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In this study, it is aimed to determine the glycemia (blood sugar) level of the diabetics by analyzing the acetone odor participated in their breath (exhalation) with the help of QCM (Quartz Crystal Microbalnce) sensor based Electronic Nose. The level of acetone concentration in humans' breath is as low as 0, 1-10 ppm. In order low level acetone concentration to be sensed by the sensors, it is needed to concentrate the volatile organic compounds. Thus, a condenser containing chemical absorbent ingredients is used in the experiment mechanism. Thanks to this, high concentration is gained by detaining the breath sample that is carrying low acetone concentration within the condenser. The QCM sensor data is compared against glycemia (blood sugar) data in the study. The minimum error rate is 23,76% when the glycemia value is applied to Artificial Neural Network.