Dietary assessment and physical activity measurements toolkit

Future Developments


Recent developments in technology have led to, or suggest, important developments in the field of physical activity measurement.  Developments of particular note are:

  • Global positioning system (GPS);
  • High frequency movement sampling;
  • Combined motion sensors

Additionally, advances in the analysis of physical activity data e.g. analysing accelerometry data using non-linear modelling techniques and a move away from monitor-based processing to more investigator controlled data handling strategies is a positive step and is likely to increase flexibility and comparison in the field.  An artificial neural network of energy expenditure using non-integrated acceleration signals showed improved estimates of energy expenditure when compared to a uniaxial accelerometer and the IDEEA monitor and shows promise when linked with raw acceleration signals to improve estimates (Rothney et al, 2007). The IDEAA monitor commercially available (MiniSun, Frenso, CA) consists of 5 accelerometers attached to the skin with hypoallergenic tape at the sternum, midthigh, bottom of each foot.  Each sensor is wired to a hip pack that serves to synchronise the signals from each channel and to store data.

The incorporation of GPS to movement sensors provides objective data about location, domain of activity and may even help assess the determinants of activity (Rodriguez et al, 2005).

High frequency movement sampling has the potential to overcome some of the limitations of accelerometry.  The technology is advanced enough to differentiate activities not currently possible.

Advanced analysis of accelerometry data combined with a physiological measure such as heart rate or temperature offers the greatest potential for the accurate estimation of energy expenditure (Corder, et al, 2008).

These technological advances and the development of novel estimation methods are likely to narrow the gap between validity and feasibility of different methods. 

References
Corder K, Ekelund U, Steele RM, Wareham NJ, Brage S
Assessment of physical activity in youth
Appl Physiol. 2008 advance publication doi:10.1152/japplphysiol. 00094.2008

Rodriguez DA, Brown AL, Troped PT
Portable global positioning units to complement accelerometry-based physical activity monitors
Med Sci Sports Exerc. 2005; 37:11 (suppl):S572-81

Rothney MP, Neumann M, Beziat A, Chen KY
An artificial neural network model of energy expenditure using non-integrated acceleration signals
J Appl Phyiol. 2007; 103:1419-27

Links
CamNtech manufacturer and distributor of Actiheart
Combined sensor: Sense Wear

If there are any tools or resources that you would like to share on the website send an email to: admin@dapa-toolkit.mrc.ac.uk

Web design by Studio 24