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Ruud_G

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 #16 
Thanks for sharing Juerg. What is actually interesting is 1) what factors are taken into consideration to decide when 2) to do a different workout and 3) how much weight (of evidence) is placed on them. In the second cass his tHb does not seem to shoot out when he lowers the load (that is I assume that since his HR drops at almost the end of the 8 min). HRV has -as you know- also many flaws in it, if his lactate level is low or higher than day before also can be influenced by many factors, the pattern in SmO2 and tHb can also fluctuate by many different factors. In that way there is still trial and error involved in it, which also comes down to classical ideas since also there we don't know what is the status of various body functions for exercise. No critique of course because with wattage based programms these questions are never askedz Just relevant questions in the quest towards physiological guided workouts.
Nkrause

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 #17 
Juerg, when you talk about a Resting Respiratory Assessment what do you mean? Haven't come across that term before. 
juergfeldmann

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 #18 
RRA  stands  for  resting respiratory  assessment  and it is  the same as a  resting  HR  assessment. Yo  rest  do nothing  and look how your respiration is.

Below is an exampel on the  values  you   assess.
Y L 2013.jpg 
 This is a program  I  developed   together  with Mary Ann Kelly in Joshua  tree. It si  a   compilation of existing  statistical information on RMR  but as well on   VC  and VE  values  and  than we  simply asses the  rest.
 Below is a  summary  of  some work shop MarY Ann I  did some years back in   California    as we  combined  nutritional feedback  and physiological test  and respiratory training together

What All Respiratory Parameters Could Affect the

HRV ( HEART RATE VARIABILITY) ESTIMATES

The respiratory parameters which can affect HRV estimates, include- respiratory frequency (RF) tidal  Volume [10], end tidal partial pressure of carbon di- (PETco2) [10,11], the time ratio of expiration/inspiration  [12] And respiratory dead space [13]. Since breathing through an oro-nasal mask or mouthpiece can also affect  breathing pattern and components of ventilator responses to chemo stimuli [14], it can be extrapolated that it will also influence HRV estimates- an observation of importance in the case of using masks for RMR and RRA testing.

How Do The Above Respiratory Parameters Affect HRV?

  1. Respiratory frequency & tidal volume :

The variation of heart rate in the frequency range of respiration, known as respiratory sinus arrhythmia (RSA), was already described by Ludwig in 1847 [15]. Despite many past studies, the precise mechanisms of  respiration-induced SA are still debated. The theories which have been proposed are not mutually exclusive. The most important ones are the modulation of cardiac filling pressure by respiratory movements [16], the direct  respiratory modulation of parasympathetic and sympathetic neural activity in the brain stem [17] and the respiratory modulation of the baroreceptor feedback control [18]. In a recent review of published evidence, Eckberg  [19] summarised that respiratory fluctuations of muscle sympathetic nerve activity and electrocardiographic RR  intervals result primarily from the action of a central ‘gate’ that opens during expiration and closes during inspiration.

Ind J Aerospace Med 48(1), 2004 67

Respiration And Heart Rate Variability : Lt Col KK Tripathi Parallel respiratory fluctuations of arterial pressures and R-R intervals are thought to be secondary to arterial baroreflex physiology- changes in systolic pressure provoke changes in the R-R interval. However, growing evidence suggests that these parallel oscillations result from the influence of respiration on sympathetic and vagal-cardiac Moto neurones rather than from baroreflex physiology. In yet another synthesis, RSA could be a physiologic phenomenon reflecting respiratory circulatory interactions improving the efficiency of pulmonary gas exchange. The matched timing of alveolar ventilation and its perfusion with RSA within each respiratory cycle could save energy expenditure by suppressing unnecessary heartbeats during expiration and ineffective ventilation during the ebb of perfusion

2 . Change in end tidal PCO2

The most likely mechanism responsible for increased RSA magnitude, with an increase in PETco2, is chemostimulation that enhances respiratory modulation of vagal outflow. Stimulation of carotid chemoreceptors

 

-2-

by increased arterial Pco2 has primarily an excitatory effect t on vagal preganglionic neurons to the heart in the  expiratory phase [20,21]. In unanesthetized trained dogs, Yasuma and Hayano [22] reported that hypercapnia (PETco2 up to 54 mmHg) increases RSA magnitude by 62% with no concomitant changes in mean R-R interval. Increased RSA could also be a manifestation of cardiorespiratory interactions [23] which contribute to CO2 elimination by reducing physiological dead space and intrapulmonary shunt, ie, matching the distribution of pulmonary blood flow to lung volume during each respiratory cycle [24]. An increased demand for CO2 elimination may therefore enhance RSA to facilitate pulmonary gas exchange. Regulation of RSA magnitude  by PaCO2 could complement CO2-modulated changes in airway smooth muscle tone in controlling dead space. Hypercapnia is shown to both decrease tracheal diameter in anesthetized dogs [25] and causes bronchoconstriction in decerebrate cats [26]. In anesthetized dogs, Hayano et al [24] also showed that RSA reduces physiological dead space, ie, the alveolar dead space, by matching perfusion to ventilation during each respiratory cycle.

