Arduino and Android-Based Anthropometric Detection Tools for Indonesian Children

Abstract

Current anthropometric measurements at Community Health Centers (CHC) by cadres and health workers in Indonesia are not completely accurate. This inaccuracy is influenced by errors when measuring, determining the age, the accuracy of cadres, and non-standard anthropometric measuring instruments. For this reason, it is necessary to design a more practical anthropometric detection tool of children's nutritional status for health practitioners and cadres, reducing the risk of mal diagnostic due to human error. It is very important to help the CHC for examination anthropometric measuring. The development life cycle system (DLCS) method, which includes planning, analysis, design, implementation, testing, and management applied to system design. This instrument was expected to be a standard solution for measuring the nutrition status of Indonesian children that was still conducted manually and separately. The design began with the identification of the child's weight and height, calibration and analysis of the function of the sensor, then the design process of the measuring instrument. At the trial stage, the data were displayed on the LCD. This series of activities used the Arduino nano R3, then data were sent to Bluetooth, and forwarded to the Android system. This study produced a detection system for children's nutritional status using body length/ age, weight/height, and bodyweight/age parameters. This android system produced nutritional status categories, namely normal, stunted, wasted, and underweight.