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BME MEASUREMENTS AND ANALYSIS LABORATORY
FALL 2004
LABORATORY #13:
NEUROPHYSIOLOGY
I.
Objectives
1.
2.
3.
II.
To examine the relationship between the autonomic and somatic nervous systems.
To assess activity of your autonomic nervous system while you are doing the “SAT”
test.
To test the theory that your performance is affected by cardiovascular “resonance, a
state that can be
induced by slow deep breathing, generally about 6 breaths per
minute.
Introduction
The autonomic nervous system
The autonomic nervous system (ANS) consists of a network of nerves and hormonal
pathways whose job is homeostasis: maintaining a stable internal environment of the body. The
main targets of autonomic nerves and hormones are key internal organs: the pacemaker of the heart,
the smooth muscles of vessels and organs, glands and viscera. Sensory and motor nerves of the
ANS enter and exit the spinal cord at different neurological levels. The ANS has two major nervous
limbs or divisions that operate in parallel to maintain homeostasis: the sympathetic nervous system
(SNS) and parasympathetic nervous system (PNS).
The two ANS limbs reciprocate to maintain homeostasis. For example, an increase in SNS activity
increases heart rate (HR) and contractility, whereas an increase in PNS decreases them both.
Although the sympathetic and parasympathetic systems are largely antagonistic in their action, they
share anatomical similarities, since they both leave the CNS as preganglionic neurons and synapse
with the postganglionic neurons. While the ANS generally works without voluntary control or
consciousness, the brain, such as the hypothalamus and the limbic system, do play important roles
in regulating it.
The Sympathetic Nervous System (SNS)
The sympathetic nervous system is a widely distributed motor system with a series of 22
ganglia located along the length of the vertebral column. Preganglionic neurons in the sympathetic
system utilize acetylcholine as neurotransmitter. Norepinephrine released by the sympathetic
neurons is dissipated by either being taken back into the synaptic nerve endings or action of the
enzyme monoamine oxidase. The overall duration of the process can be hours long, so the effect of
sympathetic system is both widespread and long lasting.
The Parasympathetic Nervous System (PNS)
The PNS is less widely distributed than the sympathetic and the parasympathetic
preganglionic neurons synapse with only a relatively few postganglionic neurons. Therefore,
parasympathetic neurons are relatively more precise and localized in their effects. The
parasympathetic preganglionic neurons are located either in the brainstem as part of the cranial
nerves or sacral spinal cord (S2 – S4).
II. 1 Control of the heart and vascular system
The cardiovascular system consists of the heart, the systemic and pulmonary arterial
systems, microcirculatory vessels, and the venous systems. The cardiovascular system adapts the
body to different physiological states, such as exercise, stress, and injuries. Modulating the
cardiovascular system in accord with need is one of the most important functions of the ANS.
Although the heart pumps periodically, continuous flow to the peripheral vessels is accomplished
by distending the aorta and large arteries during ventricular systole and recoiling of the aorta and
these arteries to perfuse the peripheral organ vasculature during ventricular diastole.
Regulation of heart rate
A normal human heart beats with the sino-atrial or SA node serving as pacemaker and
without conduction defects, which is called a sinus rhythm or a normal rhythm. Most heart rate
changes are mediated by autonomic nervous inputs to the SA node, which consists of the
sympathetic and parasympathetic nervous systems, along with hormonal influences. Efferent fibers
of the SNS and PNS travel to the heart and blood vessels where they modulate activities of these
target organs. The preganglionic parasympathetic nerves to the heart originate in the medulla
oblongata cells that lie in the dorsal motor nucleus of the vagus. Fibers from these nuclei pass
through the neck via the vagus nerves and synapse with postganglionic neurons located directly on
portions of the heart. The right branch of the vagus nerve primarily innervates the pacemaker
region whereas the left one mainly innervates the atrio-ventricular node. Atrial and to a lesser
degree, ventricular muscles are also innervated by vagal nerves.
Sympathetic nerves to the heart originate in the upper five or six thoracic and lower one or
two cervical segments of the spinal cord. Sympathetic nerves are present throughout the atria,
especially the SA node, and ventricles and the conduction system of the heart. Under normal
conditions, sympathetic and parasympathetic systems regulate the heart rate concomitantly. An
increase in heart rate is usually achieved by an increase in sympathetic activity and concomitant
decrease in parasympathetic activity, while a reduction in heart rate is produced in an opposite
manner.
