Research On Polymer Composite Film Based QCM Humidity Sensor And Its Application In Respiratory Monitoring

Humidity is one of the most important parameters in people’s daily life.Accurate and reliable humidity measurement is very important in various practical applications.With the rapid development of social intelligence and equipment integration,scientific researchers have carried out some breakthrough research on humidity sensors,such as the application of humidity sensors in respiratory monitoring.The existing breathing pattern detection mainly relies on polysomnography（PSG）,lung function tester,and end-expiratory carbon dioxide Concentration（ETCO₂）and other monitoring technologies.Although these methods can accurately record and evaluate various parameters of lung function and breathing pattern,they have disadvantages such as high cost,cumbersome operation,and not easy to carry and material resources.The advantages of breathing detection methods cannot be fully utilized in daily life.Aiming at the requirements of portable,low-threshold breathing detection,research on humidity sensors with high performance,focusing on response speed and high humidity stability has important practical significance and social value.This paper is dedicated to researching the sensitivity performance and respiratory monitoring application characteristics of Quartz crystal microbalance（QCM）humidity sensor based on polymer composite film,and combining with intelligent algorithms to realize respiratory pattern recognition.First,in-situ polymerization,co-deposition and other material synthesis methods are used to prepare polymer composite humidity-sensitive films,and high-performance QCM humidity sensors are prepared by spraying methods.At the same time,we use SEM,TEM,XRD,XPS,FT-IR,water contact angle test and other characterization methods to analyze the microscopic morphology,molecular structure,chemical bond,hydrophilicity and other characteristics of the humidity-sensitive film.Secondly,the QCM humidity test system was used to modify the dynamic response,hysteresis characteristics,response/recovery time,repeatability,selectivity,long-term stability and other moisture sensitive properties of the prepared CS-HTNs sensor halloysite nanotubes（HTNs）modified chitosan（CS）.and PDA-GO sensor of polydopamine（PDA）modified graphene oxide（GO）,and the adsorption kinetics of water molecules were studied using the bimodal exponential kinetic adsorption model,which revealed the moisture-sensitive detection mechanism of the moisture-sensitive film.Next,we screened out QCM humidity sensors with fast response/recovery time and high humidity stability for respiratory monitoring,and obtained different types of respiratory humidity characteristic data.Finally,a respiration prediction model based on probabilistic neural network and support vector machine was constructed for the recognition of five types of respiration.Both models achieved a good recognition accuracy rate（above 90%）,among them,the breathing prediction model based on the support vector machine has more superior characteristics,its prediction result is as high as 98%,the training speed is fast,and the generalization ability is strong.This paper explores the humidity sensitive detection performance of QCM humidity sensor based on polymer composite film,and applies the QCM detection method to respiratory monitoring,and further uses intelligent algorithm models to realize the recognition of different types of respiratory patterns,which provides important theoretical guidance for the study of real-time online respiratory monitoring devices,and has high use value for the early diagnosis of potential respiratory diseases and the protection of human health.In the future,sensors can be further integrated,flexible and wireless to realize wearable health care.