# Wearable Sensors for Vital Signs Measurement: A Survey
## 2 Classification of Wearable Medical Sensors
### Classification and Application of Wearable Medical Sensors
#### 2.2.2 Wearable Medical Sensors for Detecting Breathing Intensity  
The human body has two ways of breathing, namely through the nose and through the mouth. When the human body breathes, the temperature and pressure under the nose change with the passage of the breathing airflow. Therefore, the breathing state of the human body can be obtained by detecting changes in pressure and temperature. Many scholars have conducted research on the detection of respiratory intensity (Table 2). [PERSON] et al. (2018) designed a respiration measurement device based on a portable pressure sensor. A new algorithm based on the BP (back propagation) neural network was also proposed to stabilize device calibration and eliminate pressure signal noise. Finally, through experimental evaluation and case studies, the results showed that under appropriate parameter settings, the proposed BP neural network (BPNN) algorithm can effectively improve the reliability of the newly designed breathing device [22]. [PERSON] et al. (2019) discussed the manufacture of a flexible sensor, based on fiber grating encapsulated in Dragon skin 20 silicone rubber. They developed a wearable breathing and heart rate monitoring system and conducted an experimental evaluation of the sensor's response to strain, temperature changes, and relative humidity changes. The results showed that the system was easy to wear, non-invasive, and elastic, and it seemed to be suitable for matching the chest wall displacement well. It is used to monitor FR and HR, which provides the possibility of detecting respiratory intensity [23]. [PERSON] et al. (2019) designed a new type of fiber optic sensor that uses a mesh microbeam to simultaneously measure the heart rate (HR) and respiratory rate (RR) of infants during the perioperative period. The feasibility of the mesh microbend fiber sensor was evaluated, and the sensor was placed under the subject. The research results showed that the proposed microbending optical fiber sensor had good consistency with the standard physiological monitoring results used in the current medical environment when measuring HR and RR [24]. [PERSON] et al. (2020) studied the detection effect of respiratory intensity by using a medical sensor with a three -dimensional tetrapodal ZnO micro-structured networks (T-ZnO MNs) material spin-coated on an aluminum foil/ZnO piezoelectric film SAW (surface acoustic wave) device under ultraviolet light irradiation and relative humidity stimulation. they demonstrated that the sensitivity of the prepared material to UV (ultraviolet) light intensity changes significantly under the bending condition. At the same time, after using T-ZnO MNs, the sensing performance of the respiratory characteristics increased by nearly 1.7 times, showing its ability to enhance the effect of respiration and respiration monitoring applications [25]. [PERSON] et al. (2020) designed a simple electrochemical sensor to selectively detect the intensity of ROS (reactive oxygen species) in sputum samples (volume less than 500 \(\mu\)L) in response to the new coronavirus epidemic. The results showed the accuracy and sensitivity of the response calibration to both be 97%, which provides hope for real-time tracking of the new coronavirus in sputum samples based on reactive oxygen species in more than four hospitals [26]. However, in the actual breathing-intensity detection process, the air pressure changes in the nose and mouth caused by breathing are very weak, and the sensitivity of the air pressure sensor is often very high, making it more susceptible to the influence of external factors, and resulting in misjudment [27, 28]. Therefore, this research proposed an algorithm for detecting breathing state and frequency, based on changes in temperature and humidity, as shown in Figure 2. After the algorithm is processed, the temperature and humidity changes in the breath can be successfully transformed into changes in the breathing state.