Monitoring The Children’s Health Status and Forecasting Height with Nutritional Advice
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Children’s health is interesting to parents and society. A system that assists to monitor the development of their children and gives nutritional advices is an interesting of parents. In this study, we present a system that allows to track the heights and weights of a child since he/she was born up to adulthood, to predict his age of puberty, and to provide nutritional advice. Particularly, it predicts the height in near future and the adult stature for detecting the child with abnormal development. We applied Sager’s model for predicting the height in near future by using interpolation and regression techniques before puberty. After determining the puberty time, we proposed a model for predicting the height. Then we applied fuzzy logic for evaluating the health status and providing nutritional advice. Our system predicted stature in near future with error bound of 1.7361±0.0397 cm in girls and 2.4020±0.0799 cm in boys. Our model also gave a reliable adult stature prediction with error bound of 0.3507±0.2808 cm in girls and 1.3414±0.7024 cm in boys. At the same time, the nutrition was provided appropriately in terms of protein, lipid, glucid. We implemented a program based on this research. Our system promises to improve the health of every child.
Abstract
Children’s health is interesting to parents and society. A system that assists to monitor the development of their children and gives nutritional advices is an interesting of parents. In this study, we present a system that allows to track the heights and weights of a child since he/she was born up to adulthood, to predict his age of puberty, and to provide nutritional advice. Particularly, it predicts the height in near future and the adult stature for detecting the child with abnormal development. We applied Sager’s model for predicting the height in near future by using interpolation and regression techniques before puberty. After determining the puberty time, we proposed a model for predicting the height. Then we applied fuzzy logic for evaluating the health status and providing nutritional advice. Our system predicted stature in near future with error bound of 1.7361±0.0397 cm in girls and 2.4020±0.0799 cm in boys. Our model also gave a reliable adult stature prediction with error bound of 0.3507±0.2808 cm in girls and 1.3414±0.7024 cm in boys. At the same time, the nutrition was provided appropriately in terms of protein, lipid, glucid. We implemented a program based on this research. Our system promises to improve the health of every child.
참고문헌 (22)
- T. Onat, "Prediction of adult height of girls based on the percentage of adult height at onset of secondary sexual characteristics, at chronological age, and skeletal age", Hum Biol, 47, pp.117~130 (1975)
- J. Tanner, "Prediction of adult height, bone age, and occurrence of menarche, at ages 4 to 16 with allowance for midparent height", Arch Dis Child, 50, pp.14~26 (1975)[DOI]
- A. Roche, "Non-invasive measurements of physical maturity in children", Res Q Exerc Sport, (54), pp.364~371 (1983)[DOI]
- B. Lauren, "Prediction of Adult Height Using MaturityBased Cumulative Height Velocity Curves", The Journal of Pediatrics, 147, pp.508~514 (2005)[DOI]
- J. Tanner, "Assessment of skeletal maturity and prediction of adult height" (1983), Academic Press
- J. Tanner, "Assessment of skeletal maturity and prediction of adult height (TW2 Method)" (2001)
- A. Yurii, "Predicting human height by Victorian and genomic methods", European Journal of Human Genetics, 17, pp.1070~1075 (2009)[DOI]
- L. Sherar, "Prediction of adult height using maturity-based cumulative height velocity curves", The Journal of Pediatrics, 147(4), pp.508~514 (2005)[DOI]
- G. Sager, "Mathematical considerations concerning the height", weight tables of Maaser, 1981, pp.149(4), 345~356
- D. Frankenfield, "Comparision of preditive equation for resting metabolic rate in healthy nonobese and obese adults: A systematic review", Journal of the Academy of Nutrition and Dieretics, 105, pp.775~789 (2005)[DOI]
- height-for-age, weight-forage, weight-for-length, weight-for-height and body mass index-for-age: methods and development, "Child Growth Standards: length", pp.2006, World Health Organization
- H. Mamdani, "Application of fuzzy logic to approximate reasoning using linguistic synthesis", IEEE Transactions on Computers, 26, pp.1182~1191 (1977)
- [URL]
- H. Khamis, "Predicting adult stature without using skeletal age: the Khamis-Roche method", Pediatrics, 94, pp.504~507 (1994)
- N. Bayley, "Tables for predicting adult height from skeletal age: revised for use with Greulich-Pyle hand standards", J Pediatr, 40, pp.423~441 (1952)[DOI]
- A. Roche, "The RWT method for the prediction of adult stature", Pediatrics, 56, pp.1026~1033 (1975)
- Physical Status: the use and interpretation of anthropometry;WHO Technical Report Series 854, "World Health Organization", ~ (1995)
- S. Zaman, "A proposed air-conditioning system using fuzzy algorithm for industrial application", TENCON 2005 IEEE Region, 10, pp.1~6 (2005)
- L. A. Zadeh, "The concept of linguistic variable and its application to approximate reasoning (I)", Information Sciences, 8, pp.199~249 (1975)[DOI]
- L. A. Zadeh, "The concept of linguistic variable and its application to approximate reasoning (II)", Information Sciences, 8, pp.310~357 (1975)[DOI]
- L. A. Zadeh, "The concept of linguistic variable and its application to approximate reasoning (III)", Information Sciences, 9, pp.43~80 (1975)[DOI]
- K. Rajani, "Air Conditioning System with Fuzzy Logic and Neuro-Fuzzy Algorithm", Advances in Intelligent Systems and Computing, 236, pp.233~242 (2014)[DOI]