An exploratory study on a chest-worn computer for evaluation of diet, physical activity and lifestyle.

Recently, wearable computers have become new members in the family of mobile electronic devices, adding new functions to those provided by smart-phones and tablets. As "always-on" miniature computers in the personal space, they will play increasing roles in the field of healthcare. In this work, we present our development of eButton, a wearable computer designed as a personalized, attractive, and convenient chest pin in a circular shape. It contains a powerful microprocessor, numerous electronic sensors, and wireless communication links. We describe its design concepts, electronic hardware, data processing algorithms, and its applications to the evaluation of diet, physical activity and lifestyle in the study of obesity and other chronic diseases.

[1]  I-Min Lee,et al.  Using accelerometers to measure physical activity in large-scale epidemiological studies: issues and challenges , 2013, British Journal of Sports Medicine.

[2]  Mingui Sun,et al.  Segmentation for efficient browsing of chronical video recorded by a wearable device , 2010, Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference (NEBEC).

[3]  Stephen M Rappaport,et al.  Environment and Disease Risks , 2010, Science.

[4]  S. Rappaport Implications of the exposome for exposure science , 2011, Journal of Exposure Science and Environmental Epidemiology.

[5]  F. Collins,et al.  Potential etiologic and functional implications of genome-wide association loci for human diseases and traits , 2009, Proceedings of the National Academy of Sciences.

[6]  N J Wareham,et al.  The assessment of physical activity in individuals and populations: why try to be more precise about how physical activity is assessed? , 1998, International journal of obesity and related metabolic disorders : journal of the International Association for the Study of Obesity.

[7]  Mingui Sun,et al.  Accuracy of food portion size estimation from digital pictures acquired by a chest-worn camera , 2013, Public Health Nutrition.

[8]  K. Janz,et al.  Physical activity in epidemiology: moving from questionnaire to objective measurement , 2006, British Journal of Sports Medicine.

[9]  Craig Gotsman,et al.  D-Snake: Image Registration by As-Similar-As-Possible Template Deformation , 2013, IEEE Transactions on Visualization and Computer Graphics.

[10]  Zhen Li,et al.  Daily life event segmentation for lifestyle evaluation based on multi-sensor data recorded by a wearable device , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[11]  Zhi-Hong Mao,et al.  Automatic detection of dining plates in digital video , 2010, Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference (NEBEC).

[12]  Mingui Sun,et al.  Eating activity detection from images acquired by a wearable camera , 2013, SenseCam '13.

[13]  Mingui Sun,et al.  Model-based measurement of food portion size for image-based dietary assessment using 3D/2D registration , 2013, Measurement science & technology.

[14]  Walter C Willett,et al.  Balancing Life-Style and Genomics Research for Disease Prevention , 2002, Science.

[15]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[16]  K. Flegal,et al.  Prevalence and trends in obesity among US adults, 1999-2008. , 2010, JAMA.

[17]  E J Delp,et al.  Use of technology in children’s dietary assessment , 2009, European Journal of Clinical Nutrition.

[18]  J. Kaprio,et al.  Environmental and heritable factors in the causation of cancer--analyses of cohorts of twins from Sweden, Denmark, and Finland. , 2000, The New England journal of medicine.

[19]  E. Delp,et al.  Novel Technologies for Assessing Dietary Intake: Evaluating the Usability of a Mobile Telephone Food Record Among Adults and Adolescents , 2012, Journal of medical Internet research.

[20]  Zhi-Hong Mao,et al.  Helping the blind to find the floor of destination in multistory buildings using a barometer , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[21]  Zhengyou Zhang,et al.  Flexible camera calibration by viewing a plane from unknown orientations , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[22]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[23]  Yael Pritch,et al.  Saliency filters: Contrast based filtering for salient region detection , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[24]  David R Bassett,et al.  2011 Compendium of Physical Activities: a second update of codes and MET values. , 2011, Medicine and science in sports and exercise.

[25]  E. Delp,et al.  Comparison of Known Food Weights with Image-Based Portion-Size Automated Estimation and Adolescents' Self-Reported Portion Size , 2012, Journal of diabetes science and technology.

[26]  Ross A Hammond,et al.  The economic impact of obesity in the United States , 2010, Diabetes, metabolic syndrome and obesity : targets and therapy.

[27]  T. Baranowski,et al.  Comparison of a Web-based versus traditional diet recall among children. , 2012, Journal of the Academy of Nutrition and Dietetics.

[28]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[29]  S. Marshall,et al.  Using the SenseCam to improve classifications of sedentary behavior in free-living settings. , 2013, American journal of preventive medicine.

[30]  B E Ainsworth,et al.  Compendium of physical activities: an update of activity codes and MET intensities. , 2000, Medicine and science in sports and exercise.

[31]  Mingui Sun,et al.  Automatic detection of dining plates for image-based dietary evaluation , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[32]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[33]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.