ Whole finger [14] & \(0.110\) & \(-0.065\) & \(0.271\) & \(0.332\) & \(0.959\) \\ Blood vessel (Proposed1) & \(0.266\) & \(-0.159\) & \(0.423\) & \(0.515\) & \(0.896\) \\ Whole finger (Proposed1) & \(0.224\) & \(-0.055\) & \(0.391\) & \(0.473\) & \(0.905\) \\ Blood vessel (Proposed2) & \(0.193\) & \(-0.029\) & \(0.363\) & \(0.439\) & \(0.929\) \\ Whole finger (Proposed2) & \(0.194\) & \(0.007\) & \(0.366\) & \(0.440\) & \(0.930\) \\ \hline \end{tabular}  
* Proposed1: using ratio calibrations only; Proposed2: using both ratio calibrations and value (_HbA1c_) calibrations.  
\end{table}