research-article

BALANCE: towards a usable pervasive wellness application with accurate activity inference

Authors:

Tamara Denning,

Adrienne Andrew,

Rohit Chaudhri,

Jonathan Lester,

Gaetano Borriello,

Glen DuncanAuthors Info & Claims

HotMobile '09: Proceedings of the 10th workshop on Mobile Computing Systems and Applications

Article No.: 5, Pages 1 - 6

https://doi.org/10.1145/1514411.1514416

Published: 23 February 2009 Publication History

Abstract

Technology offers the potential to objectively monitor people's eating and activity behaviors and encourage healthier lifestyles. BALANCE is a mobile phone-based system for long term wellness management. The BALANCE system automatically detects the user's caloric expenditure via sensor data from a Mobile Sensing Platform unit worn on the hip. Users manually enter information on foods eaten via an interface on an N95 mobile phone. Initial validation experiments measuring oxygen consumption during treadmill walking and jogging show that the system's estimate of caloric output is within 87% of the actual value. Future work will refine and continue to evaluate the system's efficacy and develop more robust data input and activity inference methods.

References

[1]

American College of Sports Medicine. ACSM's guidelines for exercise testing and prescription. (M Whaley, senior editor, 7th ed.). Philadelphia, PA: Lippincott Williams & Wilkins; 2006.

[2]

S. A. A. Beresford, E. Locke, S. Bishop, B. West, B. A. McGregor, B. Bruemmer, G. E. Duncan, and B. Thompson. Worksite study promoting activity and changes in eating (PACE): design and baseline results. Obesity, 15(Suppl 1):4S--15S, 2007.

[3]

E. Brunner, D. Stallone, M. Juneja, S. Bingham, and M. Marmot. Dietary assessment in Whitehall II: comparison of 7 d diet diary and food-frequency questionnaire and validity against biomarkers. British Journal of Nutrition, 86:3, 405--14, 2001.

[4]

S. Consolvo, D. W. McDonald, T. Toscos, M. Y. Chen, J. Froehlich, B. Harrison, P. Klasnja, A. LaMarca, L. LeGrand, R. Libby, I. Smith, and J. A. Landay. Activity Sensing in the Wild: A Field Trial of UbiFit Garden. In Proceedings of the Twenty-sixth Annual SIGCHI Conference on Human Factors in Computing Systems (SIGCHI '08), pages 1797--1806, Florence, Italy, 2008.

Digital Library

[5]

DietTV.com. http://www.diettv.com/.

[6]

G. E. Duncan, S. J. Sydeman, M. G. Perri, M. C. Limacher, and A. D. Martin. Can sedentary adults accurately recall the intensity of their physical activity? Preventative Medicine, 33, 18--26, 2001.

[7]

Fitbit, Inc. http://www.fitbit.com/.

[8]

R. K. Ganti, P. Jayachandran, T. F. Abdelzaher, and J. A. Stankovic. Satire: A Software Architecture for Smart Attire. In Proceedings of the 4th International Conference on Mobile Systems, Application and Services, pages 110--123, Uppsala, Sweden, 2006.

Digital Library

[9]

P. Järvinen, T. H. Järvinen, L. Lähteenmäki, and C. Södergård. HyperFit: Hybrid Media in Personal Nutrition and Exercise Management. In Proceedings of the 2nd International Conference on Pervasive Computing Technologies for Healthcare, 2008.

[10]

G. Johansson, A. Wikman, A. M. Ahrn, G. Hallmans, and I. Johansson. Underreporting of energy intake in repeated 24-hour recalls related to gender, age, weight status, day of interview, educational level, reported food intake, smoking habits and area of living. Public Health Nutrition, 4(4), 919--27, 2001.

[11]

R. K. Johnson, B. A. Yon, and J. H. Hankin. Dietary Assessment and Validation. Research: Successful Approaches, Third Edition, 2008. American Dietetic Association.

[12]

C. H. Kaczkowski, P. J. H. Jones, J. Feng, and H. S. Bayley. Four-Day Multimedia Diet Records Underestimate Energy Needs in Middle-Aged and Elderly Women as Determined by Doubly-Labeled Water. Journal of Nutrition, 130:4, 802--805, 2000.

[13]

Keyoe, Inc. http://www.keyoe.com/.

[14]

J. Lester, T. Choudhury, and G. Borriello. A Practical Approach to Recognizing Physical Activities. In Proceedings of the Fourth International Conference on Pervasive Computing, Dublin, Ireland, 2006.

Digital Library

[15]

D. Mahler, V. Froelicher, N. Miller, and T. York. American College of Sports Medicine's Guidelines for Exercise Testing and Prescription. Williams & Wilkins, 1995.

[16]

U. Maurer, A. Smailagic, D. Siewiorek, and M. Deisher. Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions. In Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks (BSN '06), 2006.

Digital Library

[17]

Myca Nutrition. http://www.mycanutrition.com/.

[18]

Nokia. Wellness Diary. http://research.nokia.com/research/projects/WellnessDiary/index.html.

[19]

S. Reddy, A. Parker, J. Hyman, J. Burke, D. Estrin, and M. Hansen. Image Browsing, Processing, and Clustering for Participatory Sensing: Lessons from a DietSense Prototype. In Proceedings of the 4th Workshop on Embedded Sensor Networks (EmNets '07), pages 13--17, New York, NY, USA, 2007.

Digital Library

[20]

K. Siek, K. H. Connelly, Y. Rogers, P. Rohwer, D. Lambert, and J. L. Welch. When Do We Eat? An Evaluation of Food Items Input into an Electronic Monitoring Application. In Proceedings of the First International Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health), Innsbruck, Austria, 2006.

