Design Of Breath Detecting E-Nose Based On Resonant SAW Sensor For Lung Cancer Diagnosis

Incidence of lung cancer showed a rapid rise in recent years, and due to the low rate of early diagnosis, lung cancer has become the first cause of death caused by cancer; for its non-invasive, simple and fast characteristics, breath diagnosis is becoming a new diagnostic method. In this paper, a novel breath detecting e-Nose based on resonant surface acoustic wave (SAW) sensor is presented, which implements high-precision detection of the lung cancer diagnostic markers in breath at the ppb level; in the clinical experiments, this e-Nose distinguishes lung cancer patients and normal people effectively, and pioneers a new way for lung cancer screening and early-stage diagnosis.The content of this article is divided into three parts:The first part is the design for sensor's application. Firstly, a novel resonant SAW sensor was designed which can be used for breath detection, and its sensitivity to quality is up to 2.67kHz/ng, while the detector's noise caused by temperature change is only lOHz; secondly, according to the characteristics of lung cancer markers, the use of Tenax-TA combined with gas chromatography (GC) technique on breath samples as the pretreatment method was proposed; thirdly, a split-type sensor chamber suitable for the instrument was designed, which docks GC and the sensor perfectly, as well as provides a stable external environment for the sensor.The second part is the design of the circuits and software. The control and signal detection circuits were designed based on AT89S52 and MSP430F149, and the accuracies of temperature control and signal detection are±0.01℃and±0.1 Hz respectively; software of microprocessors was developed, which controls the process of data acquisition, transmission and detection automatically; the software of PC was designed and developed, and in on-line state, the program can display and store data from microprocessors, and control the working status of the instrument; in off-line state, the program can preprocess experiment data, extract feature of diagnostic markers, and finally calculate the diagnosis result based on the diagnostic model.The third part includes clinical samples tests and results analysis based on this system. Cooperated with Sir Run Run Shaw Hospital, breath air as the clinical samples was collected from 42 lung cancer patients and 39 normal people, which were detected by the e-Nose. With former research results of lung cancer diagnostic biomarkers, diagnostics algorithm was proposed based on the instrument for lung cancer. Experimental result shows that the sensitivity to lung cancer is 83.3%, and the specificity is 82.1%, and this system already can be used for lung cancer detection, and it has a significant meaning for lung cancer screening and improving the rate of early diagnosis of lung cancer.