It has been shown in conscious humans [27] that increase in RSA magnitude due to the direct effects of  CO2 are independent of changes in tidal volume and breathing frequency.

  1. Relative timing of inspiration and expiration

Strauss-Blasche et al [12] showed that RSA can also be modulated by a third respiratory variable. In their experiment, examining the effect of a variation in inspiration and expiration times on heart rate variability, the subjects were given 2 x two min trials of controlled breathing with either short inspiration followed by long expiration or long inspiration followed by short expiration. Average expiration/inspiration time ratios were 1.0 and 3.4, respectively and the respiration rate in both trials was approximately 10 cycles/min. In trials with short inspiration followed by long expiration, RSA (measured by mean absolute differences and by the high frequency band) was significantly larger than in trials with long inspiration followed by short expiration. This effect could  not be accounted for by differences in respiratory rate or amplitude. The higher RSA during fast/slow respiration is primarily due to a more pronounced phasic heart rate increase during inspiration, indicating that inspiratory vagal blockade is sensitive to the steepness of inspiration.

 Cardiac aliasing There is yet another mechanism reported to be involved in mediating respiratory fluctuations of heart beat. Witte et al [28] observed that if a special relationship exists between mean heart rate (fHR) and mean frequency of breathing (fB) such that fB is greater than 1/2 fHR, RSA can be observed in a frequency range which is lower than the frequency of breathing. The mathematical fundamentals of this physiological phenomenon are the same as those for the ‘aliasing’ effect in signal sampling. The authors termed it ‘cardiac aliasing’ and could experimentally demonstrate it in adult rabbits and dogs as well as in human neonates.

 

 

 

 

-3-

 

Own small ideas on this part controlled by NIRS.

 

Respiration And Heart Rate Variability : Lt Col KK Tripathi

68    nd J Aerospace Med 48(1), 2004

4        Respiratory dead space

Hirsch JA and Bishop B [14] demonstrated that choice of a mouthpiece or a face mask can differentially change breathing pattern and all the components of ventilatory responses to chemostimuli. These breathing apparatus effects did not appear to be a simple consequence of a shift from oronasal to oral breathing. In an interesting study, Furutani Y [13] evaluated the effect of the dead space induced by the face mask used in the expiratory gas exchange analysis on the measurement of heart rate variability using ECG records for 5 min during spontaneous respiration under the conditions of supine rest, sitting on the bicycle ergometer with and without a face mask. The value of LF/HF increased from supine rest to sitting in accordance to the change of body position, but the value of LF/HF when sitting with the face mask decreased to the level during supine rest. The value of HF/TP decreased from supine rest to sitting, but when sitting with the face mask returned to that during supine rest. It was also seen that the value of LF/HF decreased from supine rest to sitting with the face mask in the smaller tidal volume group (tidal volume<570 ml) and there was a significant correlation between the change of the value of LF from supine rest to sitting with the face mask and the tidal volume. These results suggest that the power spectrum of heart rate variability is strongly influenced by the dead space induced by the face mask used in expiratory gas exchange analysis. Even though the sympathetic activation from supine rest to sitting in subjects with the smaller tidal volume is unclear, interpretation of the results of heart rate variability with or without the face mask used requires care.

Is Respiratory Influence Confined To Only High (Respiratory) Frequencies In The HRV Power Spectrum?

Schipke et al [9] examined the effect of controlled respiration at six different breathing frequencies on HRV indices derived from short term recordings of six minutes each. Breathing frequencies ranged from below the lowfrequency range (LF) of the power spectrum (0.03 Hz) to above HF (0.50 Hz). Heart rate remained unchanged throughout the protocol, indicating a steady haemodynamic state. HRV differed up to 33% in SDNN,

37% in RMSSD and 75% in pNN50 between the different respiration rates. LF power differed up to 72%, HF power up to 36% and R up to 48%. These results show that respiration can change HRV power spectra both in high and low frequency regions (Figure-1, drawn from the data presented by Schipke et al, refers).

 

 

 

-4-

Novak [29] studied the dynamics of the respiratory and cardiovascular systems by continuously slowing respiration from 0.46 to 0.05 Hz. During rest, the nonrespiratory-to-respiratory frequency ratios were not affected by occasional slow breathing. As respiration slowed to 0.07-0.09 Hz, the frequency content of the respiration and cardiovascular variables increased sharply and nonlinearly to a maximum that exceeded values at higher frequencies. The nonrespiratory frequency content remained stable in the 0.01- to 0.05-Hz range and did not significantly differ from that at rest. In contrast, the 0.05- to 0.1-Hz component was suppressed. A slow 0.012- to 0.017-Hz rhythm modulated respiration and hemodynamic fluctuations at both respiratory and nonrespiratory frequencies. The study indicated that respiration input should be considered in the interpretation of global spectra. However, recently, independence of low-frequency rhythms from respiratory activity is reported [30]. Sasano [27] failed to observe any change in low frequency power or LF/HF ratio over a range of PETco2 (30, 40 & 50 mm Hg) in conscious human subjects despite a significant increase in RSA. Mean R-R interval did not differ at PETco2 of 40 and 50 mmHg but was less at 30 mmHg and changes in tidal volume and breathing frequency were prevented.

