Development Of Wireless Respiration Monitoring System Based On Fast Humidity Sensor

The respiration monitoring possesses great medical value because of the health of human body is reflected partly through respiration. The respiration monitoring is really needed in many medical project such as the vital signs monitoring of patients with critical disease; the diagnosis and treatment of patients with infectious disease and chronic respiration disease. The vital signs of patients is judged by doctors through monitoring respiration in the outdoor first aid. It is helpful for families to realize the elderly people suffered from chronic diseases mostly. Till now, only a few of equipment with large volume and high cost exists on the market, moreover, they could not achieve non-contact measurement. Therefore, a wireless respiration monitoring system based on fast humidity sensor is developed in this paper.To meet the requirement of real-time signal collection, a humidity sensor based on graphene oxide quantum dots was used to detection respiratory signal; ZigBee was used as the technology of wireless communication; the collection system of respiratory signal was developed on CC2530 hardware platform and respiration monitoring software was developed on the MFC of VS2010. There were three parts (data acquisition node, router and data receiving node) which formed the signal acquisition system based on different function of each parts. The data acquisition node collected respiratory signal and sent the signals to other nodes. The router transmitted the data to data receiving node. The data receiving node was in charge of organizing and maintaining ZigBee network, sent respiratory signal to monitoring software through the serial port, meanwhile, achieved the scene alarm. Respiration monitoring software was used as follows:process the data of the serial port; display the waveform and parameters of respiration data in the interface. Also, the software could analyze the historical data and sent alarm signal to the coordinator.Respiration signal data processing algorithm was adopted in this paper to judge different respiration conditions such as normal, hypopnea and apnea. According to the treatment scheme, the peak value of respiration signal was extracted to determine the decision threshold by maximum iterative algorithm. Three different respiration conditions were judged by the hypopnea threshold and apnea threshold in the method of dynamic threshold algorithm which was the best choice of different threshold decision algorithm, and also, this algorithm was used to update the peak value and decision threshold of respiration data.The timeliness of respiration signal detection and the accuracy of respiration status judgment were measured under different respiration intensity and frequency. The reliability of respiration monitoring system and algorithm were proved in this paper. Meanwhile, the system had advantages of fast response, strong portability, non-contact measurement and wireless communication.