Views: 0 Author: Site Editor Publish Time: 2026-02-14 Origin: Site
The core technology of the intelligent PAPR (Electric Air Purifying Respirator) is to monitor the breathing status in real time through sensors, and then use intelligent algorithms to predict and actively adjust the fan ventilation, thereby achieving breathing synchronization and enhancing comfort and safety.
Sensing technology: The "sensing organs" of the system
The intelligent PAPR relies on highly sensitive sensors to capture key physical signals in real time.
The core is the pressure sensor: A 2025 research developed a low-cost solution that uses only one differential pressure sensor to accurately estimate the real-time breathing flow of the user - 1. The principle is to monitor the difference between the fan ventilation pressure and the pressure inside the mask, and then use the algorithm to reverse calculate the airflow changes caused by breathing movements.
The front part is the humidity sensor: More advanced research (in the previously mentioned paper) introduced an ultra-hydrophobic humidity sensor. This sensor is made of special materials (such as PVDF/SiO?) and has an extremely hydrophobic surface, which effectively prevents condensation water from interfering, thus enabling more accurate and stable monitoring of the humidity fluctuations directly generated by breathing in high-humidity environments, providing a more direct signal of the breathing rhythm for the algorithm.
Core algorithm: The system's "decision-making brain"
The algorithm is responsible for processing sensor data and making predictions and decisions.
Respiration flow and leakage judgment algorithm: As shown in the flowchart, the system can automatically determine whether the mask is worn properly and whether there is leakage based on the time integral value of the respiration flow - 1. This is the foundation for ensuring protection safety.
Respiration rhythm prediction algorithm: More advanced systems use time series prediction models such as GRU (Gated Recurrent Unit) neural networks. GRU is a type of recurrent neural network that can effectively handle time series data with continuity and periodicity, such as breathing. By learning from historical breathing data, it can predict the user's next inhalation or exhalation demand in advance.
Intelligent Control: The "Operating Organs" of the System
Ultimately, the instructions generated by the algorithm will dynamically control the speed of the fan. For instance, when it is predicted that the user is about to inhale, the fan speed will be increased in advance to increase the supply of air and maintain positive pressure; during the exhalation phase, the speed will be appropriately reduced to decrease the resistance during exhalation.
