Title :
A Framework for Healthcare Everywhere: BMI Prediction Using Kinect and Data Mining Techniques on Mobiles
Author :
Tai, Chih-Hua ; Lin, Daw-Tung
Abstract :
Recently, health-care has become a popular issue. Having a good physique is also commonly regarded as important for being healthy. For evaluating our body status, the Body Mass Index (BMI) is a widely used indicator. However, calculating BMI is inconvenient and requires the physical measuring of people´s weights and heights. In this paper, we are interested in building a mobile-based BMI prediction system using Kinect and data mining techniques so that everybody can easily monitor their BMI everywhere by taking a snapshot of their face. The rationale behind this is the intuition that there is a correlation between the shape of one´s face and one´s BMI values, which people often act on when noticing a friend has either gained or lost weight. Through the evaluations of 50 volunteers, we show that the rules for training BMI prediction match with people´s common intuitions.
Keywords :
Data mining; Decision trees; Face; Face recognition; Facial features; Feature extraction; Indexes; BMI; Kinect; data mining; face feature extraction;
Conference_Titel :
Mobile Data Management (MDM), 2015 16th IEEE International Conference on
Conference_Location :
Pittsburgh, PA, USA
Print_ISBN :
978-1-4799-9971-2
DOI :
10.1109/MDM.2015.40