## 2 Materials and Methods  
### MW-PPG Signal Collection and Hb Prediction System  
The PPG signal acquisition device consists of DCM08, FSR400, a capacitive touch screen, a microcontroller, and a power supply circuit. The DCM08 is the MW-PPG acquisition sensor, which ensures long-term operational stability, and the FSR400 is the contact pressure sensor in this study, which can capture the pressure changes in the strain gauge and transmit the pressure signal to the main control MCU for subsequent processing. To capture the contact pressure at the time of signal acquisition more accurately, a contact pressure transfer structure is designed in this study. The structure is divided into three layers: the subject contact module, the pressure transfer module, and the sensor base. Among them, the center of the subject contact module adopts a recessed design to enable precise finger placement and pressure application, and the light-emitting source is extended in the center of the recess. The multi-wavelength sensor DCM08 signal receiving end is fixed and placed in the pressure transfer module, and an FPC flexible circuit board is used to transmit the multi-wavelength PPG signal and the contact pressure signal to the circuit board where the main control chip is located. The sensor is stabilized on the sensor base, and a convex structure is used underneath to transmit the pressure applied by the subject to the sensor to the FSR400 for real-time pressure detection. The framework diagram of the MW-PPG acquisition and Hb prediction system is shown in Figure 1, and the exterior of the MW-PPG signal acquisition device and the internal structure of the sensor are shown in Figure 2.  
Figure 1: The figure shows the general flow of the research. It mainly includes three main processes and nine subplots from developing signal acquisition equipment to acquiring data sets, then constructing a predictive model from the data sets, and developing the corresponding host computer to apply the model. To facilitate the preservation and management of MW-PPG data, this study used the Qt creator companion to design and develop an MW-PPG signal storage platform. The application can communicate with the MW-PPG acquisition device described in the previous section via serial port or Wi-Fi and transfer the obtained MW-PPG signals and contact pressure signals to the computer to be saved in a local database (SQLite). During the data acquisition process, the application needs to first fill in the subject's personal physiological information with the application's personal information fill-in field and notify the subject to sit still and prepare for the acquisition. After ticking the checkboxes in the Acquisition Mode column according to the time of the signal to be extracted, the Start button is clicked and the pulse wave signal of the subject is acquired. Once the acquisition is complete, it is also possible to check the quality of the PPG signal by plotting the waveform of the acquired PPG signal. The application also has the function to export the personal information and pulse wave signals in the database one by one according to their IDs to a CSV file in a fixed folder in order to facilitate the subsequent processing of data and other operations. Throughout the MW-PPG signal acquisition and Hb prediction system, to apply the prediction model in this study, our research team simultaneously developed another application program (App) to be used to call the model and predict the real-time physiological metrics of the test subject. In this application, users can create an account to save and manage their physiological and health information and predict heart rate, oxygen saturation, and Hb in real-time. The app consists of a login screen, a waveform display, a measurement screen, and a test record query screen. After the subject selects the 1-min static indicator and clicks the Start Measurement button, the app will prompt the user to start the measurement after three seconds.