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Monitoring and measuring physical activity and sedentary behaviour

Published Online:pp 283-303https://doi.org/10.1504/IJHTM.2012.052548

It is generally agreed that an active lifestyle promotes healthy living across different age groups. It helps to combat obesity, reduces the risk of diabetes and heart disease, and supports independent living, as we age. However, it is difficult to quantify a direct correlation between physical activity and health outcomes. Given that obesity and lifestyle-related illnesses occur over years, rather than days, weeks or months, seeing the effects that activity and sedentary behaviour have on individuals, in the short term, is not always possible. The ubiquitous nature of physical activity makes it extremely difficult to capture as people go about their lives. Consequently, there has been a great deal of debate on the frequency intensity time, and the type of physical activity required by different groups (pre-schoolers, children and adults, older adults, obese, infirm, disabled and depressed). There is a need to provide effective mechanisms to monitor and measure physical activity and sedentary behaviour. While several commercially available products exist to achieve this, they are expensive, proprietary, and compliance is poor. The challenge is to use new and novel technologies that are unobtrusive and natural to use, adjunct to a person’s day-to-day activities. This paper builds on this idea and explores how physical activity and sedentary behaviour information can be collected, from different environments. We have successfully developed an open and extensible working prototype to evaluate the applicability of our applied computing approach.

Keywords

intelligent environments, physical activity, sedentary behaviour, sensors, sensor networks, monitoring, measurement