Ind J Aerospace Med 48(1), 2004 69

 Respiration And Heart Rate Variability : Lt Col KK Tripathi

Even if low frequency region of HRV power spectra is relatively insusceptible from the respiratory influences, the latter will affect interpretation of spectral values in low frequency region in normalised terms due to a significant change in the total power.

Certain Examples From Aerospace Settings Wherein HRV Estimates Could Be Confounded From Respiratory Influences Hypoxia

Assessment of autonomic function during exposures to hypoxia is important as the former may affect tolerance to this stress and could contribute to certain specific syndromes viz, acute mountain sickness, high altitude pulmonary edema, and high altitude cerebral edema. HRV analysis has generally shown an increase in cardiac sympathetic activity after acute exposure to hypoxia [31, 32, 33] without a significant change in the fractal component (which indicated overall ‘irregularity’ of HRV). Certain studies have, however, reported results which are not in consonance with the above observations. For example, Sevre et al [34] have shown a transient reduction in both parasympathetic and sympathetic activity during stepwise exposure to high altitude. Pre-adaptation to hypoxia is shown to modulate

HRV responses in rats [35] but not in humans [31]; this difference could be due to difference in the period of acclimatisation. HRV analysis has also been used to demonstrate ethnic variations in reactions to hypoxia [36] and assessment of baroreflex responsiveness in hypoxia [34]. In almost all the above studies, the results are not without confounding effects of one or more respiratory variables (viz breathing frequency, tidal volume, PETco2, dead space etc) which were neither controlled nor monitored. All these respiratory attributes are known to change during hypoxia [37,38].

 

Change of SV with  Respiration ( own case studies) 

Hope this helps

.

Nkrause

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 #19 
much appreciated, thanks juerg!
juergfeldmann

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 #20 
Your  welcome
 There is  another interesting resting   information we use  and it is not very  well know . It so  called  Phase angle. It is  measured  with bio impedance  options. In simple terms   the phase angel is a feedback on the " health " of  cell  membranes.
 A healthy cell shows more " resistance"  to   penetration of   certain  wave length  . A  unhealthy  or  weekend  cell membran  shows  more penetration . So as lower the phase angle  as less optimal  cell  membrane  health.
 This  is used in some cases in medicine  and there are some studies done, where the assessed phase angels  on terminal ill  patients  to see, what  a  lower or   not   optimal  cell membrane is .
  We  tried  phase angel assessments in  cycling  and running training  camps  and when we  overloaded   clients  than we had a   clear drop in phase angle  and if they recovered   the phase angel would go back up  to    base levels of this  client. Will try to find  some  from  some camps in Spain.
Nkrause

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Posts: 49
 #21 
Wow, that would certainly be interesting. So they run a wavelength through an athlete when they're rested and then after a workout, and calculate the phase angle between the two? Fascinating stuff!
juergfeldmann

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Posts: 1,501
 #22 
Yes  that's  what we  do  and the  density of the cell membrane  will " bounce  " of the   signal  in a specific angle  before it keeps  going towards its   target.
 
We use  phase  angel in   training  camps  to  trace  overload  of  cell structures and  it had some trendsetting  . As well there was  an unpublished  study ( internal    discussion)  during a   grand tour  with the same result. Athletes would basically quite , when they reached a  certain phase  angel despite  no  other actual reason. What I  work on is to see whether the phase  angel reaction  shows  up in the resting  SmO2 trend or  not.

 

Phase Angle: is a measurement of your body's overall health. Phase angle is based on total body resistance and reactance and is independent of height, weight and body fat. Lower phase angles appear to be consistent with either cell death or a breakdown of the cell membrane.  Higher phase angles appear to be consistent large quantities of intact cell membranes and body cell mass. As you would expect the phase angle is increased with an increase in body mass, even though obesity itself is not associated with good health.  All living substances have a phase angle.  In fresh uncooked vegetables the phase angle can exceed 45 degrees. In cooked vegetables phase angle is zero because they are dead.

Phase Angle is a predictor of outcome and indicates the course of disease or increases as the result of optimal health based on good nutrition and consistent exercise.  Usually, a phase angle of 6 or greater is desired for men and 5 or greater is desired for women.

As we get older our phase angle will decrease and will be approximately 4 or less when we die. Fit adolescents may have a phase angle greater than 10.  This effect is a result of cell integrity due to age. Low phase angles are consistent with:

  • Malnutrition
  • Infection (HIV/AIDS, bacteremia)
  • Chronic disease (cirrhosis, renal disease, pulmonary tuberculosis)
  • Cancer (most types)
  • Abusive life style
  • Chronic Alcoholism
  • Old Age (80 - 100 years)
References:

M. Ott, H. Fisher, H. Polat, E. B. Helm, M. Frenz, W. F. Caspary B. Lembcke "Bioelectrical Impedance Analysis as a Predictor of Survival in Patient with HIV Infection" J. of Acquired Immune Deficiency Syndromes and Human Retrovirology 9:20-25 1995

R. Liedtke "Principles of Bioelectrical Impedance" http://rjlsystems.com
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