Human Energy Expenditure ?
Are Connected Device Right ?
Created :2017-04-11 15:16:00. – Modified : 2017-04-14 20:22:54.
Expériences En Construction.
Let’s try to compare « connected » equipment to theoric human expenditure energy curves ?
We can’t do automatic measurements with Fit$bit device !
How to made measurements with a connected device ? … … By hand, hour quarter by hour quarter ! Fit$bit device and its society don’t agree to share OUR own data (pulse and cardiac frequency) !!! Shame on us.
Then we remain scientist ie … honnest, right, intelligent. We reconstruct curves with a reference by Black et al. [BLACK-1996] as has written other web sites displays. We « discover » the right title but the reference (?) document is private ($, €).
Do it by hand and … brain ?
We plot by Matlab curves by reference by Black et al. [BLACK-1996] and a day measurements, by hands, with the connected devices display.
- Red curves are différential energy expenditure for one hour.
- Blue ones are energies integration by hour.
- Fine curves are an average by Black and all equations.
- Bold curves are real measurement on device.
We try for the real measurement to expend 2560 Calories by this day. We got it ! Thanks ! The red bold curves displays our effort to maintain the lawn (grass and not The Law 😉 ). I am green !
We tried to follow the average Black and All curves to aim the graal : 2620 Calories at 23:59:59 ! We got it !
Another day we use Matlab « data cursor ». Then we display (h) and (Calories).
The connected equipment displays : et (calories). We are in late !
Then when we compare energy evaluation with theory curves then they match correctly. But are evaluated energies by connected equipement right ? Probably Not ? All we could say it is energies displayed by equipment follows correctly the « internal » law evaluated by cardiac frequencies and movment accelerometers. Are the real human energies expenditure the same ? We don’t know ?
We think this is the same type of measurements as and its calibration like age=5200 years Before Calibration and or age=6600 years with right calibrate method [CIPRIA-11/02/2017] ?
Is this measurement and its comparison with theorical curve science ?
Of course NOT. We explain us how to do this in different part of PhD thesis annex. Let us see for example « khi² demonstration » [CIPRIA-24/02/2017].
- [CIPRIA-24/02/2017] : CIPRIA, Jean-Paul « Khi² scientific methods. » :
- [CIPRIA-11/02/2017] : CIPRIA, Jean-Paul – « How to recalibrate a 14C measurements ? » :
- [BLACK-1996] : BLACK, A. E., COLE, COWARD, et PRENTICE. « Human Energy Expenditure in Affluent Societies: An Analysis of 574 Doubly-Labelled Water Measurements. » – 1996. https://www.ncbi.nlm.nih.gov/pubmed/xxxxxx. Not free.
To describe average levels of free-living energy expenditure in people from affluent societies and to determine the influence of body weight, height, age and sex.
Analysis of 574 measurements of total energy expenditure (TEE, assessed by the doubly-labelled water method); basal metabolic rate (BMR, directly measured or derived from similar directly measured proxy measures such as during sleep); activity energy expenditure (AEE, derived as TEE-BMR); and physical activity level (PAL, derived as TEE/BMR) from people aged 2-95 years. The dataset was extracted from 1614 published and unpublished measurements in 1156 subjects after exclusion of repeat estimates and subjects in special physiological or behavioural states (eg pregnancy, athletic or military training etc).
A separate analysis of data from non-ambulant subjects, and from elite endurance athletes (all excluded from the main dataset) established the limits of human daily energy expenditure at around 1.2 x BMR and 4.5 x BMR. In the main analysis, the validity of PAL as an index of TEE adjusted for BMR was tested and confirmed. Regression equations were then derived to describe TEE, BMR, AEE and PAL in terms of body weight, height, age and sex. As anticipated, TEE, BMR and AEE were all positively related to weight and height, while age was a negative predictor, especially of activity. The influence of weight disappeared when TEE was expressed as PAL, but height and age remained as highly significant predictors. For all three components, females expended 11% less energy on average than males after adjustment for weight, height and age. Average levels of energy expenditure in different age and sex groups are tabulated.
There now exists a large and robust database of energy expenditure measurements obtained by the doubly-labelled water method. Analysis of the data from affluent societies shows that, in general, levels of energy expenditure are similar to the recommendations for energy requirements adopted by FAO/WHO/UNU (1985) and UK Department of Health (1991). PAL values for active subjects tend to be higher than is currently assumed. The current analysis provides a substantial body of normal data against which other estimates can be compared…
© Jean-Paul Cipria