Neurotransmitters released from sympathetic and parasympathetic nerves affect the heart
rate by altering currents across the pacemaker cell membranes. Norepinephrine released by
sympathetic stimulus increases the heart rate. Through the release of acetylcholine, parasympathetic
stimuli diminish heart rate. Because the cardiac tissues are rich in the enzyme acetylcholinesterase,
which breaks down acetylcholine rapidly, the effects of parasympathetic stimulation decay quickly.
Due to the brief latency and rapid decay of response, the parasympathetic system can exert a beatto-beat control of heart rate and predominate over sympathetic effects.
Heart rate is also regulated by higher centers in the cerebral cortex, the thalamus and
hypothalamus. Cortical and diencephalic centers are responsible for the variations in heart rate
during emotional states, and the hypothalamic centers are involved in the alteration due to
environmental temperature. In addition to the nervous control of heart rate, there are hormonal and
respiratory influences. The heart rate variation of cardiac transplant patients provides an indication
of these influences, since they possess no direct nervous control.
The heart generates a sequence of electrical activity during each beat. Since the body tissues
surrounding the heart are conductive to electricity, a fraction of the cardiac electrical activity can be
recorded on the body surface. The electrocardiogram (ECG) consists of several waves, the largest of
which, the R wave, represents systole.
Regulation of Blood Pressure
Arterial pressure is determined by several physical factors, including arterial blood volume,
peripheral resistance and the arterial compliance (Li, 2000). The mean arterial pressure can be
changed by modifying the peripheral resistance, which affects capillary flow. Generalized arteriolar
constriction increases the peripheral resistance, and thus the outflow from the arterial reservoir is
reduced. If the cardiac output remains constant, the imbalance between the input and output of the
arterial system will result in a rise in mean arterial pressure. A reverse alteration, dilation of the
resistance vessels, will drop the mean pressure.
The ANS is pivotal to the maintenance of adequate arterial pressure. Under physiologic conditions,
systemic arterioles receive a continuous barrage of sympathetic vasoconstrictor impulses, which
originates from a group of cells called the vasomotor center in medulla. Consequently, the smooth
muscle in the wall of its arterioles constricts constantly, and blocking the sympathetic supply to the
arteriole permits the vessel relax. Resistance to the vascular flow is then decreased. The vasomotor
center can be divided into vasoconstrictor and vasodilator areas. The vasodilator area does not exert
its effect directly on the vascular system but rather acts by inhibiting the action of vasoconstrictor
area (Little, 1977). The discharge rate of the vasoconstrictor area can be modified by a large number
of afferent impulses, among which the negative feedback from the aortic and carotid baroreceptors
is a critical one. Under resting conditions, the arterial pressure is determined mainly by the
peripheral resistance. As a result, the blood pressure will be controlled within the normal range by
the acute negative feedback reflex depending on the baroreceptors.
Origins of Heart Rate Variability and Blood Pressure Variability
Cardiovascular fluctuations, most commonly referring to heart rate and blood pressure
variability, are integral features of health ; they also provide a rich source of insight information
about cardiovascular control. HRV occurs in several frequency bands, as listed in Table 1. The most
prominent rhythmic heart rate and blood pressure oscillations in humans are related to respiratory
activity. This rhythm is called “respiratory sinus arrhythmia” (RSA) and operates in synchrony with
breathing frequency, generally ranging from 0.15 to 0.4Hz. RSA is generally believed to be
mediated predominately by fluctuation of vagal activity, because the slow and latent effect of the
sympathetic nerve is damped out.
Heart rate and blood pressure also oscillate at lower frequencies than the respiratory frequency.
Oscillations with a frequency at about 0.1Hz (from 0.05 to 0.15Hz) are defined as low frequency
(LF). LF components reflect both sympathetic and vagal activities. The oscillations with frequency
between 0.003 to 0.05Hz are termed as very low frequency (VLF) and may reflect thermoregulatory
cycle or fluctuations related to plasma renin activity. The frequencies of heart rate variability (HRV)
and blood pressure variability (BPV) lower than 0.003Hz is ultra low frequency (ULF). The ULF
component is affected by a wide range of factors including posture, autonomic pathways, and
behavioral variables. (Xiao et al., 1999).