References

  • 1. Almeida, G.J.M. , Wasko, M.C.M. , Jeong, K. , Moore, C.G. , Piva, S.R. ‘Physical activity measured by the SenseWear Armband in women with rheumatoid arthritis’. Physical Therapy: Journal of the American Physical Therapy Association. 2011, 09, 91, 9, 1367-1376 Google Scholar
  • 2. Ao, S.I. (2010). ‘Review of daily physical activity monitoring system based on single triaxial accelerometer and portable data measurement unit’. Machine Learning and Systems Engineering. 68, 569-580 Google Scholar
  • 3. Barakova, E.I. , Spink, A.S. , de Ruyter, B. , Noldus, L.P.J.J. (2012). ‘Trends in measuring human behaviour and interaction’. Personal and Ubiquitous Computing. in press Google Scholar
  • 4. Bassett, D.R. (2000). ‘Validity and reliability issues in objective monitoring of physical activity’. Research Quarterly for Exercise and Sport. 71, 2, S30-S36 Google Scholar
  • 5. Benkic, K. , Malajner, M. , Planinsic, P. , Cucej, Z. (2008). ‘Using RSSI value for distance estimation in wireless sensor networks based on ZigBee’. Presented at 15th International Conference on Systems, Signals and Image Processing, Bratislava, Slovak Republic Google Scholar
  • 6. Biddle, S.J.H. , Pearson, N. , Ross, G.M. , Braithwaite, R. (2010). ‘Tracking of sedentary behaviours of young people: a systematic review’. Preventative Medicine. 51, 5, 345-351 Google Scholar
  • 7. Cavalheri, V. (2011). ‘Energy expenditure during daily activities as measured by two motion sensors in patients with COPD’. Respiratory Medicine. 105, 6, 922-929 Google Scholar
  • 8. Chen, I. , Phee, S.J. , Luo, Z. , Lim, C.K. (2011). ‘Personalized biomedical devices and systems for healthcare applications’. Frontiers of Mechanical Engineering. 6, 1, 3-12 Google Scholar
  • 9. Clark, B.K. , Sugiyama, T. , Healy, G.N. , Salmon, J. , Dunstan, D.W. , Owen, N. (2009). ‘Validity and reliability of measures of television viewing time and other non-occupational sedentary behaviour of adults: a review’. Obesity Reviews. 10, 1, 7-16 Google Scholar
  • 10. Council on Clinical Information Technology (2011). ‘Health information technology and the medical home’. Journal of the American Academy of Pediatrics. 127, 5, 978-982 Google Scholar
  • 11. Devisch, I. (2012). ‘Co-responsibility: a new horizon for today’s health care?’. Health Care Analysis. 20, 2, 139-151 Google Scholar
  • 12. Dikaiakos, M.D. , Katsaros, D. , Mehra, P. , Pallis, G. , Vakali, A. (2009). ‘Cloud computing: distributed internet computing for IT and scientific research’. IEEE Internet Computing. 13, 5, 10-13 Google Scholar
  • 13. Dobbins, C. , Fergus, P. , Merabti, M. , Llewellyn-Jones, D. (2012a). ‘Monitoring and measuring sedentary behaviour with the aid of human digital memories’. Presented at the 9th IEEE International Consumer Communications and Networking Conference (CCNC) CeHPSA, WS, Las Vegas, USA Google Scholar
  • 14. Dobbins, C. , Fergus, P. , Merabti, M. , Llewellyn-Jones, D. (2012b). ‘Remotely monitoring and preventing the development of pressure ulcers with the aid of human digital memories’. Presented at the 47th IEEE International Conference on Communications, Ottawa, Canada Google Scholar
  • 15. Dwyer, T.J. , Alison, J.A. , McKeough, Z.J. , Daviskas, E. , Bye, P.T.P. (2011). ‘Effects of exercise on respiratory flow and sputum properties in patients with cystic fibrosis’. Chest. 139, 4, 870-877 Google Scholar
  • 16. Dwyer, T.J. , Alison, J.A. , McKeough, Z.J. , Elkins, M.R. , Bye, P.T.P. (2009). ‘Evaluation of the SenseWear activity monitor during exercise in cystic fibrosis and in health’. Respiratory Medicine. 103, 10, 1511-1517 Google Scholar
  • 17. Fergus, P. , El Rhalibi, A. , Carter, C. , Cooper, S. (2012). ‘Towards an avatar mentor framework to support physical and psychosocial treatments’. Health and Technology. 2, 1, 17-31 Google Scholar
  • 18. Fergus, P. , Haggerty, J. , Taylor, M. , Bracegirdle, L. , England, D. (2011a). ‘Towards a whole body sensing platform for healthcare applications’. Whole Body Interaction. Springer, 135-149 Google Scholar
  • 19. Fergus, P. , Taylor, M. , Haggerty, J. , Bracegirdle, L. , Merabti, M. , Rocker, C. Ziefle, M. (2011b). ‘Next generation body area networks and smart environments for healthcare’. Smart Healthcare Applications and Services: Developments and Practices. IGI, 46-74 Google Scholar
  • 20. Grossman, R.L. , White, K.P. (2012). ‘A vision for a biomedical cloud’. Journal of Internal Medicine. 271, 2, 122-130 Google Scholar
  • 21. Hamacher, D. , Bertram, D. , Folsch, C. , Schega, L. (2012). ‘Evaluation of a visual feedback system in gait retraining: a pilot study’. Gait & Posture. in press Google Scholar
  • 22. Jurik, A.D. (2009). ‘Body sensors: wireless access to physiological data’. IEEE Software. 26, 1, 71-73 Google Scholar
  • 23. Lee, M. , Kang, S. (2005). ‘Multimedia room gateway for integration and management of distributed medical devices’. presented at Workshop on High Confidence Medical Device Software and Systems (HCMDSS), University of Pennsylvania, Philadelphia, PA, USA Google Scholar
  • 24. Lord, S. , Chastin, F.M. , McInnes, L. , Little, L. , Briggs, P. , Rochester, L. (2011). ‘Exploring patterns of daily physical and sedentary behaviour in community-dwelling older adults’. Age and Ageing. 40, 2, 205-210 Google Scholar
  • 25. Merabti, M. , Fergus, P. , Abuelma’atti, O. , Heather, Y. , Judice, C. (2008). ‘Managing distributed networked appliances in home networks’. Proceedings of the IEEE. 96, 1, 166-185 Google Scholar
  • 26. Mortazavi, B. , Chu, K.C. , Li, X. , Tai, J. , Kotekar, S. , Sarrafzadeh, M. (2012). ‘Near-realistic motion video games with enforced activity’. Presented at the 9th IEEE International Conference on Wearable and Implantable Body Sensor Networks, London, UK Google Scholar
  • 27. Office for National Statistics (2010). Healthy Life Expectancy: Living Longer in Poor Health. Google Scholar
  • 28. Ouellette, J.A. , Wood, W. (1998). ‘Habit and intention in everyday life: the multiple processes by which past behaviour predicts future behaviour’. Psychological Bulletin. 124, 1, 54-74 Google Scholar
  • 29. Owen, N. , Sugiyama, T. , Eakin, E.E. , Gardiner, P.A. , Tremblay, M.S. , Sallis, J.F. (2011). ‘Adults’ sedentary behaviour: determinants and interventions’. American Journal of Preventive Medicine. 41, 2, 189-196 Google Scholar
  • 30. Piette, J.D. , Mendoza-Avelares, M.O. , Ganser, M. , Mohamed, M. , Marinec, N. , Krishnan, S. (2011). ‘A preliminary study of a cloud-computing model for chronic illness self-care support in an underdeveloped country’. American Journal of Preventive Medicine. 40, 6, 629-632 Google Scholar
  • 31. Pitta, F. , Troosters, T. , Probst, V.S. , Spruit, M.A. , Decramer, M. , Gosselink, R. (2006). ‘Quantifying physical activity in daily life with questionnaires and motion sensors in COPD’. The European Respiratory Journal. 27, 5, 1040-1055 Google Scholar
  • 32. Prayati, A. , Antonopoulos, C. , Stoyanova, T. , Koulamas, C. , Papadopoulos, G. (2010). ‘A modeling approach on the TelosB WSN platform power consumption’. Journal of Systems and Software. 83, 8, 1355-1363 Google Scholar
  • 33. Quon, B.S. (2011). ‘Monitoring habitual physical activity in cystic fibrosis patients using pedometers’. American Journal of Respiratory and Critical Care Medicine. 183, 1, A1121 Google Scholar
  • 34. Stange, K. , Nutting, P. , Miller, W. , Jaen, C. , Crabtree, B. , Flocke, S. , Gill, J. (2011). ‘Defining and measuring the patient-centered medical home’. Journal of General Internal Medicine. 25, 6, 601-612 Google Scholar
  • 35. Stratton, G. , Murphy, R. , Rosenberg, M. , Fergus, P. , Attwood, A. (2012). ‘Creating intelligent environments to monitor and manipulate physical activity and sedentary behaviour (moving and sitting) in public health and clinical settings’. Presented at the 47th IEEE International Conference on Communications, Ottawa, Canada Google Scholar
  • 36. Strayer, S.M. , Martindale, J.R. , Pelletier, S.L. , Rais, S. , Powell, J. , Schorling, J.B. (2011). ‘Development and evaluation of an instrument for assessing brief behavioral change interventions’. Patient Education and Counseling. 83, 1, 99-105 Google Scholar
  • 37. Taraldsen, K. (2011). ‘Evaluation of a body-worn sensor system to measure physical activity in older people with impaired function’. Physical Therapy: Journal of the American Physical Therapy Association. 91, 2, 277-285 Google Scholar
  • 38. Tremblay, M.S. , Colley, R.C. , Saunders, T.J. , Healy, G.N. , Owen, N. (2010). ‘Physiological and health implications of a sedentary lifestyle’. Applied Physiology, Nutrition, and Metabolism. 35, 6, 725-740 Google Scholar

Additional References