[21]

C. C. Tsai, G. Lee, F. Raab, G. J. Norman, T. Sohn, W. G. Griswold, and K. Patrick. Usability and Feasibility of PmEB: A Mobile Phone Application for Monitoring Real Time Caloric Balance. Mobile Networks and Applications, 12:2--3, 173--184.

Digital Library

[22]

D. Wang, M. Kogashiwa, and S. Kira. Development of a New Instrument for Evaluating Individuals' Dietary Intakes. Journal of the American Dietetic Association, 2006:20, 1588--1593, 2006.

[23]

K. Zhang, F. Pi-Sunyer, and C. Boozer. Improving Energy Expenditure Estimation for Physical Activity. Medicine and Science in Sports and Exercise, 2004.

Cited By

Bangamuarachchi WChamantha AMeegahapola LRuiz-Correa SPerera IGatica-Perez D(2022)Sensing Eating Events in Context: A Smartphone-Only ApproachIEEE Access10.1109/ACCESS.2022.317970210(61249-61264)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3179702
M. Silva LA. Epstein D(2021)Investigating Preferred Food Description Practices in Digital Food JournalingProceedings of the 2021 ACM Designing Interactive Systems Conference10.1145/3461778.3462145(589-605)Online publication date: 28-Jun-2021
https://dl.acm.org/doi/10.1145/3461778.3462145
Meegahapola LRuiz-Correa SRobledo-Valero VHernandez-Huerfano EAlvarez-Rivera LChenu-Abente RGatica-Perez D(2021)One More Bite? Inferring Food Consumption Level of College Students Using Smartphone Sensing and Self-ReportsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34481205:1(1-28)Online publication date: 30-Mar-2021
https://dl.acm.org/doi/10.1145/3448120
Show More Cited By

Index Terms

BALANCE: towards a usable pervasive wellness application with accurate activity inference
1. Applied computing
  1. Life and medical sciences
    1. Consumer health
    2. Health informatics

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cover image ACM Conferences

HotMobile '09: Proceedings of the 10th workshop on Mobile Computing Systems and Applications

February 2009

90 pages

ISBN:9781605582832

DOI:10.1145/1514411

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 February 2009

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National Institutes of Health

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HotMobile 09

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SIGMOBILE

HotMobile 09: Tenth Workshop on Mobile Computing Systems and Applications

February 23 - 24, 2009

California, Santa Cruz

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Overall Acceptance Rate 96 of 345 submissions, 28%

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The 26th International Workshop on Mobile Computing Systems and Applications

February 26 - 27, 2025

Palm Springs , CA , USA

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Cited By

Bangamuarachchi WChamantha AMeegahapola LRuiz-Correa SPerera IGatica-Perez D(2022)Sensing Eating Events in Context: A Smartphone-Only ApproachIEEE Access10.1109/ACCESS.2022.317970210(61249-61264)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3179702
M. Silva LA. Epstein D(2021)Investigating Preferred Food Description Practices in Digital Food JournalingProceedings of the 2021 ACM Designing Interactive Systems Conference10.1145/3461778.3462145(589-605)Online publication date: 28-Jun-2021
https://dl.acm.org/doi/10.1145/3461778.3462145
Meegahapola LRuiz-Correa SRobledo-Valero VHernandez-Huerfano EAlvarez-Rivera LChenu-Abente RGatica-Perez D(2021)One More Bite? Inferring Food Consumption Level of College Students Using Smartphone Sensing and Self-ReportsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34481205:1(1-28)Online publication date: 30-Mar-2021
https://dl.acm.org/doi/10.1145/3448120
Mamykina LM. Smaldone AR. Bakken SElhadad NG. Mitchell EM. Desai PE. Levine MN. Tobin JCassells AG. Davidson PJ. Albers DHripcsak G(2021)Scaling Up HCI Research: from Clinical Trials to Deployment in the Wild.Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411763.3443437(1-6)Online publication date: 8-May-2021
https://dl.acm.org/doi/10.1145/3411763.3443437
Nair SJavkar KWu JFrias-Martinez V(2019)Understanding Cycling Trip Purpose and Route Choice Using GPS Traces and Open DataProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33144073:1(1-26)Online publication date: 29-Mar-2019
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Zhang HSong CWang AXu CLi DXu WAgarwal SGreenstein BBalasubramanian AGollakota SZhang X(2019)PDVocalThe 25th Annual International Conference on Mobile Computing and Networking10.1145/3300061.3300125(1-16)Online publication date: 5-Aug-2019
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Kounadi OResch B(2018)A Geoprivacy by Design Guideline for Research Campaigns That Use Participatory Sensing DataJournal of Empirical Research on Human Research Ethics10.1177/155626461875987713:3(203-222)Online publication date: 23-Apr-2018
https://doi.org/10.1177/1556264618759877
Poncha LAbdelhamid SAlturjman SEver EAl-Turjman F(2018)5G in a Convergent Internet of Things Era: An Overview2018 IEEE International Conference on Communications Workshops (ICC Workshops)10.1109/ICCW.2018.8403748(1-6)Online publication date: May-2018
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Heydary MPimpale PPanangadan A(2018)Automatic Identification of Use of Public Transportation from Mobile Sensor Data2018 IEEE Green Technologies Conference (GreenTech)10.1109/GreenTech.2018.00042(189-196)Online publication date: Apr-2018
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Liu YWang YWang XXia ZXu J(2018)Privacy-Preserving Data Collection for Mobile Phone Sensing TasksInformation Security Practice and Experience10.1007/978-3-319-99807-7_32(506-518)Online publication date: 6-Sep-2018
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