Alterations in Cardiovascular Regulation and Function Assessed Using Cardiovascular System
Identification
by
Ming-Hokng Maa
Submitted to the Department of Electrical Engineering and Computer Science
in Partial Fulfillment of the Requirements for the Degrees of
Bachelor of Science in Electrical [Computer] Science and Engineering
and Master of Engineering in Electrical Engineering and Computer Science
at the Massachusetts Institute of Technology
May 10, 2000
Copyright 2000 Ming-Hokng Maa. All rights reserved.
The author hereby grants to M.I.T. permission to reproduce and
distribute publicly paper and electronic copies of this thesis
and to grant others the right to do so.
Author
Department of Eldctrical Engineering and Computer Science
May 10, 2000
Certified by
Fchard J. Cohen
Thesis Supervisor
Accepted by
.-
Arthur6 Sith
Chairman, Department Committee on Graduate Theses
MG
MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
JUL 2 7 2000
LIBRARIES
Alterations in Cardiovascular Regulation and Function Assessed using Cardiovascular System
Identification
By
Ming-Hokng Maa
Submitted to the Department of Electrical Engineering and Computer Science on June 15, 2000
in Partial Fulfillment of the Requirements for the Degrees of Bachelor of Science in Electrical
[Computer] Science and Engineering and Master of Engineering in Electrical Engineering and
Computer Science
ABSTRACT
Cardiovascular System Identification (CSI), a novel technique for the noninvasive and
quantitative characterization of short-term cardiovascular regulation, was applied to determine the
effects of simulated microgravity environments on cardiovascular deconditioning in general and
orthostatic intolerance in particular. Preliminary results indicate that simulated micro-gravity
environments significantly alter the autonomic mediation of short-term cardiovascular reflexes,
including the heart-rate baroreflex. Furthermore, CSI was applied to determine the effects of
visual pathway stimulation on short-term autonomic regulation. The results indicate that visually
induced virtual tilt does elicit changes in short-term cardiovascular regulation, correlating
positively with individual measures of tilt perception. Finally, to provide a reference point with
existing cardiovascular analysis, three quantitative models were created to estimate the Smyth
heart-rate baroreflex sensitivity coefficient from CSI analysis. Using these models, we were able
to non-invasively estimate heart-rate baroreflex sensitivity without the use of pharmaceuticals.
Thesis Supervisor: Richard J. Cohen
Title: Whitaker Professor in Biomedical Engineering
Acknowledgments
I wish to thank my academic advisor, Professor Martha Gray, for her flexibility and
encouragement of my academic and nonacademic pursuits. I also wish to thank my research
advisor Professor Richard Cohen for giving me the opportunity to work in his laboratory, thereby
introducing me to the world of engineered physiology. I also wish to thank Professor Cohen for
his flexibility and his patience for my work. Furthermore, I wish to thank all of Professor
Cohen's Lab team, past and present, especially Ramakrishna Mukkamala, Craig Ramsdell,
Antonis Armoundas, Derin Sherman, Tom Mullen, Karin Toska, Grete Sundby, and Jacquelyn
Baskin for their immense help, without which this thesis would have been neither remotely
possible nor thinkable.
Thanks also to Kaitlyn Liao for keeping me sane.
Last but most importantly, however, I wish to thank my family: my mother, father, and
brother, for their unwavering confidence, support, understanding, and love, which molded me
into my present persona and allowed me to pursue my studies at MIT, often at their personal
sacrifice. For this, there can be no words of gratitude.
The work reported here was made possible through funding by the Massachusetts
Institute of Technology and the National Space Biomedical Research Institute.
Contents
1
2
3
4
5
6
7
Preface .........................................................................................................................
8
Cardiovascular System Identification (CSI) .............................................................
10
2.1
Introduction ...................................................................................................
10
2.2
Analysis Tools...............................................................................................
16
Alterations in Cardiovascular Regulation During Simulated Space Flight............ 18
3.1
Introduction and M otivation...........................................................................
18
3.2
Short-Term Bedrest Study.................................................................................20
3.2.1
Experim ental Protocol...........................................................................
20
3.2.2
CSI Results.............................................................................................
22
3.2.3
Discussion ............................................................................................
27
3.3
Long-Term Bone Demineralization/Calcium Metabolism Study ..........
28
3.3.1
Experim ental Protocol...........................................................................
28
3.3.2
CSI Results.............................................................................................
29
CSI Calculation of Sm yth's Baroreflex Sensitivity ...............................................
35
4.1
Introduction to Heart Rate Baroreflex Sensitivity.........................................
35
4.2
Experim ental Protocol....................................................................................
38
4.3
Calculating Sm yth's Baroreflex Sensitivity.................................................
38
4.4
CSI Results...................................................................................................
41
4.5
Calculating Heart-Rate Baroreflex Sensitivity from CSI............................... 43
4.5.1
M ethod 1 ..............................................................................................
43
4.5.2
M ethod 2 ...............................................................................................
48
4.5.3
M ethod 3 ...............................................................................................
50
4.6
Discussion .....................................................................................................
54
Visual-Autonomic Influence on Short-term Cardiovascular Regulation...............55
5.1
Introduction and M otivation...........................................................................
55
5.2
Experim ental Protocol....................................................................................
56
5.3
CSI Results and Discussion...........................................................................
58
Sum m ary and Future Work ....................................................................................
63
W orks Cited ...............................................................................................................
65
4
List of Figures
Figure 2-1. CSI Model of short-term cardiovascular regulation. Reprinted from Mullen et al.
11
1997 ............................................................................................................................
12
Figure 2-2. Derivation of HRT from ECG........................................................................
lines)
Figure 2-3. Group-averaged results for subjects in supine (solid lines) and standing (dashed
14
postures. Reprinted from Mullen et al. 1997...............................................................
17
Figure 2-4. Screenshot of the CSI Analysis Tool. ..............................................................
and
Figure 3-1. Diagram of the cardiovascular effects of space flight, potential mechanisms,
possible countermeasures. Reprinted from Cohen Annual Program Report 1999. ........ 19
Figure 3-2. Group-averaged comparison of supine (solid lines) and standing (dashed lines)
23
postures in Bedrest subjects during Phase 4 Post-bedrest. ...........................................
Figure 3-3. Group-averaged CSI results for Bedrest subjects in Supine position during prebedrest (thick solid line), last-day of bedrest (dashed line), and post-bedrest (thin solid line).
25
...................................................................................................................................
preduring
position
in
Standing
subjects
Figure 3-4. Group-averaged CSI results for Bedrest
bedrest (thick solid line), last-day of bedrest (dashed line), and post-bedrest (thin solid line).
...................................................................................................................................
26
Figure 3-5. Group-averaged comparison of supine (solid lines) and standing (dashed lines)
30
postures during Post-bedrest Phase 4 Week 1............................................................
Figure 3-6. Group-averaged CSI results for 5 Bone subjects in supine position during Pre-bedrest
p2_wl (thick solid line), End-bedrest p3_w17 (dashed lines), and Post-bedrest p4_w2 (thin
32
solid line). ...................................................................................................................
Figure 3-7. Group-averaged CSI results for 5 Bone subjects in standing position during
Pre-bedrest p2_w I (thick solid line), End-bedrest p3_w17 (dashed lines), and Post-bedrest
33
p4_w2 (thin solid line). ...........................................................................................
Figure 4-1. Typical arterial blood pressure response to phenylephrine. Heart rate is reduced in
compensation to drive arterial blood pressure back to steady-state values...................... 37
Figure 4-2. Phe-BRSaII (blue filled points + red empty points) and Phe-BRSex (blue filled points)
for subject 13. The red dashed line corresponds to the Phe-BRSai regression. The blue
39
solid line corresponds to the Phe-BRSex regression....................................................
Figure 4-3. For each subject, the mean Phe-BRSan (red empty circles) and Phe-BRSex (blue filled
40
circles) are plotted along with the range of two standard deviations.............................
Figure 4-4. Group averaged CSI results............................................................................42
44
Figure 4-5. Block Diagram of Method 1. ...........................................................................
44
Figure 4-6. Diagram of an IPFM model. Reprinted from Boer and Karemaker 1985. .......
Figure 4-7. The mean BRSMethod I ± 2 standard deviations are plotted for each subject......... 46
47
Figure 4-8. Comparison of Phe-BRS and BRSMethod 1.-----..----.--.....................................
49
Figure 4-9. Block Diagram of Method 2. .........................................................................
Figure 4-10. Comparison of Phe-BRS and BRSMetfod 2.........................................................
49
Figure 4-11. Block Diagram of Method 3...........................................................................51
Figure 4-12. Comparison of Phe-BRS and BRSMthod 3.........................................................51
Figure 4-13. Phe-BRS vs.
BRSMethd
2
with modified ABP ramps. The top graph uses an ABP
ramp averaged across all subjects and all analyzable pressure segments. The bottom graph
uses an ABP ramp averaged across all pressure segments for each subject. .................. 53
5
Figure 5-1. CSI data is obtained during periods I, II, and III. Perception of body and head tilt
orientation were obtained after 3 and 13 min. Symbols depict means t stdev. Reprinted
from Ram sdell 1999.................................................................................................
57
Figure 5-2. The distribution of perceived tilt orientation for each virtual stimulus after 3 min
exposure. The box plots show the 10th, 25th, 50th (median, heavy line), 75th and 90th
percentiles. Reprinted from Ramsdell 1999...............................................................59
Figure 5-3. Group averaged CSI results for subjects in supine (thick solid line), standing (thin
solid lines), mirror virtual-tilt (long dash lines), and pitch virtual-tilt (short dash lines).....61
6
List of Tables
Table 3-1. Comparison of CSI results: supine and standing postures during pre-bedrest, endbedrest, and post-bedrest (mean standard error). * denotes a p-value < 0.05 with respect to
pre-bedrest. A denotes a p-value < 0.05 with respect to supine. N=16 subjects. ......... 27
Table 3-2. Comparison of CSI results: supine and standing postures during phase 2 week 1 vs.
phase 3 week 17 vs. phase 4 week 1. (mean ± standard error). * denotes p-value < 0.05 with
respect to pre-bedrest. A denotes p-value < 0.05 with respect to supine. N=5 subjects..... 34
Table 4-1. CSI results (mean stderr). N=13 Subjects........................................................
41
53
Table 4-2. Parameters of the perturbing ABP ramp used in Method 3. ................................
Table 5-1. Perceived orientation. Mean±standard error. ....................................................
58
Table 5-2. Comparison of CSI results: supine vs. standing vs. virtual tilt (mean±stderr). *
indicates parameters with P-values < 0.05 with respect to supine. N=16 subjects......... 60
7
1
Preface
The normal cardiovascular system generally functions well in maintaining arterial blood
pressure within a narrow homeostatic range despite a number of internal and external
cardiovascular perturbations. Some of these internal perturbations include processes such as
respiration and fluctuations in peripheral resistance; while external perturbations include such
factors as a person's level of exercise, the ambient temperature, and a person's posture (Akselrod
1985, Hirsch 1981, Saul 1991). The cardiovascular system compensates for these perturbations
through a closed-loop network of cardiovascular reflexes including among others, the heart-rate
baroreflex and the Bainbridge reflex. Unfortunately, while the basic mechanisms responsible for
short-term cardiovascular regulation arefait accompli, the integrated homeodynamic system
remains to be well understood (Mullen 1997).
