## 2 Related Work
### IoT Pulse Oximeter Design  
A pulse oximeter is a noninvasive device that measures the oxygen saturation of arterial blood in the artery blood vessels, such as in fingers or earlobes. It also measure the concentration ratio of the difference in absorption spectrum between hemoglobin containing oxygen and total hemoglobin. This medical equipment is commonly used for emergency and general patients at medical institutions. Thus, this study proposes an IoT-based pulse oximeter.  
Figure 2 shows the system configuration of an IoT pulse oximeter [36]. The driver adjusts the amount of light and the generation period of red and infrared (IR) LED. The microcontroller unit (MCU), which controls these values, is a digital-analog converter (DAC). Filter 1 removes the noise of the analog signals obtained from red and IR light in a phototransistor, which is a light sensor. Filter 1 uses a lowpass filter. The cutoff frequency is set to 0-5 Hz. A multiplexer (MUX), which is signal selector 1, separates red, IR, and ambient (AMB) signals. The sample and hold analog circuit fixes the rate of change of the separated signals. Filter 2 is used for separating analog signals by frequency. Filter 2 uses a bandpass filter. The cutoff frequency is set to 0.5-5 Hz. The amplifier amplifies the AC signal. Signal selector 2 separates the DC and AC components from the red and IR signals. The analog to digital converter (ADC) converts analog signals to digital signals. The signals are selected and adjusted using the MCU. Ultimately, the infrared alternating current (IR AC), infrared direct current (IR DC), red AC, red DC, and AMB signals are stored in the MCU.  
The signals obtained from hardware are used to analyze the SpO2 and PR in the main system using an algorithm. SpO2 and PR are important data used in real-time emergency situation analysis. Therefore, SpO2 and PR analysis algorithms are the most important core technologies in pulse oximeters. Lastly, a Wi-Fi system for managing data communication is built for communicating with edge nodes.  
Figure 3 shows the seven steps for analyzing SpO2 and PR.  
Figure 3: SpO2 and PR algorithm configuration.  
Figure 2: Hardware system configuration of the IoT pulse oximeter.  
1. The signal noise is removed in the digital filter step. The digital filter uses a bandpass filter. The sample rate is set to 160 Hz, the cutoff frequency low-pass filter is set to 0.1\(-\)0.5 Hz, and the high-pass filter is set to 8\(-\)9 Hz.
2. Only the peak values of the signals are extracted in the peak detection step.
3. In the standard deviation acquisition step, the peak component values are acquired and filtered using the standard deviation of a probability distribution.
4. The obtained values for red and IR light are normalized in the red, IR normalization step.
5. In the pulse period and the SpO2 parameter acquisition step, the amplitude is measured using the component within the range by discerning whether or not it is a peak of the pulse within the measurement range from the acquired peak components, while red DC, red AC, IR DC, and IR AC, which are the parameters for measuring SpO2, are measured.
6. In the pulse rate and SpO2 Calculation step, the measured amplitude is averaged, the PR is calculated using the correlation formula of the sampling rate, and the SpO2 is calculated using the SpO2 parameters.
7. In the state distinction step, the state of the final obtained signal is distinguished as stable, moving, or unstable.