**6. Conclusion**

Our study focuses on the development of the multi-sensor scanning system, that aims to be the future pre-diagnostic tool for obstructive sleep apnea diagnostics. Because the obstructive sleep apnea syndrome can correspond with some abnormalities in cranio-facial parameters on the head, 3D scanning of head can be a promising procedure to obtain an automated method for OSAS screening. A system for early screening can easily prioritize the patients for complex diagnostics and then for early therapy. Especially in Slovakia, the waiting periods for conventional OSAS diagnostic can be several months.

RGB-D sensors are relatively non-expensive sensors with increasing popularity used in many fields: from entertainment to mechanical engineering or medical applications. To complete the 3D scanning system for biomedical use, the main research was focused on the selection of suitable RGB-D sensor for obtaining the accurate model of the head and neck. This model can be used for noninvasive automated procedures. After selecting the representative for all technologies of RGB-D sensors

we used some metrics, which can compare their accuracy. The noise measurement, the ideal point cloud fitting, and ideal plane fitting were selected for this assessment.

After the series of experiments, we can say that the difference in accuracy between the all sensors is not so significant and all of them could be used for our implementation. On the other hand, considering the second condition – multi-sensor parallel system – the mutual interference of sensors must be taken into the account. Because ToF sensors and also SLS sensors interfere and can generate interference artifacts, we focused on stereo pair technology of RGB-D sensors. Finally, we selected the active stereo pair Intel RealSense D415. Based on depth error, the optimal distance of the sensor from object is set to 0.5 m. The system with 3 sensors respects this distance.

The scanning system is driven by a web-based application with simple graphical user interface. 3D scans can be extended by information from a digitized EU sleep questionnaire. The database of 3D models with information form questionnaire is strictly needed to build an automated diagnostic system based on machine learning or artificial intelligence. These methods are now state of the art in many imaging and signal processing tasks. System is now implemented in clinical environment to obtain first elements of the dataset.

Further research can be oriented for selecting and implementing the filtration methods for obtained data, registration methods for partial models from single sensors, and calibration algorithms for the case of changes in sensor layout.