Because of this gap in our understanding, physicians have been unable to properly
diagnose or prescribe therapies for a variety of cardiovascular problems arising from extreme
internal and/or external perturbations. Of unique importance is a class of problems arising from
extreme external perturbations involving extended microgravity environments on the normal
functioning of our cardiovascular system. For example, microgravity has been documented to
result in cardiovascular deconditioning, a collection of problems that impairs the cardiovascular
system's ability to readapt to a gravity environment. Indeed, one especially serious problem
faced by astronauts upon reentry from space flight is orthostatic intolerance, an inability to
maintain proper blood perfusion to various vital centers of the body.
In order to ensure the safety of astronauts, who are increasingly exposed to progressively
longer periods of spaceflight and eventually habitation, a full elucidation of our integrated
cardiovascular hemodynamics is required. The focus of this thesis, therefore, will be placed on a
8
battery of experiments sponsored by the National Space Biomedical Research Institute to explore
the effects of long-term microgravity environments on our cardiovascular regulatory systems.
In Section 2, we describe Cardiovascular System Identification (CSI), a novel process by
which to quantitatively and noninvasively characterize short-term cardiovascular regulation. CSI,
which has been proven to provide a useful prognostic indicator of various autonomic disorders,
will provide the primary tools with which we investigate cardiovascular hemodynamics under
various perturbations and stresses. In Section 3 Alterations in CardiovascularRegulation During
Simulated Space Flight,we describe and discuss two experimental protocols that simulate the
cardiovascular effects of microgravity on earth. In Section 4 CSI Calculationof Smyth's
Baroreflex Sensitivity, we investigate the heart-rate baroreflex sensitivity, a popular index of
heart-rate baroreflex function, and propose methods to predict this index using noninvasive CSI
methods. Finally, in Section 5 Visual-Autonomic Influence on Short-term Cardiovascular
Regulation, we begin an initial exploration into the effects of integrated visual pathway
stimulation on short-term autonomic regulation.
9
2
Cardiovascular System Identification (CSI)
2.1 Introduction
Cardiovascular System Identification is a noninvasive process by which to quantitatively
characterize short-term cardiovascular regulation. Specifically, CSI quantifies the short-term
physiologic couplings between such cardiovascular variables as arterial blood pressure (ABP),
instantaneous lung volume (ILV), and instantaneous heart rate (HRT), by analyzing their secondby-second fluctuations. By quantifying these physiologic couplings, moreover, CSI provides a
closed-loop model of such short-term cardiovascular regulatory functions as the heart-rate
baroreflex, circulatory mechanics, ILV->HR, and ILV-*ABP. See Figure 2-1.
As described in Mullen et al., the heart-rate baroreflex characterizes the inverse
autonomic baroreflex coupling between fluctuations in ABP and HRT, which is closely related to
the net autonomic input modulating the sinoatrial node (SA Node). Figure 2-2 summarizes the
relationship between ECG and HRT, while a more detailed discussion of the heart-rate baroreflex
will be presented later.
The ILV-+HR function characterizes the non-causal autonomic coupling between
respiration and HRT and is responsible for respiratory sinus arrhythmia, a process manifested by
an increase in heart rate during inspiration and a decrease during expiration. Previous studies
have linked sinus arrhythmia to an increase in sympathetic activity during inspiration and an
increase in vagal traffic during expiration (Berne 1998).
The ILV-4ABP function characterizes the mechanical stimulation of respiration on ABP
due to alterations in venous return and the filling of intrathoracic vessels and heart chambers
associated with the changes in intrathoracic pressure (Mullen 1997). In contrast to the other
physiologic couplings, the ILV-*ABP function is primarily mechanically mediated.
10
NHR
HR
BAROREFLEX
Heart Rate
ILV-1-HIRTachogram
ILV+HR(HR)
(Autonomic Activity)
Instantaneous
Lung Volume
(ILV)
SA
DE
I
Pulsatile
Heart Rate
(PHR)
Arterial Blood
Pressure
(ABP)
1ILV-ABP
CIRCULATORY
MECHANICS
NABP
Figure 2-1. CSI Model of short-term cardiovascular regulation. Reprinted
from Mullen et aL 1997.
The SA Node is an integrate-and-fire center that closely models the underlying
physiologic process, converting HRT into a pulsatile heart rate signal (PHR), a train of impulses
synchronized with left-ventricular contractions.
Finally, the circulatory mechanics coupling characterizes the ABP waveform that is
generated with each cardiac contraction and is determined by parameters such as cardiac
contractility and the mechanical properties of the arteries and peripheral circulatory system.
11
In addition, two noise sources, NHR and NAp, are also included. NHR models the changes
in HRT not caused by changes in ABP or ILV. These changes may derive from autonomic
cerebral activity that cannot be modeled. Similarly, NAp models the changes in ABP not caused
by ILV or PHR. Such a source may derive from variations in local peripheral vascular resistance
caused by any number of existing physiologic pathways.
ECG
Time
T
PHR Signal
i
2
Time
HR Tachogram
lIT
2
Time
Figure 2-2. Derivation of HRT from ECG.
This CSI model can be represented by the following pair of linear time-invariant
autoregressive moving-average (ARMA) difference equations:
Mn
HRT(t)=
i=1
ABP(t) =
p
aiHRT(t - i) +
biABP(t - i)+ IciILV(t - i) +WHR(t
i=-p'
i=1
diABP(t - i) +
eXPHR(t - i) +
f 1 ILV(t - i) + WABP (t)
where m, n, p, p', q, r, s, and s' are all positive integers and restrict both the model's order and the
causality or non-causality of the associated physiologic couplings. WHR and WAr represent the
noise terms associated with NHR and HAp. Before solving this system of equations, all signals
12
are downsampled to match the bandwidth of the particular transfer function involved. Both
equations can be solved by minimizing the variance of the noise terms in a least squares sense.
The system-identification algorithms are discussed elsewhere (Ljung 1987; Perrott 1996).
Figure 2-3 plots a solution set to the CSI equations comparing cardiovascular regulation
and function during postural changes from supine to standing positions (Mullen 1997). Of
especial importance to this thesis are the four transfer functions: HR-Baroreflex, ILV-4HR,
Circulatory Mechanics, and ILV->ABP. As expected, both the HR-Baroreflex impulse response
and the ILV-+HR impulse response reflect normal physiologic behavior. In response to an
impulse of ABP at time 0, the HR-Baroreflex function immediately decreases at time 0 towards
negative values, representing a reflexive decrease in HRT. Similarly, notice that the ILV-+HR
impulse response function characterizes a noncausal increase in heart rate associated with
inspiration or an impulse of ILV at time 0. This is consistent with the observation that HRT
typically increases in anticipation of corresponding changes in ILV. Finally, notice that the
circulatory mechanics impulse response resembles a single blood pressure pulse with a time delay
of approximately 0.25s, reflecting the interval between the cardiac R-wave and the onset of the
radial ABP pulse (Mullen 1997).
Note that the change in posture from supine to standing positions results primarily in a
shift from parasympathetic toward sympathetic control. Accordingly, both the HR-Baroreflex
and ILV-+HR impulse responses are diminished. This is consistent with previous human studies
that have found heart rate variability to be primarily controlled via parasympathetic pathways
(Akselrod 1985, Saul 1991). In contrast, the mechanically mediated circulatory mechanics and
ILV->ABP transfer functions do not exhibit large changes during postural shifts. Later parts of
this thesis will further reconfirm the effects of postural changes on these autonomically mediated
reflexes.
13
800
NHR
600H
ILV-+HR
HR BAROREFLEX
0.28-
0.0'
4-
-0.2-,'
0
..
-0.4-y
........
S-0.6
-4-
0
'2
2
4
Time (sec)
6
8
Autonomic Activity
(Heart Rate Tachogram)
-0.8.
(02
Time (sec)
Ak
200
SA NODE
00 O
ILV
4.
0.5
'' 1 . 0
5
Atrio-Ventricular Activation
(Pulsatile Heart Rate)
1-
0.0
0.1 0.2 0.3 0.4
Frequency (Hz)
CIRCULATORY
Frequency (Hz)
MECHANICS
0.5
Arterial
Blood Pressure
SA0 NABP
ILV-ABP
6.
3-
Time (sec)
--'
0
0.
-3-
0
5
10
Time (sec)
15
0.0
0.5.
.0.
FresecH)
.5
Figure 2-3. Group-averaged results for subjects in supine (solid lines) and
standing (dashed lines) postures. Reprinted from Mullen et a. 1997.
In order to make quantitative comparisons of these transfer functions, they will first be
parameterized according to the following equations:
14
Peak Amplitude
=
I1niin[h(t)] I for HR Baroreflex
otherwise
max[h(t)]
Area= fh(t)dt
Absolute Area= f Ih(t) Idt
t Ih(t)Idt
Characteristic Time= -'
JI h(t)Idt
These parameters will then be log normalized and compared using a two-tailed paired student ttest.
Unless otherwise stated, each of the experimental protocols outlined below involved
acquiring six-minute segments of all CSI variables according to the protocol outlined in Mullen et
al. In this protocol, the ABP signal is measured from the middle finger of either hand using a
Finapres blood pressure monitor (Ohmeda, Inc). The ILV signal is measured with a Respitrace
system two-belt chest-abdomen inductance plesthysmograph (Ambulatory Monitoring Systems,
Inc.) and calibrated with an 800 cc inflatable spirobag. Data is collected under a random interval
breathing protocol to broaden the frequency content of the recorded physiologic signals for CSI
analysis (Berger 1989). In this breathing protocol, subjects breathe in response to pre-recorded
auditory cues with a mean rate of 12 breaths per minute and inter-breath intervals randomly
varying between 1 to 15 seconds. Finally, all CSI analysis is performed using the methods and
algorithms previously described by Mullen et al and Perrott et al.
15
2.2 Analysis Tools
In order to efficiently process the large volume of CSI data expected to enter the various
studies described in the following chapters, a graphical analysis tool was created in Matlab 5.0 to
provide a flexible software platform from which to quickly prototype and integrate various preand post-processing algorithms with the existing CSI algorithms. This graphical analysis tool
included functionalities ranging from signal annotation to signal deglitching, data calibration, and
push-button interfaces to existing CSI algorithms. HRT is directly calculated from the
electrocardiogram signal in the manner described by Berger et al. Figure 2-4 displays a
screenshot of the application. Unless otherwise noted, all algorithms implemented in the chapters
to follow were similarly prototyped in Matlab 5.0.
For several of the studies described below, data was digitally acquired and
recorded onto digital audio tapes (DAT) by offsite collaborating laboratories that
physically conducted all of the human experimental protocols. This data was
subsequently digitized at MIT via a TEAC RD-120TE DAT recorder, calibrated, and
archived onto several Linux-based workstations for signal processing and CSI analysis.
