‘Let’s Exercise’: A Context Aware Mobile Agent for Motivating Physical Activity

  • Saurav Gupta
  • Sanjay P. Sood
  • D. K. Jain
Conference paper


Context-aware Computing, considered as a part of ubiquitous computing, is an upcoming technology that has the potential to be used for improving one’s own health and providing personalized healthcare services. This paper discusses a randomized controlled trial conducted amongst 97 individuals, who were screened for stress and obesity. Out of these, 33 individuals (n = 33) were identified as suffering from both stress and obesity. With the fact that physical activity acts as a catalyst in reducing stress and obesity, the mobile application, ‘Let’s Exercise’ was designed to send context-aware alerts to the users. These alerts motivated and recommended these users to take up physical activity depending upon their operating environment. The 33 users were subject to a four-week observational period, after which a positive behavioral change was observed amongst these individuals. This was due to the increase in the level of physical activity in their daily routines after receiving the contextual alerts. Post the study, the users also showed strong confidence and willingness in the adoption of this technology.


Context awareness Computer to physical environment interaction Computer to human interaction Ubiquitous computing mHealth 


  1. 1.
    Vrbaski, M., Petriu, D.: Toward a context awareness framework for healthcare applications. In: IEEE International Symposium on Medical Measurements and Applications Proceedings (MeMeA), doi: 10.1109/MeMeA.2013.6549764, May 2013
  2. 2.
    Gardini, M. et al.: Clariisa, a Context-Aware Framework Based on Geolocation for a Health Care Governance System. In: IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom) (2013)Google Scholar
  3. 3.
    Tobón, D.P., Falk, T.H., Maier, M.: Context awareness in WBANs: a survey on medical and non-medical applications. In: IEEE Wireless Communications, Aug 2013Google Scholar
  4. 4.
    Lin, Y., Jessurun, J., Vries, B., Timmermans, H.: Motivate: towards Context-Aware Recommendation Mobile System for Healthy Living. In: 5th International Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health) and Workshops 2011 (IEEE) (2011)Google Scholar
  5. 5.
    Lin, Y., Jessurun, A.J., Vries, B., Timmermans, H.: A context- aware persuasive system for active living-simulator system design. In: Conference proceeding of 10th International Conference on Design & Decision Support Systems in Architecture and Urban Planning, pp. 1–12 (2010)Google Scholar
  6. 6.
    Khan, M., Lee, S.: Need for a context-aware personalized health intervention system to ensure long-term behavior change to prevent obesity. In: 5th International Workshop on Software Engineering in Health Care (SEHC 2013), May 2013Google Scholar
  7. 7.
    Viswanathan, H., Chen, B., Pompili, D.: Research challenges in computation communication, and context awareness for ubiquitous healthcare. IEEE Communications Magazine, May 2012Google Scholar
  8. 8.
    Seppälä, A., Nykänen, P., Ruotsalainen, P.: Development of Personal Wellness Information Model for Pervasive Healthcare. J. Comput. Netw. Commun. 2012(596749) (2012)Google Scholar
  9. 9.
    Torres, S.J., Nowson, C.A.: Relationship between stress, eating behavior, and obesity. Nutrition 23(11–12):887–894 (2007)Google Scholar
  10. 10.
    Anjana, et al.: Physical activity and inactivity patterns in India—results from the ICMR-INDIAB study (Phase-1). Intern. J. Behav. Nutr. Phys. Act. 11(26), 2014 (2014)Google Scholar
  11. 11.
  12. 12.
    Stress Indicator Questionnaire. The Counseling team International. link: Accessed 03 Feb 2015
  13. 13.
    Gupta, S., Sood, S.P.: Context aware mobile agent for reducing stress and obesity by motivating physical activity-a design approach. IEEE 9th IndiaCom, March 2015Google Scholar
  14. 14.
    Krepsemail, G.L., et al.: Development and validation of motivational messages to improve prescription medication adherence for patients with chronic health problems. Patient Educ. Couns. 83(3), 375–381 (2011)CrossRefGoogle Scholar
  15. 15.
    Kim, C.M., Keller, J.M.: Effects of motivational and volitional email messages (MVEM) with personal messages on undergraduate students’ motivation, study habits and achievement. British J. Educ. Technol. 39(1), 2008 (2008). doi: 10.1111/j.1467-8535.2007.00701.x Google Scholar
  16. 16.
    Visser, J., Keller, J.M.: The clinical use of motivational messages: an inquiry into the validity of the ARCS model of motivational design. Instr. Sci. 19(6), 467–500 (1990)Google Scholar
  17. 17.
    Mulgund, P., et al.: Personalized medication adherence motivating and reminding system (PMAMRS). Adv. Impact Des. Sci. Mov. Theory Pract. Lect. Notes Comput. Sci. 8463, 448–452 (2014)CrossRefGoogle Scholar
  18. 18.
    Aziz, N., Kallur, S.D., Nirmalan, P.K.: Implications of the revised consensus body mass indices for asian indians on clinical obstetric practice. J. Clin. Diagn. Res. (2014). doi: 10.7860/JCDR/2014/8062.4212 Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • Saurav Gupta
    • 1
  • Sanjay P. Sood
    • 2
  • D. K. Jain
    • 3
  1. 1.Department of Health Infomatics & Electronics, EngineerCentre for Development of Advanced ComputingMohaliIndia
  2. 2.Department of Information TechnologySeMT, Chandigarh AdministrationChandigarhIndia
  3. 3.Centre for Development of Advanced ComputingMohaliIndia

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