Even though BPV shares the same frequency components with HRV, the changes in BPV can vary
from those in HRV, especially under some pathologic conditions. For example, HRV may be
diminished in hypertensive patients, whereas blood pressure variation increases as the baroreflex
regulation is reduced. Therefore investigation in both HRV and BPV can disclose more
comprehensive view about the cardiovascular regulation.
Table 1: Frequency components of heart rate variability and blood pressure variability.
Components
Frequency (Hz)
Likely Origins
HF
LF
0.15 - 0.40
0.05 - 0.15
VLF
0.003 - 0.05
ULF
<0.003
Parasympathetic outflow
Both sympathetic and parasympathetic outflow
or sympathetic outflow
Possibly thermoregulatory or plasma rennin
activity
Wide range of determinants like posture,
autonomic pathways, behavioral variables
Cardiovascular Resonance
Oscillations of the ANS can be put into ‘resonance’ by certain behaviours. One method is to
breathe deeply at the correct resonant frequency (Leher & Vaschillo, 2003). For most individuals,
this frequency is about 6 breaths per minute. The technique involves abdominal breathing through
pursed lips with a prolonged exhalation.
The main function of the heart is to pump blood through two circuits:
II.3 Methodology
Heart Rate Variability (HRV) Measurements
The subject is fitted for heartbeat monitoring with sensors, such as Lead II ECG electrodes
or finger plethysmograph for pulse. Breathing can also be recorded using a chest band containing
pneumatic sensors. While being recorded, the subject can either be stationary of perform daily
activities, including ambulation and moderate exercise.
Obtaining valid HRV measurements depends upon careful data collection, strictly objective
procedures for data preparation, and proper statistical and mathematical analyses. The methods
used in this project are designed with these considerations, and have been validated in several
publications [1-8]. Procedure sequence is as follows:
1.
Firstly, the Tachogram, consisting of the sequence of accurate R-R intervals, is collected.
This requires accurate detection of R waves, and storage of each interval with sufficient
temporal resolution. R waves can be detected from the ECG using a template matching
algorithm or a simple amplitude thresholding method. Intervals are stored digitally.
2.
Once obtained, the tachogram must be examined and edited if necessary to ensure its
suitability for analysis. Suitable tachograms must be (1) free of artifacts, (2) sufficiently long
in duration, and (3) stationary. Objective criteria will be used to ensure such suitability of
tachogram epochs for HRV analysis. Epochs with excessive artifacts, i.e > 8 per minute,
will be rejected. Intermittent artifacts such as non-sinus rhythm beats, ie. premature or
aberrant beats, and for spurious noise artifacts or missed beats must be removed and
replaced. To prepare epochs containing an acceptable number of artifacts for further
analysis, they are replaced with "corrected" beats. Tachogram editing is a multi-level
procedure that is objective and applies fixed criteria to all subjects:
a.
The first editing level is an automatic algorithm that recognizes and replaces each
aberrant interval with a corrected one. An example of the automatic beat
classification, using sample parameters is shown in the appendix below: The
software program illustrated operates by color coding the abnormal beat intervals.
Correction of the intervals then can be done by an algorithm that uses linear
predictive coding (LPC) to insert a beat at the most statistically appropriate point.
Alternative methods, such as simply inserting a duplicate interval from the preceding
one, are also done, but are less accurate than the LPC method, since the latter
predicts an interval based on the pattern from several preceding ones.
b.
The second editing level, if required, involves manual identification and correction
of those artifacts not eliminated automatically. This may be required when multiple
artifacts occur in rapid succession.
c.
A third editing level is sometimes required, that involves 'cutting and splicing' of the
tachogram. This may be done by cutting out epochs (of a few minutes duration) with
excessive artifacts, and joining the record with the subsequent record. The spliced
interval is determined by LPC. The process selects only stationary epochs.
3.
The edited and stationary tachogram, once free of artifacts and of sufficient duration, now
can be further analyzed using time domain HRV methods. For this study the minimum data
record will be 600 heart beat intervals. Time domain statistics will include all those listed in
the Task force on Heart rate variability (Journal of the American College of Cardiology).