The complete dataset, CSI algorithms, and associated signal conditioning algorithms is
archived at the data repository of the National Space Biomedical Research Institute.
16
Figure 2-4. Screenshot of the CSI Analysis Tool.
17
3 Alterations in Cardiovascular Regulation During
Simulated Space Flight
3.1
Introductionand Motivation
While the cardiovascular system generally functions well over a large dynamic operating
range, extended periods of space flight or microgravity has been documented to result in
cardiovascular deconditioning, a collection of problems that impairs the cardiovascular system's
ability to readapt to a gravity environment. One especially serious problem faced by astronauts
upon reentry from space flight is orthostatic hypotension (Charles 1994, Buckey 1996).
Traditionally, orthostatic hypotension is defined as a 20 mmHg or greater reduction in
systolic blood pressure or a 10 mmHg or greater reduction in diastolic blood pressure within three
minutes of standing. Upon standing, the blood pools in the vessels of the legs, reducing the
effective circulating volume and subsequently the stroke volume, resulting in drop in blood
pressure. In normal conditions, baroreceptors activate the autonomic nervous system to release
catecholamines to restore blood pressure back towards normal values. When the baroreflex fails,
however, heart rate and blood pressure do not rise adequately, resulting in orthostatic
hypotension. In some cases, the effects of orthostatic hypotension are sufficiently severe such
that astronauts cannot stand erect for an extended period immediately following reentry from
space, and instead experiencing episodes of syncope or fainting. This results in potentially
dangerous situations in the event of emergency egress from spacecraft either on Earth or on other
planetary bodies such as Mars.
During extended periods of microgravity space flight, it is hypothesized that orthostatic
hypotension occurs due to blood pooling in the legs, reducing the preload to the heart, decreasing
cardiac output, and resulting in hypotension. Factors believed to contribute to this process
include altered venous compliance, changes in peripheral resistance arterial baroreflex and heart
18
rate arterial baroreflex, decreases in intravascular fluid volume, and changes in cardiac function
(Cohen Annual Report 1999). Figure 3-1 outlines some of the potential mechanisms underlying
cardiovascular deconditioning and their potential countermeasures. Unfortunately, while current
evidence suggests microgravity induced alterations in cardiovascular regulation are to blame, the
precise physiologic mechanisms responsible for these changes in cardiovascular regulation
remain unknown. In part, our gaps in knowledge are due to the ambiguity and imprecision of
existing data from studies to date on the cardiovascular effects of space flight.
toCircadian
Retun
Conditions of
Space Flight
to
Ert
Re-en
Altered Ves
Compliance
Consequenes&
Requirements
-Adrenergic ixt
Reduced
Altered Cardiac
Altered Cardiac
Attend Cardia
Intravascular
Mechanical
Structure
Electrical
Resistance
-Resistance
baorefle
-lgmscle
rean &tone
Altered
Mcrowascular
-Vascreactivity
-Hormones
-LAcal
Function
-HR barcreflex
intake
-Hormones
-PGE2
-Contractility
Function
-Reduced rascle
Mau
maediatcrs
Altered Cardiac
Negative Impact
on Mission
Success
Cardiac Atrophy
Orthostatic Intolerance
Electrical
Stability
a-syrapathetic
agonists
Potential
Countermeasures
Volume
-Salt, water
- LBNP training
-Lg
-NO synthase
blockera
-
exercise
- Antd-gravity
esyroatlfeic
agonists
suits
-
angictensin
-Sal
and water
loading
--
syapathetic
ageoita
-Mineralo-
- Parasynpathetic
corticcids
- indomehacin
- digitalis
blockers
-Growth
hormone
-Anti-a
hyturic
agents
- Angiotensin
Other
hyperbrcphic
agonists
Figure 3-1. Diagram of the cardiovascular effects of space flight, potential
mechanisms, and possible countermeasures. Reprinted from Cohen Annual
Program Report 1999.
Two studies were therefore initiated to examine the effects of simulated microgravity on
changes in cardiovascular regulation: the Short-Term Bedrest Study and the Long-Term Bone
Demineralization/Calcium Metabolism Study. In both of these studies, the primary goal was to
apply CSI to quantitatively characterize changes in cardiovascular regulation and function, if any,
19
caused by simulated microgravity. With the aid of CSI, the primary hypothesis under experiment
is that the heart rate baroreflex and other autonomically mediated physiologic mechanisms are
altered by exposure to simulated microgravity. Furthermore, alterations in these physiologic
mechanisms play an important role in orthostatic intolerance. These studies are described in
greater depth below.
3.2 Short-Term Bedrest Study
In 1998, a study was initiated at the General Clinical Research Center of the Brigham and
Women's Hospital to study the effects of 16 day simulated microgravity, sleep deprivation, and
disruption of diurnal rhythms on cardiovascular regulation in general and orthostatic intolerance
in particular. In the main, this thesis will focus on the first stimulus while ignoring the effects of
the other stimuli.
3.2.1 Experimental Protocol
While it is difficult in general to reproduce a microgravity environment on earth, the most
commonly used model and the one adopted for this study is prolonged supine bedrest, five-degree
head down tilt.
Fifteen male subjects in excellent health and with anthropometric characteristics similar
to those of American astronauts [age = 33.5 ± 11.3 (SD) years, height = 70± 2.4 (SD) inches,
weight = 76.8 ± 7.6 (SD) kilograms] were selected after screening physical and psychological
examinations. Screening laboratories and tests included a 12-lead electrocardiogram, complete
blood count with differential, chemistry profile, thyroid function tests and urinalysis. The
exclusion criteria included history or evidence for psychiatric disorders, hypertension, diabetes,
coronary artery disease, renal insufficiency, thyroid disease, alcohol or drug abuse, viral hepatitis
20
or anemia. The Brigham and Women's Hospital (Boston, Massachusetts) Research Committee
approved the protocol and informed consent was obtained.
Following the screening procedures, subjects were admitted to the Brigham and
Women's Hospital General Clinical Research Center for Phase 2. During Phase 2, they spent
three (subjects 1-4) or five (subjects 5-15) days undergoing baseline testing and equilibrating to
an isocaloric diet consisting of 200 mEq sodium, 100 mEq potassium, and 2500 ml fluid.
Subjects were then instrumented for CSI in conjunction with a tilt-stand protocol. Data
acquisition for CSI involves non-invasively measuring and recording the surface ECG, ABP, and
ILV, for each subject using an on-line dedicated data sampling and analysis program. The ABP
signal is measured from the middle finger of the left or right hand using a Finapres (Ohmeda,
Inc.) or Portapres (TNO, Netherlands) blood pressure monitor. The ILV signal is measured with
a Respitrace (Ambulatory Monitoring Systems, Inc.) system two belt chest-abdomen inductance
plethysmograph and calibrated with an 800 cc inflatable spirobag. For each CSI data acquisition
period, these signals were recorded for eight minutes. For data acquisition, subjects breathe
according to a random interval breathing protocol (Berger et al. 1989) which requires them to
breathe in response to auditory cues at a comfortable mean rate of 12 breaths per minute, but with
inter-breath intervals randomly varying between one and 15 seconds. Subjects adjust their own
tidal volumes thereby leaving blood gases unperturbed. The random interval breathing protocol
broadens the frequency content of the recorded physiological signals, thereby facilitating CSI.
Data for CSI was acquired with subjects laying supine on a tilt table, then at thirty degrees head
up tilt, then at sixty degrees of head up tilt, and finally standing. Following these CSI data
acquisition sessions, the subjects stood upright quietly for an additional 140 minutes for hormonal
measurements for a parallel study. The test was immediately terminated if a subject experienced
a sudden precipitous drop in blood pressure and had difficulty appropriately responding to
questions, i.e., manifested mental status changes consistent with presyncopal symptoms.
21
During Phase 3, days 5 through 21, subjects then underwent -5* head-down tilt bed rest for
nine (subject 1), 14 (subjects 2-4), or 16 days (subjects 5-15). Subjects were strictly confined to
bed for the entire bed rest period. They ate all meals lying on their side, propped up with one
elbow. They used a bedpan to urinate or defecate. All CSI variables were measured on days 10,
20, and 21. The tilt-stand test with CSI data acquisition described above was repeated at the end
of the bed rest period and again finally in Phase 4 (Post-Bedrest), after two (subjects 1-4) or three
(subjects 5-15) days of normal ambulatory activity.
3.2.2 CSI Results
To reconfirm the effects of postural changes on short-term cardiovascular regulation
presented by Mullen et al., we first compared the changes in parameterized CSI results from
supine to standing positions using data acquired during post-bedrest. These results are
summarized graphically in Figure 3-2. Changes in posture from supine to standing result in both
autonomic shifts from parasympathetic toward sympathetic activity as well as mechanical effects
in left-ventricular pre-load. Accordingly, notice that the peak amplitudes of all coupling
mechanisms, both autonomic and mechanical, are altered. In particular, both the ILV-+HR and
Heart Rate Baroreflex couplings are diminished in the standing posture relative to supine. This is
consistent with findings in humans that the parasympathetic nervous system is normally the
primary mediator of heart rate variability (Akselrod 1981, Saul 1991, 1989).
22
400-
NHR
2-I
00.0 0.1 0.2 0.3 0.4
Frequency (Hz)
ILV-HR
0.
UE
HR BAROREFLEX
0.0 -
10-04
20
4
'
Autonomic Activity
(Heart Rate Tachogram)
'
Tim (scc)
0
2
4
6
SA NODE
Atrio-Ventricular Activation
(Impulse Heart Rate)
8.
0.
CIRCULATORY
ICLTR
0-
0 .1 0.2 0.3 0.4 0.5
MECHANICS
Frequency (Hz)
Arterial
Blood Pressure
6040-20
.
ILV+-6ABP
rie
(s
u126-
E -612.
5
10
Timc (sec)
N ABP
15
8(X) -
,f
400-
0.0
0.1
0.2 0.3 0.4
Frequency (Hz)
0.
Figure 3-2. Group-averaged comparison of supine (solid lines) and standing
(dashed lines) postures in Bedrest subjects during Phase 4 Post-bedrest.
23
Figure 3-3 plots the group-averaged CSI results in supine position during pre-bedrest
(thick solid line), last-day of bedrest (dashed line), and post-bedrest (thin solid line). Similarly,
Figure 3-4 plots the group-averaged CSI results in standing position during pre-bedrest (thick
solid line), last-day of bedrest (dashed line), and post-bedrest (thin solid line).
Notice that the peak amplitude of the heart-rate baroreflex function is noticeably
diminished by simulated microgravity in both supine and standing postures, but more than
recovers to pre-bedrest values three days after bed-rest. Likewise, the peak amplitude of the
circulatory mechanics function is also diminished by bedrest only to recover to pre-bedrest values
three days post-bedrest. This may be perhaps be explained by the fact that while circulatory
mechanics is determined by the mechanical properties of the heart and vascular system, these
parameters are autonomically modulated. For example, a decrease in cardiac contractility, which
is modulated by beta-sympathetic pathways, may lead to a decrease in the peak amplitude of the
circulatory mechanics. These results suggest that extended periods of simulated microgravity
alters the heart-rate baroreflex and other autonomically mediated reflexes.
