BodyMedia and BodyBugg users, question for ya

I did go back and look at the "dips" when I'm sleeping. The lowest it puts me is 1.1 cal/min and that's only for a few minutes. Also, I noticed when I take it off at night it automatically assumes I burn 1.3 cal/min the whole night.

1.3 x 1440 = 1872 BMR sound close?

Especially Katch BMR?

Couple have said it actually adjusted from the Harris down to the Katch level, so it can happen.

Yes, pretty accurate since my RMR tests at 1771 give or take 177 calories. On BodyMedia's website, it says "The Activity Manager does not base your calorie burn upon BMR or RMR. However, the World Health Organization RMR calculation (WHO-RMR) is used indirectly." (http://www.bodymedia.com/search.html?searchTerm=RMR) So I'm not sure how they're figuring it out other than using all of the data it collects in some complex way. I find it all very fascinating!

Interesting.
So the activity levels you can select at the beginning dealing with your goals is the standard Harris TDEE table, and when they calculate the goals, they base it on the Harris BMR.

Indirectly, I think that's where the adjustment comes in, based on the heat they see leaving at night. If you are good at heat escaping that spot where the sensor is to match their tables of what that means for BMR.

I guess, at some point you hope they did the math right. That RMR calc is without published studies. At least they adjust from there it seems, if your body reads well for heat flux.

But then you see a study where they screwed it up. I mean, come on, some of these are BMR, some are RMR, and there is a difference between those 2 levels, RMR should be higher.
I love how this study found the BMR calculators under-estimated the RMR that was tested. No duh.

A new predictive equation to calculate resting metabolic rate in athletes.
J Sports Med Phys Fitness. 1999 Sep;39(3):213-9.

BACKGROUND: The purposes of the present study were: 1) to examine the accuracy and precision of seven published equations for predicting resting metabolic rate (RMR) in male athletes and 2) to develop a population-specific equation. Setting: The study occurred during a non-intensive training period. The measurements were performed at the Human Physiology laboratory. Participants: Fifty-one male athletes (22 waterpolo, 12 judo, 17 karate) who exercised regularly at least three hours per day. Measures: RMR was measured (mRMR) using indirect calorimetry (ventilated hood system). Besides, mRMR was compared with values predicted (pRMR) using equations of FAO/WHO/UNU, Harris and Benedict, Mifflin et al., Owen et al., Cunningham, Robertson and Reid, Fleisch. Statistical analyses. mRMR was compared with pRMR by means of Student's paired "t" tests, linear regression analysis and the Bland-Altman test. Relationships between mRMR and the different predictive variables were evaluated by Pearson correlation coefficients. The best subset was used to develop the predictive equation for RMR. RESULTS: mRMR was significantly underestimated by six of the seven equations in this sample of athletes. Only the Cunningham equation overestimated (+59 kcal/d) the actual RMR. Bland-Altman 95% limits of agreement were wide (+/- 200-300 kcal/d) for all equations. RMR correlated best with body surface area (r = 0.88), body weight (r = 0.84) and height (r = 0.81). The best-fit equation for the entire data included both weight and height and it was given by: RMR (kcal/d) = -857 + 9.0 (Wt in kg) + 11.7 (Ht in cm) (R2 = 0.78; SEE = 91 kcal/d; 95% IC: -226, 228). CONCLUSIONS: For an individual resting metabolic rate evaluation, the use of indirect calorimetry is recommended. In conditions where this technique cannot be used, our developed equation can predict the RMR of athletes better than any of the currently available prediction equations.