Artificial Intelligence in Medicine
Volume 42, Issue 2 , Pages 121-136 , February 2008

Recognition of dietary activity events using on-body sensors

Received 20 November 2006 ,Revised 20 November 2007 ,Accepted 21 November 2007.

References 

  1. WHO, Global strategy on diet, physical activity and health (WHA57.17), in: Fiftyseventh World Health Assembly, World Health Organization; 2004.
  2. Sjöberg A, Hallberg L, Höglund D, Hulthen L. Meal pattern, food choice, nutrient intake and lifestyle factors in the Göteborg Adolescence Study. Eur J Clin Nutr. 2003;57(12):1569–1578
  3. Rolls BJ, Drewnowski A, Ledikwe JH. Changing the energy density of the diet as a strategy for weight management. J Am Diet Assoc. 2005;105(5 Suppl. 1):S98–S103
  4. MyFoodPhone, World’s first camera-phone & web-based-video nutrition service. Internet: accessed on August 2007 (Feb 2005).
  5. Beidler J, Insogna A, Cappobianco N, Bi Y, Borja M. The PNA project. J Comput Sci Colleges. 2001;16(4):276–284
  6. Mankoff J, Hsieh G, Hung HC, Lee S, Nitao E. Using low-cost sensing to support nutritional awareness. In: Goos G, Hartmanis J, van Leeuwen J, editors. Ubicomp 2002: Proceedings of the 4th International Conference on Ubiquitous Computing, vol. 2498 of Lecture Notes in Computer Science, Springer Berlin, Heidelberg; 2002. p. 371–6.
  7. Siek KA, Connelly KH, Rogers Y, Rohwer P, Lambert D, Welch JL. When do we eat? an evaluation of food items input into an electronic food monitoring application. In: Aarts E, Kohno R, Lukowicz P, Trainini JC, editors, PHC 2006: Proceedings of the 1st International Conference on Pervasive Computing Technologies for Healthcare, ICST, IEEE digital library; 2006. p. 1–10.
  8. Stone AA, Shiffman S, Schwartz JE, Broderick JE, Hufford MR. Patient non-compliance with paper diaries. Brit Med J. 2002;324(7347):1193–1194
  9. Westerterp-Plantenga MS. Eating behavior in humans, characterized by cumulative food intake curves—a review. Neurosci Biobehav Rev. 2000;24(2):239–248
  10. Kissileff HR, Klingsberg G, Itallie TBV. Universal eating monitor for continuous recording of solid or liquid consumption in man. Am J Physiol. 1980;238(1):R14–R22
  11. Stellar E, Shrager EE. Chews and swallows and the microstructure of eating. Am J Clin Nutr. 1985;42(5 Suppl):973–982
  12. Chang K-H, Liu S-Y, Chu H-H, Hsu JY, Chen C, Lin T-Y, etal. The diet-aware dining table: observing dietary behaviors over a tabletop surface. In: Fishkin K, Schiele B, Nixon P, Quigley A, editors. PERVASIVE 2006: Proceedings of the 4th International Conference on Pervasive Computing, vol. 3968 of Lecture Notes in Computer Science, Springer Berlin, Heidelberg; 2006. p. 366–82.
  13. Schmidt A, Strohbach M, van Laerhoven K, Friday A, Gellersen H-W, Context acquisition based on load sensing. In: Goos G, Hartmanis J, van Leeuwen J, editors. Ubicomp 2002: Proceedings of the 4th international conference on Ubiquitous Computing, vol. 2498 of Lecture Notes in Computer Science, Springer Berlin, Heidelberg; 2002. p. 333–50.
  14. Beigl M, Gellersen H-W, Schmidt A. MediaCups: experience with design and use of computer-augmented everyday artefacts. Comp Network. 2001;35(4):401–409(special issue on pervasive computing)
  15. Patterson D, Fox D, Kautz H, Philipose M, Fine-grained activity recognition by aggregating abstract object usage. In: Rhodes B, Mase K, editors. ISWC 2005: Proceedings of the Ninth IEEE International Symposium on Wearable Computers, IEEE Press; 2005. p. 44–51.
  16. Chambers S, Venkatesh S, West G, Bui H. Hierarchical recognition of intentional human gestures for sports video annotation. In: Kasturi R, Laurendeau D, Suen C, editors. Proceedings of the 16th International Conference on Pattern Recognition, vol. 2, IEEE Press; 2002. p. 1082–5.
  17. Ogris G, Stiefmeier T, Junker H, Lukowicz P, Troster G. Using ultrasonic hand tracking to augment motion analysis based recognition of manipulative gestures. In: Rhodes B, Mase K. editors. ISWC 2005: Proceedings of the Ninth IEEE International Symposium on Wearable Computers, IEEE Press; 2005. p. 152–9.
  18. Lee H-K, Kim JH. An HMM-based threshold model approach for gesture recognition. IEEE Trans Pattern Anal Machine Intel. 1999;21(10):961–973
  19. Ward J, Lukowicz P, Tröster G, Starner T. Activity recognition of assembly tasks using body-worn microphones and accelerometers. IEEE Trans Pattern Anal Machine Intel. 2006;28(10):1553–1567
  20. Lee C, Yangsheng X. Online, interactive learning of gestures for human/robot interfaces. In: Caplan N, Lee CG, editors. ICRA 1996: Proceedings of the IEEE International Conference on Robotics and Automation, vol. 4 of IEEE Robotics and Automation Society, IEEE Press; 1996. p. 2982–7.