Finally, Table 3-1 compares all CSI parameters (mean ± standard error) of the impulse
response functions for pre-bed rest vs. end of bedrest (i.e., within an hour of completing the bed
rest period) vs. post-bed rest (i.e., 2 or 3 days following bed rest) for both supine and standing
postures. An * denotes a parameter with a p-value < 0.05 with respect to the corresponding prebedrest parameter. An A denotes a parameter with a p-value < 0.05 with respect to the
corresponding supine parameter. While all parameters are presented, the Peak Amplitude
parameter proved to be the most robust for discriminating differences before and after bed rest.
24
NHR
400-
Ei 100-s
ILV-+-HR
0.0 0.1
0.2
0.3
Frequency
0.4 0.
(Hz)
,0
HR BAROREFLEX
0.4F 0.0 -
10i
100.8-
20 4
Time (see)
6
8
Autonomic Activity
(Heart Rate Tachogram)
0
2
1
6
SA NODE
ILV
Atrio-Ventricular Activation
(Impulse Heart Rate)
84-.
CIRCULATORY
MECHANICS
0.0 0.1 0.2 0.3 0.4 0.5
Frequency (Hz)
Arterial
Blood Pressure
80604020-
-20-....s
0 1
ILV-'ABP
T~m(sec)
..
~12g 60
5
1
$ime (see)
T
15
-6.
-12-
NABP
400 -
200
r
E
0.0
Figure 3-3.
0.1
0.2 0.3 0.4
rrequency (Hz)
0.-
Group-averaged CSI results for Bedrest subjects in Supine
position during pre-bedrest (thick solid line), last-day of bedrest (dashed
line), and post-bedrest (thin solid line).
25
8
NHR
4X)>-
2
200-
0-
ILV-+-HR
0.0 0.1 0.2 0.3 0.4 0.
Frequency (Hz)
HR BAROREFLEX
4-
0.0 -
20-
E
2-0
20
4
6
8
Time (scc)
Autonomic Activity
(Heart Rate Tachogram)
,.
0
2
6
SA NODE
Atrio-Ventricular Activation
(Impulse Heart Rate)
8-
0,
0.0
.CIRCULATORY
0.1 0.2 0.3 0.4 0.5
Frequency (Hz)
MECHANICS
Arterial
Blood Pressure
80-
140-
20
.
S-6-12
0
5
10
ILVBTime
15N
(sec)P
60-
2200
0.0 0.1
0.2 0.3
0.4
Frequency (Hz)
0
Figure 3-4. Group-averaged CSI results for Bedrest subjects in Standing
position during pre-bedrest (thick solid line), last-day of bedrest (dashed
line), and post-bedrest (thin solid line).
26
8
Table 3-1. Comparison of CSI results: supine and standing postures during
*
pre-bedrest, end-bedrest, and post-bedrest (meantstandard error).
denotes a p-value < 0.05 with respect to pre-bedrest. A denotes a p-value <
0.05 with respect to supine. N=16 subjects.
Impulse
Response
Condition
Supine
ILV->HR
In(Absolute Area)
Area
In(Peak Amplitude)
Standing
Supine
Standing
Supine
Standing
In(Characteristic Time)
Supine
Standing
Pre-Bedrest
1.38±0.15
0.42±0.27A
0.02±3.08
-4.71±3.03
2.53±0.16
2.58±0.15
1.02±0.14 1.40±0.17
End Bedrest
1.15±0.16
0.30±0.26^
3.01±2.56
-3.46±2.76A
2.56±0.18
2.43±0.12
1.22±0.15 1.65±0.18
Post-Bedrest
1.25±0.17
0.52±0.27"
6.26±4.61*
-3.47±4.64
2.75±0.15
2.71±0.16
0.77±0.28 1.61±0.19^
-0.76±0.13
-0.82±0.10
-0.72±0.12
-1.39±0.23^
0.16±0.09
0.47±0.10A
1.27±0.10 1.63±0.13^
0.13±0.13
1.49±0.12 1.72±0.13
HR baroreflex Pre-Bedrest
End Bedrest
-1.64±0.19* -1.33±0.15*
-0.38±0.08* -1.05±0.15^ -0.29±0.15*
Post-Bedrest -0.92±0.09 -1.23±0.07*A -0.83±0.25
-1.07±0.20
0.27±0.09
0.31±0.11
1.42±0.13 1.82±0.15"
-0.78±2.65
0.60±2.95
2.66±0.14
2.86*0.19
2.12±0.10 1.93±0.08
2.00±0.14 1.91±0.16
Pre-Bedrest
0.77±0.11
1.26±0.22^
End Bedrest
1.41±0.17*
1.00±0.24
5.76±3.95
4.17±4.02A
2.93±0.15
2.77±0.20
Post-Bedrest
1.44*0.13*
0.94±0.26
5.76±3.35
-2.62±3.97
2.88±0.19
2.88±0.15
1.92±0.13
Circulatory
Pre-Bedrest
4.13±0.03
3.87±0.06"
67.76±2.68 55.48±3.26"
4.20±0.04
3.99±0.06"
0.58±0.04 0.67±0.06
Mechanics
End Bedrest
4.04±0.04*
3.62±0.07*^ 60.47±3.80 45.59±3.02*^ 4.07±0.07
3.79±0.07*^
0.53±0.06 0.67±0.09
Post-Bedrest
4.13±0.03
3.76±0.05"
62.93±2.44 45.92±2.59*^ 4.13±0.04
3.81±0.06*^
0.55±0.05 0.65±0.08
ILV->ABP
1.94±0.13
3.2.3 Discussion
The results of the head-down tilt bedrest study indicate that simulated
weightlessness significantly decreases the gain of the autonomically-mediated Heart-Rate
Baroreflex, corroborating findings from previous studies by Convertino and Fritsch.
Interestingly, the other autonomically-mediated impulse response, ILV-+HR, was not
significantly attenuated by head-down tilt bedrest. This finding indicates that head-down
tilt bed rest does not necessarily cause a syndrome of global autonomic dysfunction
similar to diabetic autonomic neuropathy, but that it can alter the function of
autonomically-mediated cardiovascular regulatory mechanisms.
Head-down tilt also causes changes in the mechanically mediated Circulatory
Mechanics and ILV-+ABP impulse responses consistent with a decrease in intravascular
27
volume. These impulse responses are affected to a lesser degree than the autonomicallymediated Heart-rate baroreflex.
3.3 Long-Term Bone DemineralizationlCalcium Metabolism
Study
In addition to the Short-Term 16-day Bedrest study, a second study was initiated with the
Bone Demineralization/Calcium Metabolism Team of the National Space Biomedical Research
Institute to examine the effects of long-term simulated microgravity on cardiovascular
deconditioning. Previously, the Bone Demineralization/Calcium Metabolism team had proposed
long-term 17-week bedrest studies to analyze the processes underlying bone demineralization and
calcium metabolism in space flight as well as potential countermeasures in the form of in-bed
resistive exercises. Appropriately, 17-weeks reflects the amount of time Mir crews currently
spend in microgravity. Collaboration with this study therefore offered a unique opportunity to
apply CSI techniques to the study of cardiovascular function and regulation in long-term
simulated space flight.
3.3.1 Experimental Protocol
The Bone Demineralization/Calcium Metabolism study will eventually analyze 20
normotensive subjects (10 males and 10 females) over three years. Each subject undergoes a 22week testing period divided into three primary phases. The full protocol can be found in the
original project proposal submitted to the National Space and Biomedical Research Institute
(Cohen 1998). An abridged protocol, omitting procedures not directly relevant to CSI analysis, is
summarized as follows. During Phase 2 (weeks 1-2), all subjects undergo pre-bedrest orientation
and baseline measurements of all CSI variables in both supine and standing postures.
28
Each CSI data acquisition session is repeated twice for a total of 15 minutes as subjects breathe
according to the random interval breathing protocol previously discussed. Subsequently, Phase 3
(weeks 1-17) consists of uninterrupted bedrest. Horizontal movement in bed is permitted and the
subjects will be allowed to rise on one elbow, with the armpit touching the bed, for eating and
reading. They will not be allowed to sit up or dangle their legs over the bed. All CSI variables are
again measured twice for a total of 15 minutes during weeks 8, 12, 15, and 20. Finally, this
protocol concludes with Phase 4 (weeks 1-2), which consists of post-bedrest recovery where
subjects become re-ambulatory. All CSI variables are again measured in both supine and standing
postures for a total of 15 minutes.
3.3.2 CSI Results
To date, only five subjects have completed the entire protocol. To reconfirm the effects
of postural changes on short-term cardiovascular regulation as presented by Mullen et al., Figure
3-5 compares the group-averaged changes in CSI impulse responses from supine to standing
positions using data acquired during post-bedrest phase 4 week 1 (p4_wl). Unfortunately, there
was insufficient data to analyze the corresponding supine-standing comparison in the pre-bedrest
phase. Notice that the peak amplitudes of all coupling mechanisms, both autonomic and
mechanical, are altered. In particular, both the ILV-*HR and Heart Rate Baroreflex couplings
are diminished in the standing posture relative to supine. This is consistent with findings in
humans that the parasympathetic nervous system is normally the primary mediator of heart rate
variability (Akselrod 1981, Saul 1991, 1989).
29
4xE-
NHR
200-
0.
0.0
ILV--HR
0.1 0.2 0.3 0.4
Frequency (Hz)
0.
HR BAROREFLEX
200.
;0 0.4 -
2
~
-10-
Activity.
1.
20-
20
4
Time
(scc)
6
8
Autonomic Activity
(Heart Rate Tachogram)
2-0.8-
-1.2
0
2
s c
6
SA NODE
ILV
10.
Atrio-Ventricular Activation
(Impulse Heart Rate)
8642-
00
CIRCULATORY
0.1 0.2 0.3 0.4 0.5
Frequency (Hz)
Arterial
Blood Pressure
80MECHANICS
80-
6040-
ILV+ABP
0
-6
1 Tme (s c)
4
20
-6-
2
-12
S
0
5
10
mcTime
15N
ABP
(sec)
2200
0.0 0.1----.
Figure 3-5. Group-averaged comparison of supine (solid lines) and standing
(dashed lines) postures during Post-bedrest Phase 4 Week 1.
30
Figure 3-6 plots the group-averaged CSI results in supine position, Pre-bedrest p2_wl
(thick solid line), End-bedrest p3_w17 (dashed lines), and Post-bedrest p4_w l (thin solid line).
Similarly, Figure 3-7 plots the group-averaged CSI results of the current five subjects in standing
position, Pre-bedrest p2_wl (thick solid line), End-bedrest p3_w17 (dashed lines), and Postbedrest p4_w l (thin solid line). Finally, Table 3-2 compares all CSI parameters (mean ± standard
error) of the impulse response functions for Pre-bedrest vs. End-bedrest vs. Post-bedrest for both
supine and standing postures. An * denotes a parameter with a p-value < 0.05 with respect to the
corresponding Pre-bedrest parameter. An A denotes a parameter with a p-value < 0.05 with
respect to the corresponding supine parameter. While all parameters are presented, again the
Peak Amplitude parameter proved to be the most robust for comparing differences before and
after bed rest.
