Title :
Wearable context-aware food recognition for calorie monitoring
Author :
Shroff, Geeta ; Smailagic, Asim ; Siewiorek, Daniel P.
Author_Institution :
Comput. Sci. Dept., Carnegie Mellon Univ., Pittsburgh, PA
fDate :
Sept. 28 2008-Oct. 1 2008
Abstract :
We propose DiaWear, a novel assistive mobile phone-based calorie monitoring system to improve the quality of life of diabetes patients and individuals with unique nutrition management needs. Our goal is to achieve improved daily semi-automatic food recognition using a mobile wearable cell phone. DiaWear currently uses a neural network classification scheme to identify food items from a captured image. It is difficult to account for the varying and implicit nature of certain foods using traditional image recognition techniques. To overcome these limitations, we introduce the role of the mobile phone as a platform to gather contextual information from the user and system in obtaining better food recognition.
Keywords :
biomedical communication; image recognition; medical computing; medical disorders; mobile computing; neural nets; patient monitoring; calorie monitoring; diabetes patient; image recognition technique; mobile phone; neural network classification scheme; nutrition management; wearable context-aware food recognition; Biomedical monitoring; Cellular phones; Computer science; Computerized monitoring; Diabetes; Image recognition; Neural networks; Patient monitoring; Probability; Remote monitoring;
Conference_Titel :
Wearable Computers, 2008. ISWC 2008. 12th IEEE International Symposium on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
978-1-4244-2637-9
DOI :
10.1109/ISWC.2008.4911602