These include MinN, MaxN, MeanNN, SDNN, RMSSD, PNN50, HRVidx and TINN (as
defined by the task force).
4.
Spectral analysis measures periodic variation in the heart rate by reducing the heart rate
signal into its constituent frequency components and quantifying the relative power. The
spectrum is then obtained using the standard periodogram method. This involves applying
a Hanning window to the epoch followed by the Fast Fourier Transform of overlapping
segments of at least 512 points. Frequency domain measures will include total spectral
energy, and energy in selected frequency bands, including ultra low, very low, low, and
high, expressed in (beats/min)2. The frequency band limits will be similar to those
previously published
5.
Spectra of the breathing records will be done using methods similar to the above, and
additionally the cross spectrum between respiratory and IHR signals can be estimated for
each segment. The complex transfer function will then be estimated using the cross-spectral
method and separated into its magnitude and phase components. Distinct patterns for these
two components correlate with distinct states of sympathetic and vagal modulation of heart
rate. Inference with respect to autonomic states, with respect to sympathetic or vagal
modulation will be possible from this analysis.
Speed/Accuracy Tradeoff (SAT) Test – Fitts’ Task
The basic laws governing motor behavior are analogous to the laws of physics, however,
they are less precise and rigorous. One law or principle of human performance states that the more
rapidly we move, the less accurate we become, so to speak ‘haste makes waste’. A simple measure
of this behaviour is the Speed/Accuracy Trade-off (SAT) Test devised by Fitts (See Kelso, 1992 or
Fitts, 1954). Fitts’ paradigm applies to various physiological cases including different muscles,
fitting a peg into holes, or even under microscopic conditions (See Langolf, 1976).
The SAT Test monitors the subject’s ability to point two stationary targets in turn as fast as
possible. The targets are 2 rectangular bars, of varying width (W) and spacing (A). The task is to hit
each bar alternately as many times as possible within given period of time (20 seconds).
Fitt’s found a logarithmic relationship between the speed and accuracy, the speed being a number of
hits within given time period and the accuracy being controlled by target arrangements (variations
of A and W).
MT = a + b log2(2A/W)
where
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MT = average movement time = 20s/# of hits
A = amplitude (distance) of movement between targets
W = width of the target
a = intercept
b = slope
The term log2 (2A/W) is also called ‘the index of difficulty (ID)’, because MT becomes
longer for wider A or narrower W, as seen in the graph below.
The slope of the Fitt’s curve is a good measure of performance: the smaller the slope, the
better the performance.
III.
Purpose
The purpose of this laboratory experiment is to understand the relationship between the
autonomic and somatic nervous systems. To learn why you would need to improve your
measurements by using filters, baseline correction, etc.
IV.
Materials and Methods
IV.1. Apparatus
Hardware
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PC running Windows
BIOPAC Data Acquisition Unit (MP30)
SS4LA Pulse Photoplethysmograph Transducer, BSL: The SS4LA consists of a matched infrared
emitter and photo diode, which transmits changes in blood density, caused by varying blood pressure
in specific body locations.
Software
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BIOPAC PRO Student Lab Software
LabView Software
SAT Labview VI
Breathing Prompter Labview VI
R-R Intervals Labview VI
Log-a-rhythm Software
IV.2. Setup
BIOPAC
1.
2.
3.
4.
5.
6.
Plug an Electrode Lead Set into CH 1 on the Biopac MP30 unit.
Turn the MP30 data acquisition unit on.
Turn the computer on.
Go to MP30 > Setup Channels
Go to Channel1 (CHl) , then click on ‘Presets’, Select PPG (0.5 – 35 Hz)
From the bars menu, go to MP30 >Data Acquisition > Set the acquisition length to 5 minutes.
IV.3. Subject — Transducer Connection
1. Clean the window of the transducer (Pulse Plethysmograph)
2. Position the transducer so that the sensor is on the bottom of your fingertip (the part without the
fingernail). Wrap the Velcro tape around your finger so that the transducer fits snugly, but not so that
circulation is cut off – it’s a fine line between tight and too tight.
