Preliminary study of Data Mining analysis of high speed Kymography and voice data

The use of high-speed laryngeal images technology contributes increasingly to promote greater objectivity in the characterization of laryngeal physiology, as well as, in the diagnosis and monitoring of laryngeal diseases. Vocal fold paralysis is still an unknown incidence, both in Brazil and in the rest of the World, its occurrence has become more frequent in medical and speech-pathologist clinics. Data mining is the process of analyzing hidden patterns of data according to different perspectives for categorization into useful information. In other words, Data Mining is able to identify patterns between information and grouping them according to some given criteria. Objective: To analyze high-speed kymographic images and voice signals with and without unilateral vocal fold paralysis using the data mining computerized system DAMICORE. Methodology: High-speed kymography and acoustic voice signals of subjects with and without unilateral vocal fold paralysis were analyzed by a computerized data mining tool, the DAMICORE system. Results: Data mining analysis for High-speed kymography of healthy individuals gather the groups by sex, while images from subjects with unilateral vocal fold paralysis were gathered by contrast of colors and by light incidence in the images. For voice signals, the technique considered the presence of external noise as a criterion for gathering groups. Conclusion: We concluded that DAMICORE it is a promising tool for kymographic images and voice signal data mining analysis. This tool shown high sensibility to noise in acoustical signals. Consequently, future research should consider this characteristic.