Notice that the peak amplitude of the heart-rate baroreflex function is statistically
diminished by the end of bedrest but more than recovers to pre-bedrest values two weeks after
bed-rest. In contrast, like the Short-term Bedrest study, the peak amplitude of the ILV-+HR
transfer function is not altered in a statistically significant sense. Interestingly, the ILV->ABP
transfer function also shows a statistically significant change caused by bedrest. This difference,
however, may be an artifact of the small sample size (data from only 3 subjects were compared
after elimination of outliers in the paired t-test). While only a minimal sample set of data was
available for this preliminary study, the results are encouraging and corroborate the results of the
Short-term Bedrest study, suggesting that the heart rate baroreflex and other autonomically
mediated physiologic mechanisms are altered by exposure to long term simulated microgravity.
31
NHR
400-
S2001~
00.0 0.1
ILV-+HR
0.2
0.3 0.4
Frequency (Hz)
30-
0. i
HR BAROREFLEX
",
,
0.4 -~
Y20
S0.4-
-1020-
~-0.8-/
201
,
204
Time (scc)
,
6
8
Autonomic Activity
(Heart Rate Tachogram)
-1.2
0
6
2
Time (sec)
A
SA NODE
ILV
Atrio-Ventricular Activation
(Impulse Heart Rate)
S2011
CIRCULATORY
MECHANICS
0.0 0.1 0.2
0.3 0.4 0.5
Frequency (Hzi)
Arterial
80-
Blood Pressure
20-
ILV-ABP
g12-
6
400-
6-
200
0E
-12-.
0
5
10
Time (Sec)
01
15
NABP
0.0
0.1
0.2
0.3
0.4
Frequency (Hz)
0
Figure 3-6. Group-averaged CSI results for 5 Bone subjects in supine
position during Pre-bedrest p2_wi (thick solid line), End-bedrest p3_w17
(dashed lines), and Post-bedrest p4_ w2 (thin solid line).
32
8
4x-
NHR
00.0 0.1 O.2 0.3 0.4
Frequency (Hz)
ILV-+HR
30-
0.
HR BAROREFLEX
520-
E 0.01
-10-
20-
,*.
,
,
-0.8-
'
Autonomic Activity
(Heart Rate Tachogram)
-1.2 ,.
0
6
2
Time (sec)
SA NODE
ILV
Atrio-Ventricular Activation
(Impulse Heart Rate)
10.
86-0
2 V
CIRCULATORY
MECHANICS
0.0 0.1 0.2 0.3 0.4 0.5
Frequency (Hz)
Arterial
Blood Pressure
80604P
4020-20
ILV-+ABP
S
5
c) 4
3e(s
126-
EE-6'
0
5
10
Tiic (scc)
15
NABP
200-
0.
0.() 0.1
0.2 0. 0.4
Frequency (Hz)
.
Figure 3-7. Group-averaged CSI results for 5 Bone subjects in
standing position during Pre-bedrest p2_wl (thick solid line), End-bedrest
p3_w17 (dashed lines), and Post-bedrest p4_w2 (thin solid line).
33
8
Table 3-2. Comparison of CSI results: supine and standing postures during
phase 2 week 1 vs. phase 3 week 17 vs. phase 4 week 1. (mean t standard
error). * denotes p-value < 0.05 with respect to pre-bedrest. A denotes pvalue < 0.05 with respect to supine. N=5 subjects.
Impulse Response
ILV->HR
HR baroreflex
Condition
In(Peak Amplitude)
Supine
Standing
Pre-bedrest
2.69±0.29
2.36±0.05
End-bedrest
2.01±0.15
Standing
In(Absolute Area)
Supine
Standing
In(Characteristic Time)
Supine
Standing
-1.70±3.88 -16.52±16.98 3.63±0.23 3.51±0.32 0.96±0.18 1.41±0.32
-8.68±8.14
3.62±0.15
1.53±0.07*
Post-bedrest 2.44±0.19
1.52±0.18A
-5.12±7.18 -13.88±9.88 3.87±0.16 3.57±0.17 1.22±0.18 1.95±0.08^
Pre-bedrest
-0.12±0.11
-0.19±0.14
-0.51±0.24
End-bedrest -0.72±0.22*
ILV->ABP
Area
Supine
-0.53±0.13
-0.38±0.10
0.31±0.29 0.48±0.22 1.32±0.13 1.13±0.32
0.37±0.15
1.47±0.11
Post-bedrest -0.16±0.14 -0.98±0.07*A -0.41±0.09
-1.30±0.37
0.61±0.11 0.53±0.13* 1.12±0.11 1.86±0.15^
Pre-bedrest
2.05±0.31
9.52±9.49
3.58±0.29 2.89±0.47 1.78±0.10 1.52±0.03
End-bedrest
1.93±0.10
Post-bedrest 1.86±0.17
Circulatory Mechanics Pre-bedrest
4.06±0.07
End-bedrest
3.87±0.08
Post-bedrest 3.98±0.06
1.22±0.56
8.05±10.07
6.78±4.31
1.87±0.21
3.13±0.14
1.67±0.08
-2.68±4.23 11.78±9.88 3.23±0.12* 3.82±0.10A 1.89±0.08 2.35±0.05^
3.48±0.21^ 20.45±2.50 12.33±0.70 2.96±0.11 2.52±0.00 -0.66±0.07 -0.44±0.14
14.53±1.27
2.61±0.12
-0.80±0.09
3.54±0.08^ 14.85±0.50* 10.90±1.03^ 2.69±0.03* 2.45±0.06A -0.66±0.04 -0.27±0.05^
34
4 CSI Calculation of Smyth's Baroreflex Sensitivity
Heart rate baroreflex sensitivity has been demonstrated to be a useful prognostic indicator
of various cardiovascular diseases. Current methods to assess the heart rate baroreflex sensitivity,
however, are not only difficult to obtain, but also require invasive and difficult to administer
pharmacological or mechanical interventions. A joint study was therefore initiated with Dr. Ernst
Raeder of the Veterans Affairs Medical Center NYC with the objective of creating algorithms to
estimate a quantitative measure of heart-rate baroreflex sensitivity from noninvasive
Cardiovascular System Identification methods with the eventual goal of supplanting current
protocols.
4.1 Introductionto Heart Rate Baroreflex Sensitivity
The heart rate baroreflex is a common cardiovascular reflex that plays an important role
in the beat-by-beat homeostatic regulation of arterial blood pressure in the presence of
cardiovascular perturbations. The feedback arm of this reflex is comprised of pressoreceptors in
the carotid sinus and aortic arch that are activated by changes in arterial blood pressure. These
pressoreceptors activate the glossopharyngeal nerve, increasing vagal stimulation to mediate
changes in heart rate. Decreases in arterial blood pressure lead to a compensatory increase in
heart rate that then increases cardiac output, restoring arterial blood pressure towards homeostatic
norms. In contrast, increases in arterial blood pressure result in reflex decreases in heart rate and
a subsequent reduction of arterial blood pressure (Handbook of Physiology, 755).
In terms of short-term cardiovascular regulation, the heart rate baroreflex plays several
important roles, including maintaining sufficient arterial blood pressure during postural changes
from supine to standing positions that might otherwise lead to syncope (Handbook of Physiology,
35
755). In addition, the heart rate baroreflex has also been found to be an important clinical
prognostic indicator of cardiovascular health, especially in patients after myocardial infarction
and those with congestive heart failure (Rea 1990, Bigger 1989, Billmanl982).
Historically, a number of techniques have been established to quantify the heart-rate
baroreflex. These include: 1) electrical stimulation of the carotid sinus nerves; 2) the use of
pressurized neck chambers to vary the transmural pressure across the carotid sinuses and hence
the vascular diameter, stimulating the carotid baroreceptors; and 3) the injection of vasoactive
drugs to vary arterial blood pressure. Each of these techniques, however, has various advantages
and disadvantages. For example, while electrical stimulation of the carotid sinus nerves permits
for repeatable stimuli, it artificially activates the carotid sensors because activation occurs away
from the normal site of the pressoreceptors. Similarly, in the case of neck chambers, the
disadvantages include difficulty of use, an inability to stimulate the aortic baroreceptors, and
subject awareness of stimuli that may result in unwanted autonomic influences. Because of these
disadvantages, the use of vasoactives such as angiotensin and phenylephrine to vary vessel
diameters and hence blood pressures has become popular in the calculation of heart-rate
baroreflex (Handbook of Physiology, 755).
Smyth et al. was the first to introduce a quantitative measure of heart rate baroreflex
sensitivity using intravenous administration of the peripheral vasoconstrictor, phenylephrine, to
induce a transient increase in arterial blood pressure above steady-state levels. Figure 4-1 plots a
typical pressure response to phenylephrine. In Smyth's protocol, he defined the heart-rate
baroreflex sensitivity, Phe-BRS, as the slope of a linear least squares regression of R-R intervals
with the preceding value of systolic blood pressure (SBP). The choice of regression variables and
sample delay was empirically determined. Other potential regression variables, such as pulse
pressure or diastolic pressure were found to have less statistical correlation.
36
Arterial Blood Pressure
Injection
100
I
20
10
40
50
60
70
sec
HeartRate
70A
V
00
*
A
1r2
60
V
-
4
I
27
sAte
0
020
3040
s0o6
70
Figure 4-1. Typical arterial blood pressure response to phenylephrine.
Heart rate is reduced in compensation to drive arterial blood pressure back
to steady-state values.
Unfortunately, Smyth's protocol suffers from several drawbacks. First, Phe-BRS
requires intravenous injections, which limits its ease-of-use and widespread clinical adoption.
Second, Phe-BRS is not capable of distinguishing or isolating the feedback mechanism of arterial
blood pressure on heart rate from the feedfoward effect of heart rate on blood pressure. Third,
Phe-BRS has limited reproducibility due to several factors including: 1) Difficulties in identifying
the exact beginning of phenylephrine-induced changes in blood pressure from normal alterations
in pressure and 2) Natural variations in the central influence that modulate baroreflex behavior
(Handbook of Physiology 759). While some of the influences comprising the third factor may be
unavoidable, we hope to eliminate the first and second drawbacks via CSI analysis.
37
4.2 Experimental Protocol
This study examined 13 healthy normotensive human patients at the Department of
Veterans Affairs Medical Center using a concatenated protocol which consisted of the CSI
protocol as outlined by Mullen immediately followed by the phenylephrine protocol as described
by Smyth. For the Smyth protocol, multiple serially graded doses of phenylephrine injections
were repeated. For each subject, therefore, two sets of data were acquired, a CSI data set and a
phenylephrine data set. For both protocols, ECG, ABP, and ILV were digitally recorded onto a
personal computer at 360 Hz via a single lead surface electrocardiograph, Finapres 2300, and
Respitrace, respectively.
