ABSTRACT
Obesity is a growing healthcare challenge in present days. Objective automated methods of food intake monitoring are necessary to face this challenge in future. A method for non-invasive monitoring of human food intake behavior by the evaluation of chewing and swallowing sounds has been developed. A wearable food intake sensor has been created by integrating in-ear microphone and a reference microphone in a hearing aid case. A concept for food intake monitoring requiring low computational cost is presented. After the detection of food intake activity periods, signal recognition algorithms based on Hidden Markov Models distinguish several types of food based on the sound properties of their chewing sounds. Algorithms are developed using manual labeled records of the food intake sounds of 40 participants.
- Amft, O. 2008. Automatic dietary monitoring using on-body sensors - Detection of eating and drinking behaviour in healthy individuals. Doctoral Thesis. ETH Zurich.Google Scholar
- Beasley, J. 2007. The pros and cons of using pdas for dietary self-monitoring. J. Am. Diet Assoc., Res. 107 (2007), 739.Google ScholarCross Ref
- Chang, K.-H., Liu, S.-Y., Chu, H.-H., Hsu, J. Y., Chen, C., Lin, T.-Y., Chen, C.-Y. and Huang, P. (2006). The diet-aware dining table: Observing dietary behaviors over a tabletop surface. In PERVASIVE 2006: Proceedings of the 4th International Conference on Pervasive Computing, vol. 3968 of Lecture Notes in Computer Science (Dublin, Ireland, May 07--10, 2006). Springer Berlin, Heidelberg. 366--382. Google ScholarDigital Library
- Drake, B. 1963. Food crushing sounds. an introductory study, J. Food Sci., Res. 28 (1963), 233--241.Google Scholar
- Hoffmann, R., Eichner, M. and Wolff, M. 2007. Analysis of Verbal and Nonverbal Acoustic Signals with the Dresden UASR System. In Verbal and Nonverbal Communication Behaviours, A. Esposito, M. Faundez-Zanuy, E. Keller, M. Marinaro, Eds. Springer, Heidelberg. Google ScholarDigital Library
- Lee III, W. E., Deibel, A. E., Glembin, C. T. and Munday, E. G. 1988. Analysis of Food Crushing Sound During Mastication: Frequency-Time Studies. J. Texture Stud. Res. 19 (1988), 27--38.Google Scholar
- Lopez-Meyer, P., Schuckers, S., Makeyev, O. and Sazonov, E. (2010). Detection of Periods of Food Intake using Support Vector Machines. In 32nd Annual International Conference of the IEEE EMBS (Buenos Aires, Argentinia, September 4 2010). 1004--1007.Google ScholarCross Ref
- Päßler, S. and Fischer, W.-J., "Acoustical Method for Objective Food Intake Monitoring Using a Wearable Sensor System". In Proceedings of the 5th International Conference on Pervasive Computing Technologies for Healthcare (Dublin, Ireland, May 23--26, 2011). In press.Google ScholarCross Ref
- Päßler, S. and Fischer, W.-J., "Food Intake Activity Detection Using a Wearable Microphone System". In Proceedings of the 7th International Conference on Intelligent Environments -- IE'11 (Nottingham, UK, July 25--28, 2011). In press. Google ScholarDigital Library
- Schoeller, D. A. 1995. Limitations in the assessment of dietary energy intake by self-report. Metabolism, Res. 44, 18--22.Google ScholarCross Ref
- Shuzo, M., Komori, S., Takashima, T., Lopez, G., Tatsuta, S., Yanagimoto, S., Warisawa, S., Delaunay J.-J. and Yamada, I. 2009. Wearable Eating Habit Sensing Using Sound Information. In Proceedings of the 2009 Conference on Micromechatronics for Information and Precision Equipment (Ibaraki, Japan, June 17--20, 2009). MIPE 2009. 221--222.Google Scholar
- Wolf A. M. and Colditz G. A. 1998. Current estimates of the economic cost of obesity in the United States. Obes. Res. 6 (1998), 97--106.Google ScholarCross Ref
- World Health Organization 2006. Obesity and overweight: What are overweight and obesity?. Fact sheet N°311, WHO.Google Scholar
Index Terms
- Food intake recognition conception for wearable devices
Recommendations
Food Intake Activity Detection Using a Wearable Microphone System
IE '11: Proceedings of the 2011 Seventh International Conference on Intelligent EnvironmentsA method for non-invasive monitoring of human food intake behavior and long-term dietary protocol has been developed by the sole use of chewing and swallowing sound sensors. A novel sensor system has been built containing an in-ear microphone and a ...
Adaptive implicit interaction for healthy nutrition and food intake supervision
HCII'11: Proceedings of the 14th international conference on Human-computer interaction: towards mobile and intelligent interaction environments - Volume Part IIIThe current work is going to provide you information about our solution in the challenge of nutrition and food intake supervision, which has been developed lately. We will give an overview of the system and the implemented mechanisms, which were needed ...
Adaptation of Models for Food Intake Sound Recognition Using Maximum a Posteriori Estimation Algorithm
BSN '12: Proceedings of the 2012 Ninth International Conference on Wearable and Implantable Body Sensor NetworksObesity and overweight are big healthcare challenges in the world's population. Automatic food intake recognition algorithms based on analysis of food intake sounds offer the potential of being a useful tool for simplifying data logging of consumed ...
Comments