IV.3. Protocol
Introduction
This laboratory examines the relationship between the autonomic and somatic nervous
systems. You will be the subject. The activity of your autonomic nervous system will be assessed
while you are doing the ‘SAT’ test. Don’t panic, ‘SAT’ here means “Speed/Accuracy Tradeoff. It is
measured by the “Fitts” pointing task. You will test the theory that your performance is affected by
cardiovascular “resonance , a state that can be induced by slow deep breathing, generally about 6
breaths per minute.
1. First you will measure your baseline heart rate variability (HRV). You will record your
pulse with the finger plethysmograph, as you did earlier. Sit at the computer station while
recording pulse and breathing normally for 5 minutes. Make sure you have a good pulse
record goal is to get sharp peaks for your pulse, with a flat baseline. To save the data, from
Edit menu choose ‘select all’ then from Clipboard “copy wave data”, then paste into
Notepad. Be sure to delete the first line file identifier. Save the text file as <your
name>_pulses_ctl. You should create a directory with your name, to place all your files.
2.
Open the folder on the desktop named “BME_13”. Next start the SAT test, by starting up
the SAT program. (You need not record pulse and breath during this). Set your test time at
15 seconds and select the “Fitts Test Tab” and then push the “Run” arrow. The test involves
hitting the left and right targets as fast as you can. The program will display 2 bars. Before
starting, position the cursor in between the 2 bars and then to begin start clicking on each bar
alternately, until the timer stops you (after 15 seconds.). Then 2 different bars will appear
and you will do as before. You might rest each time when the bars change position. This
sequence will continue for 5 or 6 iterations, and then give you a final score. Print your
performance graph and save the file as <your name>_SAT_ctl.
3.
Then run the “Breathing Prompter” program. This will display a bar that prompts you to
breathe in and out slowly. Select a comfortable time interval between 7 to 10 breaths per
minute. Use abdominal breathing through pursed lips and prolonged exhalation. Do this for
5 minutes while recording pulse, and save the file as <your name>_HRV_R. Exit the
Breathing program.
4. Then Repeat
# 2. above. Save the file as <your name>_SAT_R.
5. Then Repeat # 1. above, with normal (unpaced) breathing. Save the file as <your
name>_HRV_post
6. Then Repeat
# 2. above. Save the file as <your name>_SAT_post
7. Now you should have 6 files saved. To analyze the 3 pulses files, first look at them in the
Biopac program. If the signal drifts and wanders with low frequency waves due to motion
artifact, filter the data with a high pass cutoff of approximately 1 Hz. To do that go to
"Transform" and select "Digital Filters" and select "IIR" and "High Pass" filter. Save the
file again. Start up the RR Interval (Labview) program. This program is not too user
friendly, and requires time and patience. When you select the run arrow, it prompts you for
the file. Select your first file to analyze, i.e. "Pulses_ctl. Once you select the file, the pulse
record will appear in the top window with a highly compressed scale. Look at the amplitude
of the pulses on the ordinate and adjust the threshold to be within approximately 60 to 70%
of the peak heights. Also adjust the width parameter to be about 15. As you make these
adjustments you will see a new signal appear in the lower window. This is the RR record.
Your goal is to adjust the threshold and width parameters to give the most accurate RR
record, that is one with the fewest artifacts. Artifacts appear as large "spikes" in the record.
So once you are satisfied that you have minimized the artifacts, copy the RR record to an
Excel file and save it. Name your files carefully so you do not lose track. To copy the list of
RR intervals, hit the red "save" button and select the name, adding .xls extension. Go to
excel and multiply all the numbers by 5 to derive RR intervals in milliseconds (this is
because sampling rate is 200 per second). Examine the RR list (Tachogram) for obvious
artifacts and delete spurious numbers that may be at the beginning or end of the list.
8. Once you have a reasonably good record of intervals (5 minutes of recording should produce
about 350 intervals), perform statistics on them using Excel. This would include mean and
standard deviation. The S.D. is a reasonable index of HRV.
9.
If you have time, copy the numbers into Notepad (i.e. .txt) and run the "Log-a-Rhythm"
program, to do more advanced HRV analysis. To do this, import the ascii file into log-arhythm, and use the menu to get a report. The program has automated artifact correction in
the Edit menu, that you should use if needed. Print out the report.
V.