  21. Amft O, Junker H, Tröster G. Detection of eating and drinking arm gestures using inertial body-worn sensors. In: Rhodes B, Mase K. editors. ISWC 2005: IEEE Proceedings of the Ninth International Symposium on Wearable Computers, IEEE Press; 2005. p. 160–3.
  22. Vickers ZM. The relationships of pitch, loudness and eating technique to judgments of the crispness and crunchiness of food sounds. J Text Stud. 1985;16(1):85–95
  23. Dacremont C, Colas B, Sauvageot F. Contribution of air- and bone-conduction to the creation of sounds perceived during sensory evaluation of foods. J Text Stud. 1991;22(4):443–456
  24. AlChakra W, Allaf K, Jemai A. Characterization of brittle food products: Application of the acoustical emission method. J Text Stud. 1996;27(3):327–348
  25. Edmister J, Vickers Z. Instrumental acoustical measures of crispness in foods. J Text Stud. 1985;16(2):153–167
  26. Drake B. Food crushing sounds. an introductory study. J Food Sci. 1963;28(2):233–241
  27. DeBelie N, De Smedt V. Principal component analysis of chewing sounds to detect differences in apple crispness. J Postharvest Biol Technol. 2000;18:109–119
  28. DeBelie N, Sivertsvik M, DeBaerdemaeker J. Differences in chewing sounds of dry-crisp snacks by multivariate data analysis. J Sound Vibrat. 2003;266(3):625–643
  29. Amft O, Stäger M, Lukowicz P, Tröster G. Analysis of chewing sounds for dietary monitoring. In: Beigl M, Intille S, Rekimoto J, Tokuda H. editors. UbiComp 2005: Proceedings of the 7th International Conference on Ubiquitous Computing., vol. 3660 of Lecture Notes in Computer Science, Springer Berlin, Heidelberg; 2005. p. 56–72.
  30. Ertekin C, Aydogdu I. Neurophysiology of swallowing. Clin Neurophysiol. 2003;114(12):2226–2244
  31. Denk DM, Swoboda H, Steiner E. Physiology of the larynx. Der Radiol. 1998;38(2):63–70in German
  32. Gupta V, Reddy NP, Canilang EP. Surface EMG measurements at the throat during dry and wet swallowing. Dysphagia. 1996;11(3):173–179
  33. Logan WJ, Kavanagh JF, Wornall AW. Sonic correlates of human deglutition. J Appl Physiol. 1967;23(2):279–284
  34. Cichero JAY, Murdoch BE. Detection of swallowing sounds: methodology revisited. Dysphagia. 2002;17(1):40–49
  35. Danbolt C, Hult P, Grahn LT, Ask P. Validation and characterization of the computerized laryngeal analyzer (CLA) technique. Dysphagia. 1999;14(4):191–195
  36. Limdi A, McCutcheon M, Taub E, Whitehead W, Cook I, EW, Design of a microcontroller-based device for deglutition detection and biofeedback. In: EMBS 1989: Proceedings of the Annual International Conference of the IEEE Engineering in Engineering in Medicine and Biology Society, vol. 5, IEEE Press; 1989. p. 1393–4.
  37. Sukthankar SM, Reddy NP, Canilang EP, Stephenson L, Thomas R. Design and development of portable biofeedback systems for use in oral dysphagia rehabilitation. Med Eng Phys. 1994;16(5):430–435
  38. Amft O, Tröster G. Methods for detection and classification of normal swallowing from muscle activation and sound. In: Aarts E, Kohno R, Lukowicz P, Trainini JC. editors. PHC 2006: Proceedings of the First International Conference on Pervasive Computing Technologies for Healthcare, ICST, IEEE digital library; 2006. p. 1–10.
  39. Ho TK, Hull J, Srihari S. Decision combination in multiple classifier systems. IEEE Trans Pattern Anal Machine Intel. 1994;16(1):66–75
  40. Bannach D, Amft O, Kunze KS, Heinz EA, Tröster G, Lukowicz P. Waving real hand gestures recorded by wearable motion sensors to a virtual car and driver in a mixed-reality parking game. In: Blair A, Cho S-B, Lucas SM. editors. CIG 2007: Proceedings of the 2nd IEEE Symposium on Computational Intelligence and Games, IEEE Press; 2007. p. 32–9.
  41. Ward JA, Lukowicz P, Tröster G. Evaluating performance in continuous context recognition using event-driven error characterisation. In: Hazas M, Krumm J, Strang T. (Eds.), LoCA 2006: Proceedings of the Second International Workshop on Location- and Context-Awareness, vol. 3987 of Lecture Notes in Computer Science, Springer, Berlin/Heidelberg; 2006. p. 239–55.
  42. Amft O, Kusserow M, Tröster G. Automatic identification of temporal sequences in chewing sounds. In: Hu T, Mandoiu I, Obradovic Z. editors. BIBM2007: Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, IEEE Press, San Jose, CA, USA; 2007. p. 194–201.

PII: S0933-3657(07)00147-9

doi: 10.1016/j.artmed.2007.11.007

Artificial Intelligence in Medicine
Volume 42, Issue 2 , Pages 121-136 , February 2008

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