4.3 Calculating Smyth's Baroreflex Sensitivity
For each subject, every region of data that exhibited an ABP(t) increase of at least 25
mmHg for at least 20 seconds was selected for analysis. These conditions were chosen to reflect
those observed by Smyth et al. The same portion of each pressure response, e.g., the 20-30
second rise in ABP(t) from the beginning of the response to the peak pressure was selected for
analysis. Before analysis, all SBP[n] and R-R[n] data points within this response with values
greater than or less than two standard deviations from their respective means were considered
outliers and omitted from further analysis. For each valid data segment, the beat-by-beat systolic
pressures were linearly regressed against the successive value of R-R interval using the method of
least squares. The slope of this regression line then provided the heart-rate baroreflex sensitivity,
Phe-BRS. Least-squares regressions with p-values greater than 0.05 were omitted from further
analysis.
38
In Smyth's original analysis, he noticed that Phe-BRS was dependant on the respiratory
cycle, with a larger value during expiration than inspiration. One potential explanation is the
activation of Po2 and Pco2 chemoreceptors on heart-rate control. Other theories suggest that,
"central structures involved in breathing rhythmicity interfere with the integrating mechanisms of
the baroreceptor-heart rate control" (Handbook of Physiology). The regression analysis was
therefore performed twice, once regressing over all data points in a pressure response, Phe-BRSali,
and once regressing over only those data points that began or occurred during expiration, PheBRSex. Figure 4-2 plots a typical regression.
Phe-BRSX and Phe-BRSall for Subject 13
1100
p-value - 2.61e-6
p-value . 1.45e-6
Phe-BRS.A: Slope. 2.5 ms/mm'-lg
1050-
Phe-BRS : Slope . 3.4 ms/mmHg
1000*
0r5
-)
0*
-
-
0
900-
8001
75
160
165
170
175
195
185
190
180
Systolic Blood Pressure[n] (mmHg)
200
205
J.-(
210
Figure 4-2. Phe-BRS.11 (blue filled points + red empty points) and Phe-BRSe,
(blue filled points) for subject 13. The red dashed line corresponds to the
Phe-BRS.11 regression. The blue solid line corresponds to the Phe-BRS,,
regression.
39
To calculate a representative Phe-BRSan and Phe-BRSex for each subject, all valid pressure
responses recorded for each subject were analyzed and the results averaged. For each subject,
Phe-BRSs greater than or less than two standard deviations from their respective means were
considered outliers and omitted from the average. Figure 4-3 plots the average Phe-BRS - two
standard deviations for each subject.
Phe-BRS ex and Phe-BRSal for all Subjects
40 r
35
F
'4
-. 30
E
U25
Cn 20
CL 15
4
9
A
C,
:4
10
ca
4)'
C.
0
-5
11
I
I
I
I
I
I
12
13
14
15
17
18
Subject
I
3
I
5
I
6
I
'
7
8
9
Figure 4-3. For each subject, the mean Phe-BRSa.i (red empty circles) and
Phe-BRS,, (blue filled circles) are plotted along with the range of two
standard deviations.
Note that for some subjects, it was not possible to calculate one or both of their Phe-BRSs either
because analyzable pressure response data did not exist or because the linear regressions resulted
in p-values greater than 0.05. In addition, note that Phe-BRSan did not statistically differ from
40
Phe-BRSex. Because of this, future analysis ignored the effects of the respiratory cycle on PheBRS and used Phe-BRSu for all future comparisons.
4.4 CSI Results
Using the CSI data set for each subject, CSI analysis was then subsequently performed
for each subject. All protocols and algorithms are outlined in Mullen et al. Figure 4-4 plots the
group-averaged CSI results while Table 4-1 summarizes their parameterization.
Table 4-1. CSI results (meanwstderr). N=13 Subjects.
Impulse Response
ILV-+HR
HR Baroreflex
ILV->ABP
Circulatory Mechanics
Ln (Peak Amplitude)
2.37±0.21
-1.18±0.14
1.65±0.11
4.24±0.06
Area
5.49±1.25
-0.29±0.06
0.61±3.45
4.63±0.71
41
Ln (Absolute Area)
3.06±0.19
-0.52±0.15
3.19±0.12
1.42±0.16
Ln (Characteristic Time)
0.18±0.21
1.04±0.06
1.68±0.04
-0.69±0.09
XN
HR
2W -
M
ILV-+HR
0.0
0.1 0.2 0.3 0.4
Frequency (Hz)
20-
0.
BAROREFLEX
,
L10-
*40.0-
S-0.4
2020 4
Tinc (scc)
8
Autonomic Activity
(Heart Rate Tachogram)
0
2
'
6
Time (sec)
SA NODE
ILV
Atrio-Ventricular Activation
(Impulse Heart Rate)
2
0.0
CIRCULATORY
MECHANICS
0.1 0.2 0.3 0.4 0.5
Frequency (Hz)
Arterial
Blood Pressure
80604020-20
0.5 Timksec) 1.5
0.0
ILV-'ABP
2.1
12. 6502 -62
0
5
10
Time (sec)
15
NABP
2(W) 1
.p
100-
0'
.
0
0
-2.
0.3 0.4
Frequency (Hz)
0.
Figure 4-4. Group averaged CSI results.
42
8
4.5 Calculating Heart-Rate Baroreflex Sensitivityfrom CSI
Several different approaches to estimate Phe-BRS from CSI analysis were evaluated. In
this section, we describe three different approaches and discuss their results.
4.5.1 Method 1
The first method for estimating Phe-BRS from CSI methods is flow-diagrammed in
Figure 4-5. First, the portion of the phenylephrine data set corresponding to the pressure ramp
response to phenylephrine is downsampled to 1.5 Hz and the mean removed to create AILVp,1.5(t),
AABPp,1 .5(t), and AHR, 1 .5(t). Using the CSI transfer functions previously calculated, AHRp,1.5(t),
the changes in HRT or autonomic activity that CSI predicts would occur given the ABP ramp and
ILV signal associated with an injection of phenylephrine, can be calculated as the following sum
of convolutions:
AHRp,1.S (t) = AILV, 1.5 (t * HLv-+HR (t) + AABP,1. (t) * HABP4HR
(
In order to convert this predicted change in HRT into R-R intervals, we adopt the Integral
Pulse Frequency Modulation (IPFM) model described by Hyndman and Mohn and summarized in
Figure 4-6. IPFM models are especially useful in describing physiological processes that convert
a continuous signal into a discrete signal. The input signal, composed of a DC term and a
modulating signal m(t), is integrated over time. Whenever the integrated value y(t) equals a fixed
threshold value I, an event is generated and the integrator is reset to zero. In the absence of a
modulating signal, the output signal x(t) is simply a periodic impulse train with constant intervals
equal to I (Boer 1985).
43
Phenylephrine Ramp Data
ECGP
ILV ,3(t)
ABP,,310(t)
AILV, 13(t)
AABP ,1s(t) SBPP [n]
3,(t)
RR [n]
CSI Data
AILVLS(t)
_CSI
H
HA-BP-HHR
AABPus(t)
AHR1
5(t)
A HR ,,1.5
(t)
IPFM
A
1 = JHR ,,1.s
lk
H
+1
(O dt
RIZ [n]
Figure 4-5. Block Diagram of Method 1.
I;
tim
rset.
1 +m(t)
..:
y(t)
x(t)
1 +m(t)
time
y(t)
time
x(t)
time
Figure 4-6.
Diagram of an IPFM model.
Karemaker 1985.
44
Reprinted from Boer and
To convert HRT to R-R intervals, we adapt the LPFM model as follows:
tk+1
T= J(1+m(t))dt
tk
tk+1
+
1= JH+ Iiim(t)lt
tk
tk+H
1 beat=fHR+ AHR )beats dt
4
sec dtc
where m(t) represents autonomic modulation of the SA node's base firing rate and T is the
integrator's threshold value or the mean R-R interval in the absence of autonomic modulation of
the SA node's base firing rate. Note that 1/T is simply the mean heart rate. In this equation,
given a starting time tk, we may easily calculate tk+,1. Before we can use this IPFM model,
however, we need to add a mean constant heart rate such that the number of predicted RR
A
intervals, RR p [n], equals the number of R-R intervals in the original phenylephrine ramp data,
A
RR,[n]. Finally, we linearly regress RRp[n] with SBP,[n-1] using the method of least squares.
The slope of this regression, BRSfetod 1,is the heart rate baroreflex sensitivity predicted by CSI
analysis. Figure 4-7 summarizes the BRSMetod I for each subject.
45
Method 1
35
30-
25E
-
E
20
20
T
5
OS
11
12
13
15
14
Figure 4-7. The mean BRSMethod
each subject.
To compare Phe-BRS with BRSMeth
17
18
Subject
1
1, Figure
3
5
6
7
8
9
t 2 standard deviations are plotted for
4-8 plots each subject in a coordinate space where
the x-axis represents that subject's Phe-BRS while the y-axis represents that subject's
BRSMethOd 1-
Superimposed on this coordinate space is the line of unity. The normalized mean square error
between these two indices can then be calculated according to the following equation:
2
NMVSE
k
k,=1
BRSSmyth(n) - BRSMthdl(n)
BRSSmyth(f)
The normalization eliminates the dependence on the dynamic range of the data while the
normalization by the set size eliminates the dependence on the size of a particular data set. For
46
Method 1, the NMSE=0.102. In addition, a two-parameter linear least-squares regression which
fit the data to the equation y = ax + b was also calculated. A p-value of 0.0014 indicates that
there is a statistically significant linear relationship between the Phe-BRS and
BRSMethod 1-
Finally, a one-parameter fit which fit the data to the equation y = ax was also calculated.
In this
one-parameter fit, we minimized the sum of squared errors.
Method 1
25
e=0.7
p-vlue=.0.7
Line of Unity: NMSE
2 parameter fit Slop e=0.1927
1 parameter fit: Slop
20 k
~=0.Z
p-au=.047
E
j15
S10
C
U
5
0
'C
0
5
15
10
Smyth Phe-BRS [ms/mmHg]
20
25
Figure 4-8. Comparison of Phe-BRS and BRSMethod 1.
Unfortunately, Method 1 still depends on the availability of phenylephrine data, which forces the
clinician or researcher to intravenously deliver pharmaceuticals, rendering Method 1 no more
useful than Smyth's original protocol. Instead, a protocol that can infer Phe-BRS from only
noninvasive CSI data is preferred. To this end, two additional approaches were tested. Methods
2 and 3 in the following sections outline these two different approaches.
47
4.5.2 Method 2
The second method is flow-diagrammed in Figure 4-9. First, we create an artificial zero
mean 1.5 Hz 20 sec, 25 mmHg blood pressure ramp signal and convolve this signal with the
previously calculated
HABPHR(t)
to predict AHRp, 1.5(t), the changes in HRT or autonomic activity
that CSI predicts would occur given such a perturbing pressure ramp. In order to convert
AHRp, 1.5(t) into RR[n] interval data, we again employ an IPFM model. Rather than adding the
mean heart rate from phenylephrine data, however, we assume that all physiologic variables and
processes are stationary, i.e., that the statistical properties of HRT, ABP, and ILV do not fluctuate
over time. If HRT is stationary, then we may add the mean heart rate from the CSI data set rather
than from the phenylephrine data set. To compare Phe-BRS with
BRSMethod 2,
Figure 4-10
plots each subject in a coordinate space where the x-axis represents that subject's PheBRS while the y-axis represents that subject's BRSMethd
2.
