Friday, October 18, 2013

The Heart as a Computer

The Heart as a Computer .

Andre Willers
18 Oct 2013
This is not medical advice .
Synopsis :
The Heart organ can be described as a computer roughly equivalent to an old XT (~16kb/sec)

Discussion :
1.See Appendix A.
Information in HRV per heartbeat 1 hz = ((0.15-.07)*1)^-1 = 156 bits
In double “lub-dub” , information  = 156^2 = 16384 bits hidden in frequency interference.

The heart programs a lot of bodily responses .

2.Damage to half of the heart :
Immediate loss of half of system responsiveness .

3.How to compensate :
Programmed Percussion .
If the medical systems did their job , there would be an exact pattern of percussions to mimic a healthy heart .
Since they didn’t , try heavy rock with big speakers that cause visceral effects .

4.The body can adapt easier to a strong signal than to a weak one .
5. Beta blockers are immaterial . At least one heavy percussion rhythm is needed for the system to retrain using at least periods between beats in interference mode .

6.You will live longer if you listen to a loud orchestra .


Appendix A
After analysing the variability of the RR intervals, a number of studies [11] [12]
[19] [22] [25] [26] [29] [30] [32] [35] have shown that an increase in mental load
causes a decrease in the so-called mid-frequency (MF, 0.07-0.15 Hz) power band
of the Heart Period Variability (HPV) power spectrum. Focusing on this
frequency band filters other peaks of the power spectrum: the typical peak in the
0.15-0.45 Hz band corresponds to the respiratory rate (called respiratory sinus
arrhythmia); the peak in the 0.04-0.07 Hz band is in connection with the
thermoregulatory fluctuations of the blood vessels [12] [19]. Heart rate
fluctuations in the MF (0.07-0.15 Hz) power band may also reflect postural
changes (via the blood pressure control of the so called baroreflex). To separate
the effect of the mental load from the effect of postural changes, a ratio of the MF
component around 0.1 Hz and the higher frequency respiratory component can be
applied [30]. However, it is emphasised that if the participants work continuously
in a sitting posture (e.g., during computer usage), and their larger muscle
movements (e.g., stretching, laughing, sneezing, talking, etc.) eventually are
filtered from the records (e.g., via video analysis), the MF (0.07-0.15 Hz) power
band itself can characterize the mental effort sensitively enough, as is shown by
the following results presented in this paper.


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