Activity-based nutrition management model for healthcare using similar group analysis

Abstract

BACKGROUND: Due to environmental factors such as nutrient intake imbalance, lack of exercise, and increased stress, it is necessary to control nutrition in order to prevent diseases and provide treatment in terms of healthcare. OBJECTIVE: This study proposes the activity-based nutrition management model with the use of the cluster analysis of similar group for healthcare. METHODS: The proposed method is to conduct the cluster analysis of similar group for nutrition management and to develop the real-time activity information based nutrition management algorithm with the use of big data in order to improve the quality of healthcare management service. It is to re-process an existing nutrition database and add voice recognition function in line with the service so as to improve convenience of intake-food inputs. In addition, the Bluetooth Low Energy (BLE) communication based standard collection of bio signals occurring in real-time is developed. This study also proposes the method of improving an existing algorithm of drawing a daily recommended allowance with the use of real-time activity information, and the proposed service provides the essential information of nutrition management with the use of public big data. RESULTS: To verify the developed technology and service model and its effectiveness, the nutrition management service system is designed and developed with human interface. CONCLUSIONS: The developed health model helps to solve the obesity problem, save medical costs, and address the issue of national health.