Lab Report Guidelines
V.1.
Report Format
Introduction: Motivate lab in your own words (personal assessment of topic importance); Give
justification for methods used in the laboratory experiment.
Methods:
Description of data collection and measurements. Describe experimental protocol and care
taken to perform the laboratory experiment.
Results:
Data (Objective summary of results). Focus on the organization of the data.
1. Assemble all your data on HRV and SAT performance. The HRV index could be the
S.D. of the RR intervals or other index derived from the Log-a-Rhythm program. If
available, include your average breathing rates in the three conditions. Put all data in
a table.
2. Plot on a bar chart your HRV index and SAT slope for the three conditions. Include a
detailed figure caption, and label axes, and bars.
Analysis:
Meaning of the results, what conclusions can or cannot be made and why?
Include results from IV.5: Data Analysis and Interpretation.
Summary & Conclusions: Include only overall trends or findings from Analysis Section. There need be
no more than 3 or 4 main points. Base your discussion on the questions in V.2, below.
References: (quote all sources used, including web sources, no plagiarism)
V.2.
Analysis Guide Questions
1. Did your HRV change between conditions? What was the magnitude of the change?
2. Did SAT vary between conditions?
3. Was your performance affected by your autonomic state, as measured by the HRV? What
other variables may have influenced the results?
4. How would artifacts in the tachogram (i.e. missed intervals or double counts) affect the
results?
5. Why does speed affect accuracy? ? Are there any types of motions in which accuracy
increases with speed?
VI. References
1. Rosen, H. Craelius, W. Curcie, D. Hiatt, M. Hegyi , T. Spectral Analysis of Heart
Variability in the Newborn Infant, Biology of the Neonate 77:4:2000, 224-229; Veerappan S,
Rosen H, Craelius W, Curcie D, Hiatt M, Hegyi T, Spectral analysis of heart rate variability
in premature infants with feeding bradycardia, PEDIATRIC RESEARCH 47: (5) 659-662
MAY 2000
2. Rosen, H. Craelius, W. Curcie, D. Hiatt, M. Hegyi , T.: Spectral Analysis of Heart
3. Craelius W, Restivo M, Assadi M, El-Sherif N: Optimal time averaging of cardiac signals.
IEEE Transactions on Biomedical Engineering Vol. 33, pp. 957-966, 1986.; Craelius W ,
Restivo M, El-Sherif N: Signal Processing Options for detecting Ischemic ventricular
potentials. Journal of Electrocardiology 30, Sept. 345-51, 1987 )
4. Craelius W, Tangella M, Akay M: Heart rate variability as an index of autonomic imbalance
In patients following myocardial infarction. Medical & Biological Engineering &
Computing, 30: 385-388, 1992.; Bekheit S, Tangella M, El-Sakr, Rashid A, Craelius W, ElSherif N: Use of heart rate spectral analysis to measure effects of calcium channel blockers
on autonomic nervous system. American Journal of Cardiology 119:79-85, 1990).
5. Bekheit S, Tangella M, El-Sakr, Rashid A, Craelius W, El-Sherif N: Use of heart rate
spectral analysis to measure effects of calcium channel blockers on autonomic nervous
system. American Journal of Cardiology 119:79-85, 1990.)
6. Curcie, D, Craelius W: Recognition of Individual Heart Rate Patterns with Cepstral Vectors,
Biological Cybernetics, 77/2:103-109, 1997).
7. Lehrer PM, Vaschillo E : Resonance in the baroreflex system assessed by biofeedback .
BIOLOGICAL PSYCHOLOGY 62 (3): 229-229 MAR 2003
8. Fitts, P.M. The information capacity of the human motor system in controlling the amplitude
of movement. Journal of Experimental Psychology, 1954, 47, 381-391.
9. Langolf, G.D., Chaffin, D.B., & Foulke, J.A. An investigation of Fitts’ law using a wide
range of movement amplitudes. Journal of Motor Behavior, 1976, 8, 113-128.
10. US 5,333,615 : Craelius, W,
Newby, N : "Apparatus for Digitally Recording and
Analyzing Electrocardial and Other Signals" .
11. US 6,390,986 Craelius, W, Curcie, D: Classification of heart rate variability patterns in
diabetics using cepstral analysis".