Design And Implementation Of Pressure And Breathing Detection System For Smart Clothin

In recent years,wearable devices and mobile health care have developed rapidly,and the combination of the two has realized the transformation from hospital treatment to family prevention and health care.Wearables based physiological parameters testing scheme is a research hotspot in this field.It can realize synchronous measurement of multiple physiological parameters and has better wearing comfort,which is the future development direction of wearable technology.Based on the team has been developed on the basis of the pressure sensor and breathing fabric,the research and development in intelligent clothing pressure and breathing test system,solved the signal detection,circuit design,data transmission,algorithm processing key technical problems,such as prepared to test on the recognition and respiration rate of smart clothing prototype sample,verify the feasibility of the scheme,It provides technical accumulation and valuable experience for further optimization of the intelligent clothing.The main work of this project includes:1.Designed pressure and respiration detection system based on fabric sensor.According to the characteristics of fabric sensor output signal and the requirements of garment integration,a multi-node distributed detection system scheme based on Bluetooth wireless communication is developed,and the circuit design and software programming of each node in the system are completed.The bluetooth networking among nodes is studied,the star network topology is built,bluetooth data transmission and network energy saving schemes are designed,and the energy consumption of nodes is reduced from hardware and software to meet the energy consumption requirements of intelligent clothing.2.The signal processing algorithm based on breath fabric sensor is studied.Based on the frequency analysis of the original measured signals of the breathing fabric sensor,a breathing signal processing algorithm is proposed.The algorithm includes signal preprocessing,feature point extraction and respiration rate calculation.The pre-processing algorithm combines moving average filter and median filter to improve the signal-to-noise ratio of respiratory signal effectively.The feature point extraction algorithm adopts differential double threshold algorithm,which adds time threshold on the basis of amplitude threshold to improve the accuracy of peak point identification.The algorithm has been successfully implemented in microcontroller.3.An intelligent clothing prototype sample integrated with the detection system was made and experimental research was carried out.The experimental platform of the detection system was built,and the experiments of compression recognition and respiration rate detection were carried out.The experimental result shows that the design of the detection system can be implemented on the recognition and detection function of respiration rate,in the case of outside pressure more than set threshold,can achieve accurate pressure identification,breathing rate under stationary and specific motions of the overall relative error under 6.4% and 3.7% respectively,so as to prove the feasibility of the system.