Superimposed on this
coordinate space is the line of unity. For Method 2, the NMSE=0.162. As expected, the
NMSE for Method 2 slightly larger than that for Method 1 because we have reduced the
amount of phenylephrine information used for this pure CSI estimation. Again, using a
linear least squares regression, we note that there is a significant linear relationship between the
Phe-BRS and BRSMethod
2.
48
ABP Ramp
2s
-12.5mmHg
CSI Data
AILV1.5t)
AABPI.S(t)
CSI
HABPIHR
AHRH.S(t)
HR
A HRp,1.s(t)
IPFM
4+1
1=
HR,,1.s(t)dt
RRp(n)
Figure 4-9. Block Diagram of Method 2.
Method 2
25 r
7
20
I
Line of Unity: NMSE=0.1627
2 parameter fit- Slope-z0.53 p-value=0.00427
1 parameterfrt Slope=0.83x
.70
U
E
E
7
15 -
7
0
1,)
S10
U
X.
7
0
5
10
15
Smyih Phe-BRS [ms/mmHg]
Figure 4-10. Comparison of Phe-BRS and
49
20
BRSMethod 2.
25
4.5.3 Method 3
The second approach to estimating Phe-BRS from only CSI data entails eliminating the
IPFM model completely from the algorithm. This approach is outlined in Figure 4-11. First, the
CSI data originally acquired at 360 Hz is converted to beat-by-beat data where each beat-by-beat
value is simply the average of the 360 Hz data over each beat. Second, rather than calculating the
HABPjHR(t) transfer function at 1.5 Hz, we substitute the beat-by-beat data (ABP[n], ILV[n], and
RR[n]) into our ARMA equations to calculate
HABP-+RR[n]
and other beat-by-beat transfer
functions. Finally, we convolve an artificially created zero-mean 25 mmHg 20 sec ABP[n] ramp
A
with
HABP-RR[n]
to directly predict RR p [n]. To compare Phe-BRS with BRSMethod 3, Figure
4-12 plots each subject in a coordinate space where the x-axis represents that subject's
Phe-BRS while the y-axis represents that subject's BRSMethod 3. Superimposed on this
coordinate space is the line of unity.
As expected, the NMSE for Method 3 is significantly larger than that for Method 1 or
Method 2. In addition, from the linear least squares regression, there is only a marginally
significant linear relationship between the Phe-BRS and BRSMethOd 3. The most probable reason is
the loss of information in HABpaRR[n] that resulted from decimation of CSI data to beat-by-beat
values prior to CSI analysis. A second reason may lie in the artificiality of the ABP(t) ramp.
Physiologic ABP ramps induced by phenylephrine may perhaps be nonlinear or have different
characteristics than those reported by Smyth.
50
ABP Ramp
-12.5mmHg
CSI Data
AILV[n]
BBCSI
AABP[n]
H
ARR[n]
RRp(n)
Figure 4-11. Block Diagram of Method 3.
Method 3
25
7-
7
E
E
7
k
20
Line of Unity: NMSE=0.191
2 parameter fit Slopeao.32
1 parameter fit Slope=0.64
7
p-vaIue~0.05S
5F
7
7
V)
C,
7
7
.7
7
7
7
7-
7
7
0)
10 k
7.
7
7
7
7
0
0
0
0.
U
5
7
7
.7
7
7,
.7
7
0
0
.7
7-c
5
10
15
Smyth Phe-BRS [ms/mmHg]
Figure 4-12. Comparison of Phe-BRS and
51
20
BRSMethd
25
.
3
In an attempt to better approximate the actual physiologic ABP ramp responses seen in
the phenylephrine data set, the parameters of the artificial perturbing ABP ramp used in Method 3
(Figure 4-11) were varied in two ways. First, we replaced the artificial Smyth ABP ramp of 25
mmHg over 20 sec with one that reflected the average rise and run in ABP induced by
phenylephrine across all 13 subjects over all valid pressure segments. This resulted in an
artificial ABP ramp of 36.8 mmHg over a period of 43 sec. The results of using this group-
averaged ABP ramp in Method 3 is shown in the top graph of Figure 4-13. Notice that the NMSE
for Method 3 was larger with the group-averaged ABP ramp (NMSE=0.226) than with the
original Smyth ABP ramp (NMSE=O.191). One potential reason is that an ABP ramp of 36.8
mmHg over 43 seconds may outstrip the linear range of the model for some subjects into
nonlinear regions where CSI cannot identify.
To further refine this approach, therefore, we then created custom perturbing ABP ramps
for each subject. For each subject, we replaced the artificial Smyth ABP ramp of 25 mmHg over
20 sec with one that reflected the average rise and run in ABP induced by phenylephrine over all
valid pressure segments in that specific subject. Table 4-2 lists the ABP ramps used for each
subject while the bottom graph of Figure 4-13 plots the results of using these subject-specific
group-averaged ABP ramps in Method 3. As expected, the NMSE decreased from 0.226 to
0.195.
52
Method 3: ABP ramp from group averages
25Line of Unity: NMSEm0.226
2 parameter fit SlopexO.31
1 parameter fit Slope=0.66
X 20 15 -
p-value=0.091
'0
to
510
-
Smyth Phe-BRS
Method
UX20 -
0
-@2
OA
15
[ms/mmHg]
20
25
3: ABP ramp from individual subject averages
Line of Unity: NMSE=0.195
parameter fit SlopezO.36
I parameter fit Slope=0.67
p-value=0.047-
-E--5
0
15
10
Smyth Phe-BRS [ms/mmHg]
5
20
25
Figure 4-13. Phe-BRS VS. BRSmethod 2 with modified ABP ramps. The top
graph uses an ABP ramp averaged across all subjects and all analyzable
pressure segments. The bottom graph uses an ABP ramp averaged across
all pressure segments for each subject.
Table 4-2. Parameters of the perturbing ABP ramp used in Method 3.
Subject
11
12
13
14
15
17
18
3
5
6
7
8
9
Rise (mmnHg)
29.1
52.9
40.1
34.0
34.0
33.3
29.3
37.4
27.5
89.2
33.1
27.9
20.0
53
Run (sec)
33.5
22.1
54.2
36.2
68.7
20.8
35.1
43.1
28.5
129
69.8
45.0
26.0
4.6 Discussion
Using the algorithms previously described, we have presented three different methods for
extracting the Smyth Heart-Rate Baroreflex Sensitivity from CSI analyses. While Method 1 still
requires the physician to deliver vasoconstrictors into the patient's bloodstream, Methods 2 and 3
are noninvasive protocols that require only the measurement of ABP, ECG, and ILV in order to
provide a reasonable estimate of Smyth's Heart-Rate Baroreflex Sensitivity.
As expected, as we increase the amount of phenylephrine information available to our
estimation models, our normalized mean squared errors decrease. However, there will always be
some discrepancy between Smyth's Heart-Rate Baroreflex Sensitivity and that calculated using
CSI methods because Smyth's regression only takes into consideration one delay value. In other
words, Smyth essentially employs a moving average model with a delay sample of one beat. In
contrast, CSI uses an autoregressive moving average model that takes into account multiple delay
values. In many senses, therefore, CSI methods capture a more sophisticated and complete
snapshot of short-term cardiovascular regulation than that captured by Smyth. When this aspect
is taken into consideration along with the difficulty-of-use and repeatability issues of Smyth's
protocol, a strong case can be made for the utility of CSI methods.
54
5 Visual-Autonomic Influence on Short-term
Cardiovascular Regulation
5.1 Introductionand Motivation
It has long been known that visual sensory data is integrated into the central nervous
system to establish postural and motion equilibrium (Robinson 1977). For example, Howard et
al. demonstrated that static visual cues are sufficient to convince supine subjects of verticality
while a moving visual scene is sufficient to convince stationary subjects of self-rotation. In
addition, it is well established that visual illusions such as rotation, translation, or tilt of a
subject's visual surrounding induces compelling illusions of perceived self-motion (Fischer and
Kornmuller 1930, Dichgans and Brandt 1978, Held 1978), static tilt (Witkin and Asch 1948), and
tumbling (Howard and Childersen 1993).
Previous studies by Mullen et al. have demonstrated that changes in posture from supine
to standing positions triggers cardiovascular reflexes, increasing parasympathetic control and
decreasing sympathetic activity. Based on established visual-autonomic shared neural pathways
in both animals and humans (Yates 1992 1993 1994 1995, Biaggioni 1998), therefore, it was
hypothesized that visual illusions of standing should also trigger the same autonomic
cardiovascular reflexes. If so, the significance of these findings would be that visual environment
stimuli may be used in the future to enhance cardiovascular and/or vestibular countermeasures for
long-duration space flight. Unfortunately, the degree to which the visual system modulates shortterm cardiovascular regulation has yet to be established. A repeated measures study was
therefore undertaken to examine and quantify cardiovascular regulatory responses during actual
and visually-induced virtual head-upright tilts.
55
5.2 Experimental Protocol
A two-phase study was conducted with 16 healthy, normotensive, non-smoking human
subjects (8 male, 8 female, ages 20-50 yrs) in cooperation with the Neurovestibular Adaptation
Team of the National Space Biomedical Research Institute. The full experimental protocol is
detailed in the 1999 Annual Project Report submitted by Ramsdell et al. However, an abridged
version relevant for this study is presented as follows. Before each phase, subjects were asked to
refrain from consuming caffeine or performing rigorous exercise for 24 hours before each study
session. Phase 1 consisted primarily of acquiring control measurements. CSI data was acquired
while subjects were physically tilted from eight minutes of supine posture to five minutes of 800
head upright posture via a tilt table.
Part 2 of this study then studied the effects of visually induced virtual tilt in modulating
autonomic cardiovascular reflexes. First, baseline CSI measurements were acquired from all
subjects in the supine position while the subjects' eyes were closed. Following this baseline
measurement, subjects were subjected to two different types of visual illusions to convince the
subject of verticality: 1) Mirror Bed and 2) Device for Orientation and Motion Environments
(DOME).
The mirror bed consisted of a mirror mounted over a subject lying supine and pivoted to a
450 angle above the subject's face to align surrounding visual vertical cues with the subject's
longitudinal body axis. The bed was raised to four feet tall to have subjects view the surrounding
room at a height as close to normal eye level as possible. In addition, the bed was positioned so
that the subjects viewed instrument consoles and a doorway to provide strong vertical polarity
cues. After positioning the subject on the bed relative to the mirror, a footrest was clamped in
place to provide a tactile sense of a floor underneath and to control for feet orientation. Care was
taken to avoid applying pressure with the footrest to minimize muscle pump activity in the lower
extremities. After the initial baseline CSI measurements with eyes closed, subjects were asked to
56
open their eyes to the 450 mirror for thirteen minutes. The subjects were asked to quantify their
perception of body tilt position in degrees, with 00 equal to no tilt and 900 equal to standing
upright, after 3 minutes and 13 minutes of exposure with the CSI measurements obtained in
between. These results are summarized in Table 5-1. Figure 5-1 summarizes the mirror-bed
protocol.
