Tuesday, October 9, 2007

Stop looking at averages, it's not that simple!

I've often said that physiology is messy (click here for an older post on it). I am sure I am not the first person to say that and I can't even remember who I stole it from.

I was having a conversation with Dr. Biltz at the U of the MN the other day (the really cool part about hanging out there is that I can pick the brains of super smart people) about the "thingification" of physiology. Open any text book and even in exercise physiology--which I tell people is basically physiology "in motion" (at rest it is pretty boring anyway), the descriptions still make it sounds like it is at rest. Sure, they say it is not at a steady state, but the quantities they use and words make it seem "fixed'

Dr. Biltz argues that ALL of it is in motion and prefers to think of it in terms of "different flow rates' which makes perfect sense to me since my primary background the first 8 years in college and beyond was engineering (I actually switched from the PhD program in Biomedical Engineering here to Kinesiology when I only had 2 more biomed classes left to take--ugh!) In engineering, we use rate calcs all the time, although I still think Newton invented Calculus just to torture students.

We should also stop looking at the means of data. We are past gaining a ton of new info that way and who the heck is "normal" anyway? (Sure as heck it's not me!) As I've stated before (check out the link here), physiology is associated with every "bad" engineering word--non linear, anisotropic, dynamic, highly variable, etc.

There are more data emerging within the last few years that is not only using the means/averages. One area is Heart Rate Variability (HRV) that uses the variability of the HR on a super small scale to get at the ratio of sympathetic to parasympathetic stimulation.

Analogy time. Think of sympathetic stimulation as an accelerator and parasympathetic as a brake. If you pull out a heart and let it beat on its own (click here to see the post about the visible heart experiments where they did just that), it will go to a rate of 100 beats per minute.

So under most conditions the heart is mainly under parasympathetic stimulation (aka braking) to DECREASE the heart rate (HR). When you start to exercise, the body with start to WITHDRAW parasympathetic stimulation up to about a rate of 100. Now, it is really never all parasympathetic or sympathetic and HRV can be used as tool to look at the percentage of each one at any given rate. This gives us clues as to how the nervous system maintains control.

Even new implantable defibrillators will give you a picture of HRV! See the picture at the top here.

This non linear, dynamic analysis can be applied to many areas! Here is a link to a study looking at GH levels. Many times you will see the word "entropy" or a newer method is "sample entropy" which appears to be better (I will save you the math but if you want to know how to calculate sample entropy see the list below for some good late night reading if you can't sleep).

Rant over and off my soapbox I go.
Rock on
Mike N

General references on the topics above

1. Bornas X., J. Llabres, M. Noguera, A. Pez. Sample entropy of ECG time series of fearful flyers: preliminary results. Nonlinear Dynamics Psychol Life Sci. 10(3):301-318, 2006.

2. Cao H., D. E. Lake, M. P. Griffin, J. R. Moorman. Increased nonstationarity of neonatal heart rate before the clinical diagnosis of sepsis. Ann Biomed Eng. 32(2):233-244, 2004.

3. Javorka M., J. Javorkova, I. Tonhajzerova, A. Calkovska, K. Javorka. Heart rate variability in young patients with diabetes mellitus and healthy subjects explored by Poincare and sequence plots. Clin Physiol Funct Imaging. 25(2):119-127, 2005.

4. Kaplan D. T., M. I. Furman, S. M. Pincus, S. M. Ryan, L. A. Lipsitz, A. L. Goldberger. Aging and the complexity of cardiovascular dynamics. Biophys J. 59(4):945-949, 1991.

5. Maestri R., G. D. Pinna, A. Porta, et al. Assessing nonlinear properties of heart rate variability from short-term recordings: are these measurements reliable? Physiol Meas. 28(9):1067-1077, 2007.

6. Nagai N., T. Matsumoto, H. Kita, T. Moritani. Autonomic nervous system activity and the state and development of obesity in Japanese school children. Obes Res. 11(1):25-32, 2003.

7. Nagai N., T. Moritani. Effect of physical activity on autonomic nervous system function in lean and obese children. Int J Obes Relat Metab Disord. 28(1):27-33, 2004.

8. Pincus S. Approximate entropy (ApEn) as a complexity measure. Chaos. 5(1):110-117, 1995.

9. Pincus S., R. E. Kalman. Not all (possibly) "random" sequences are created equal. Proc Natl Acad Sci U S A. 94(8):3513-3518, 1997.

10. Pincus S. M. Orderliness of hormone release. Novartis Found Symp. 227:82-96; discussion 96-104, 2000.

11. Pincus S. M., J. D. Veldhuis, A. D. Rogol. Longitudinal changes in growth hormone secretory process irregularity assessed transpubertally in healthy boys. Am J Physiol Endocrinol Metab. 279(2):E417-24, 2000.

12. Platisa M. M., V. Gal. Reflection of heart rate regulation on linear and nonlinear heart rate variability measures. Physiol Meas. 27(2):145-154, 2006.

13. Richman J. S., J. R. Moorman. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 278(6):H2039-49, 2000.

14. Ryan S. M., A. L. Goldberger, S. M. Pincus, J. Mietus, L. A. Lipsitz. Gender- and age-related differences in heart rate dynamics: are women more complex than men? J Am Coll Cardiol. 24(7):1700-1707, 1994.

15. Tulppo M. P., T. H. Makikallio, T. E. Takala, T. Seppanen, H. V. Huikuri. Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am J Physiol. 271(1 Pt 2):H244-52, 1996.

16. Veldhuis J. D., M. L. Johnson, O. L. Veldhuis, M. Straume, S. M. Pincus. Impact of pulsatility on the ensemble orderliness (approximate entropy) of neurohormone secretion. Am J Physiol Regul Integr Comp Physiol. 281(6):R1975-85, 2001.

17. Veldman R. G., M. Frolich, S. M. Pincus, J. D. Veldhuis, F. Roelfsema. Growth hormone and prolactin are secreted more irregularly in patients with Cushing's disease. Clin Endocrinol (Oxf). 52(5):625-632, 2000.