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Cho, Nayoung;Kim, Hyeongun;Kim, Jaegon;Baik, Byeongju;Yang, Yeonmi
- Journal of the korean academy of Pediatric Dentistry
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- v.42 no.3
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- pp.233-241
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- 2015
The aim of this study was to determine the bite force and lip closing force in preschool children and to analyze the correlation between these forces by age, height and weight, respectively. Data were obtained from 98 children (56 males, 42 females) ranging from 3 to 6 years of age. The magnitude of the bite force was measured bilaterally corresponding with the 2nd primary molars using a bite force gauge, $GM10^{(R)}$ (Nagano Keiki) and the force of lip closure was measured using LIP DE $CUM^{(R)}$ (Cosmo Instruments). The averages of bite force for boys and girls were 217.69 N and 205.05 N, respectively. The relationship between bite force with age, height, and weight present significant positive correlation (p < 0.001, p < 0.001, and p < 0.001, respectively). The averages of lip closing force for boys and girls were 4.81 N and 4.07 N respectively. The relationship between lip closing force with age, height, and weight present significant positive correlation (p < 0.001, p < 0.001, and p < 0.001, respectively). No significant differences were observed between boys and girls (p > 0.05) in both forces. A significant correlation was observed between lip closing force and bite force (p = 0.002).
https://doi.org/10.5933/JKAPD.2015.42.3.233 인용 PDF KSCI

김진옥;황대준;백경석;정진현
- The Journal of Korean Institute of Communications and Information Sciences
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- v.26 no.12A
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- pp.2067-2073
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- 2001
Biometric systems are forms of technology that use unique human physical characteristics to automatically identify a person. They have sensors to pick up some physical characteristics, convert them into digital patterns, and compare them with patterns stored for individual identification. However, lip-print recognition has been less developed than recognition of other human physical attributes such as the fingerprint, voice patterns, retinal at blood vessel patterns, or the face. The lip print recognition by a CCD camera has the merit of being linked with other recognition systems such as the retinal/iris eye and the face. A new method using multi-resolution architecture is proposed to recognize a lip print from the pattern kernels. A set of pattern kernels is a function of some local lip print masks. This function converts the information from a lip print into digital data. Recognition in the multi-resolution system is more reliable than recognition in the single-resolution system. The multi-resolution architecture allows us to reduce the false recognition rate from 15% to 4.7%. This paper shows that a lip print is sufficiently used by the measurements of biometric systems.
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