90-
I.....I
M Bodey
G Head
504F
P
Random..Inter.a.
IL
30-
~nBMir
I
I
I
0
I
I
I
£
I
I
£
I
£
5
I
1ii
15
20
Elapsed Time (min)
Figure 5-1. CSI data is obtained during periods I, II, and III. Perception of
body and head tilt orientation were obtained after 3 and 13 min. Symbols
depict means * stdev. Reprinted from Ramsdell 1999.
In addition to the mirror bed, visually induced illusions of tilt and rotation were elicited in
subjects lying supine by a full-field virtual environment generator known as DOME. In DOME,
subjects lay supine with their head positioned near the center of the 12-foot diameter spherical
dome. Two video projects display a wide-angle view of a virtual scene on the top interior of the
57
dome. This scene consisted of a checkerboard virtual room with vertical cues (doorway, stick
figure, window, signs) aligned with the longitudinal body axis. After the baseline CSI
measurements with eyes closed, the subjects' eyes were opened and the virtual scene was rotated
in either the subject's pitch, yaw, or roll plane at 35 deg/sec to elicit sensations of tilt and/or
rotation. The pitch and yaw DOME visual stimuli rotated about an earth horizontal axis,
producing the sense of tilt and rotation. The roll visual stimulus, on the other hand, rotated about
an earth vertical axis typically resulting in the sense of rotation without tilt.
In summary, the visual conditions were therefore chosen to provide the following
combinations of perceived tilt and/or rotation:
1.
Mirror bed: perceived tilt without rotation
2. DOME Pitch and Yaw: perceived tilt and rotation
3.
DOME Roll: perceived rotation without tilt
5.3 CSI Results and Discussion
During each virtual illusion, the subjects were asked to quantify their perception of body
tilt position in degrees, with 0* equal to no tilt and 900 equal to standing upright, after 3 minutes
and 13 minutes of exposure with the CSI measurements obtained in between. These results are
summarized quantitatively in Table 5-1 and graphically in Figure 5-2. Notice that the Mirror Bed
stimulus elicited the greatest perception of tilt.
Table 5-1. Perceived orientation. Mean±standard error.
Stimulus
Mirror Bed (Body)
Mirror Bed (Head)
DOME Pitch
DOME Yaw
DOME Roll
Perceived Tilt Orientation
Perceived Self-Motion
3 min
13 min
3 min
13 min
42.8±5.70
51.1±6.40
23.8±13.90
15.7±15.80
0.0±19.60
45.0 +5.70
54.7±6.70
13.1±13.70
14.3±15.60
1.4±19.60
74.4±11.0
65.7±14.8
66.4±13.7
55.6±14.9
55.7±16.3
47.9± 14.6
58
Mirror
Pitch
Yaw
Roll
8060 " 40 20-
P
"a
0-
S-20 -40-60-80 -
Figure 5-2. The distribution of perceived tilt orientation for each virtual
stimulus after 3 min exposure. The box plots show the 10th, 25th, 50th
(median, heavy line), 75th and 90th percentiles. Reprinted from Ramsdell
1999.
Table 5-2 quantitatively summarizes the changes in CSI parameters while Figure 5-3
provides a graphical summary. Changes in physical posture from supine to standing result in
autonomic shifts from parasympathetic toward sympathetic activity as well as in mechanical
effects such as changes in left-ventricular pre-load. Accordingly, notice that the peak amplitudes
of all coupling mechanisms, both autonomic and mechanical, are altered by changing posture
from supine to standing. In particular, both the ILV-+HR and Heart Rate Baroreflex couplings
are diminished in the standing posture relative to supine. This is consistent with findings in
humans that the parasympathetic nervous system is normally the primary mediator of heart rate
variability (Akselrod 1981, Saul 1991 1989).
With regard to the visually-induced virtual tilts, one would expect that the peak
amplitudes of the autonomically mediated impulse responses would likewise be blunted,
proportional to the degree to which the subject believed they were actually standing. Indeed, this
is the case for the DOME simulator, in which subjects uniformly reported DOME pitch to be
59
more convincing than DOME yaw or roll in inducing sensations of tilt. Concomitant, larger
diminutions occurred in the peak amplitudes of the autonomically mediated impulse responses for
DOME Pitch over Roll or Yaw. Interestingly, however, in the case of the Mirror-Bed stimulus,
an increase in the peak amplitudes of both ILV->HR and Heart-Rate Baroreflex occurred for
visually-induced virtual tilt relative to supine.
Table 5-2. Comparison of CSI results: supine vs. standing vs. virtual tilt
(meanestderr). * indicates parameters with P-values < 0.05 with respect to
supine. N=16 subjects.
Impulse Response
Condition In(Peak Amplitude)
ILV->HR
Supine
2.17±0.13
-0.74±6.12
3.37±0.13
1.19±0.12
Standing
1.59±0.18
-10.97±4.19
3.40±0.08
1.58±0.09
Mirror
Pitch
2.43±0.09*
1.69±0.18
2.57±6.79
1.93±5.12
3.40±0.09
3.13±0.09
1.32±0.16
0.94±0.12
Roll
Yaw
2.24t0.22
2.45±0.18
8.65±7.48
2.09±2.65
3.16±0.03
3.02±0.13
0.79±0.23
0.93t0.06
Supine
-0.42±0.06
-0.93±0.31
0.56±0.09
Standing
Mirror
Pitch
-1.03±0.11*
-0.03±0.10*
-0.58±0.01*
-1.51±0.69
-1.16±0.46
-0.56±0.23
0.34±0.08
0.85±0.19
0.27±0.06
Roll
Yaw
Supine
Standing
-0.61±0.21
#DIV/0!
1.44±0.10
2.22±0.05*
-0.53±0.23
-0.62±0.35
-4.62±5.03
8.92±3.40*
0.31±0.21
0.14±0.10
3.42±0.11
3.86±0.07
1.44±0.07
1.89±0.06*
1.28±0.09
1.22±0.09
1.41±0.03
Mirror
Pitch
Roll
Yaw
1.36±0.09
1.33±0.04
1.28±0.01
1.08±0.04*
-10.89±2.93*
-13.39t6.31*
-1.98±5.27
-30.95±16.51
3.51±0.09
3.42±0.05
3.23±0.02
3.34±0.26
2.06±0.04
2.13±0.16
4.17±0.04
3.92±0.03*
4.13±0.04
4.17±0.04
21.76±0.90
17.14±1.00*
19.86±0.96*
21.51±1.43
3.10±0.02
2.82±0.03*
3.05±0.04
3.08±0.04
-0.66±0.05
-0.64±0.04
-0.76±0.07
-0.70±0.06
4.28±0.05
4.27±0.03
20.20±1.31
21.75±1.44*
2.94±0.04
3.06±0.01
-0.83±0.03
-0.76±0.01
HR baroreflex
ILV->ABP
Circulatory Mechanics Supine
Standing
Mirror
Pitch
Roll
Yaw
Area
60
In(Absolute Area) In(Characteristic Time)
1.14±0.13
2.22±0.06
2.05±0.08
2.15±0.01
2.19±0.21
NHR
600-
sm
2000-
0.0
ILV-+-HR
0.1
0.2
0.3 0.4
(Hz)
0.
BAROREFLEX
Frequency
0.4-
10o0.4100.820
4
6
Time
(see>)
8
Autonomic Activity
(Heart Rate Tachogram)
0
2
1
6
Time (see)
Ak
SA NODE
ILV
Atrio-Ventricular Activation
(Impulse Heart Rate)
2-
CIRCULATORY
MECHANICS
Arterial
Blood Pressure
804020-
E
E0t
-200
ILV-+ABP
3mes
c>4
1
5
12
6-12
0
5
10
15
NABP
'Timc (scc)
~
00I
E~l
\
200
0.0
0.1
0.2
0.3
Frequency (Hz)
0.4 0..
Figure 5-3. Group averaged CSI results for subjects in supine (thick solid
line), standing (thin solid lines), mirror virtual-tilt (long dash lines), and
pitch virtual-tilt (short dash lines).
61
8
These preliminary results indicate that visually induced virtual tilt does elicit
changes in short-term cardiovascular regulation. Furthermore, in the case of the DOME
simulator, the degree of change in cardiovascular reflexes correlates positively with
individual measures of tilt perception. Specifically, both the ILV-+HR and Heart Rate
Baroreflex are diminished by visually-induced tilt. In contrast, visually-induced Mirror
Bed tilt resulted in an increased gain for both autonomic transfer functions. This
difference serves to highlight the complexity of the visual-autonomic integration,
pointing the way for future research.
62
6 Summary and Future Work
Cardiovascular System Identification (CSI) was applied to determine the effects of
simulated microgravity environments on cardiovascular deconditioning in general and orthostatic
intolerance in particular. Preliminary results indicate that simulated micro-gravity environments
significantly influence the autonomic mediation of short-term cardiovascular reflexes, including
heart-rate baroreflex. Furthermore, CSI was applied to determine the effects and influence of
visual pathway stimulation on short-term autonomic regulation. The results indicate that visually
induced virtual tilt does elicit changes in short-term cardiovascular regulation, primarily
correlating positively with individual measures of tilt perception. Finally, to provide a reference
point with existing cardiovascular analysis, three quantitative models were created to estimate the
Smyth heart-rate baroreflex sensitivity coefficient from CSI analysis. Using these models, we
were able to non-invasively estimate heart-rate baroreflex sensitivity without the use of invasive
pharmaceuticals.
In addition to the mechanisms studied in this thesis, it has also been recognized that
changes in left ventricular contractility may also lead to orthostatic intolerance. Unfortunately,
the empirical data to date has been ambiguous at best. For example, Frey demonstrated loss of
myocardial mass after a 10-day mission by members of the D2 German Spacelab mission using
magnetic resonance imaging (Frey 1996). However, a year later, Hoffler and Johnson reported
that cardiac contractility, as measured in terms of the velocity of circumferential fiber shortening,
did not change after spaceflight (Hoffler and Johnson 1977). In part, these discrepancies may be
caused by both the difficulty in measuring ventricular contractility as well as ambiguity of which
variable to measure. MIT's Cardiovascular Laboratory, therefore, has strived to extend the CSI
methodology to determine the end-systolic compliance from non-invasively measured stroke
volume and arterial blood pressure data.
63
In addition to left ventricular contractility, alterations in the regulation of total peripheral
resistance have also been implicated with orthostatic intolerance. To this end, therefore, further
extensions to the CSI model are currently underway to create system identification algorithms to
estimate total peripheral resistance from stroke volume and arterial blood pressure data.
Cardiovascular System Identification has been demonstrated to provide a useful closedloop model of the short-term cardiovascular regulatory system, with researchers both within and
without MIT's Cardiovascular Laboratory successfully modeling the effects of various stresses on
cardiovascular regulation via CSI. Yet, both this CSI model and its identification procedures are
continually expanding to model greater physiologic phenomena using noninvasive measurements
with the promise of elucidating ever more physiologic processes.
64
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