## 2 Experiment Details
### Data Acquisition with Smartphone
#### 2.1.2 Acquisition with Android Phone  
As for Android-based platform, the choice for the smartphone is more complex. Android devices come in a wide range of hardware specifications regarding the built-in camera and the optical setup. Therefore, the quality of acquired data can vary significantly in different models constructed by different manufacturers. We therefore conducted a preliminary study (Supplementary Material Figure S1) to evaluate the performance of data acquisition on three smartphones with varying price ranges and camera specifications.  
For the preliminary study, 3 trials were completed from five subjects using a Xiaomi Redmi Note 5 Pro (Xiaomi, Beijing, China), Samsung Galaxy Note 8 (Made by Samsung, San Jose, CA, USA), and OnePlus 6T (Made by OnePlus, Guangdong, China). The camera sensors on the Redmi Note 5 Pro and the Galaxy Note 8 are manufactured by Samsung, whereas the OnePlus 6T has a camera sensor produced by Sony IMX. All of them have a dual camera setup with an illumination source in the form of a WLED flash placed next to the cameras. For this portion of the study, the video data were recorded at 30 fps at a resolution of 1920 \(\times\) 1080 pixels. Detailed specification for each of the phones is provided in Table 1. The Aperture column of Table 1 denotes the focal length of the smartphone camera.  
The quality of the PPG signal acquired from the same subject using three different smartphones is shown in Figure 2. In the first two signals, considerably more baseline variation can be observed in contrast with the third signal. To further evaluate the perfor  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Smartphones** & **Megapixel (MP)** & **Cam Type** & **Aperture** & **Sensor (\(\mu\)m)** & **Stabilization** \\ \hline \multirow{3}{*}{MI Note 5} & Cam1: 12 mp & Main cam & f/2.2 & 1.25 & \multirow{3}{*}{EIS} \\  & Cam2: 5 mp & Depth cam & f/2.0 & 1.12 & \\ \cline{1-1} \cline{3-6} \multirow{3}{*}{SM-Note 8} & Cam1: 12 mp & Main cam & f/2.4 & 1.0 & \\ \cline{1-1} \cline{3-6} \multirow{3}{*}{OnePlus 6T} & Cam2: 12 mp & Telephoto & f/1.7 & 1.4 & \\ \cline{1-1} \cline{3-6} \multirow{3}{*}{OnePlus 6T} & Cam1: 16 mp & Main cam & f/1.7 & 1.22 & \\ \cline{1-1} \cline{3-6} \multirow{3}{*}{} & Cam2: 20 mp & Telephoto & f/1.7 & 1.0 & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Android smartphones camera specifications.  
mance of the acquired signals by these phones, we attempted to extract the features from the acquired signals. For this, the signals were first preprocessed (Supplementary Material Figure S2) to remove high-frequency noise and baseline drift. Then, peak analysis was performed on the preprocessed PPG (Supplementary Material Figure S3)--the 1 st derivative and 2 nd derivative (Supplementary Material Figure S4) of the signals. From Supplementary Material Table S1, it can be seen the model was able to detect the 2 nd derivative peak with very few misses and false positives across all the subjects. We performed peak detection and observed the results as shown in Figure 2. With 5 different subjects and multiple trials with the three candidate smartphones, we could see that the Xiaomi was outperformed by the others in terms of accuracy.  
Even though the acquisition quality of Samsung Galaxy Note 8 and OnePlus 6T are comparable, Samsung Galaxy is more expensive with very similar specifications. Consequently, OnePlus 6T has been chosen as the desired Android platform for data acquisition for the study of glucose level detection. The further details on this study are available in the Supplementary resources.