Quantitative Assessment of Diabetics with Various Degrees of
Autonomic Neuropathy
Chuang-Chien Chiu
1
, Shoou-Jeng Yeh
2
and Yi-Chun Kuo
1
1
Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, R.O.C.
2
Section of Neurology and Neurophysiology, Taichung Cheng-Ching General Hospital, Taiwan, R.O.C.
Keywords: Cerebral Autoregulation, Diabetics, Power Spectral Density Analysis, Cross-correlation Analysis.
Abstract: In this study, we investigate the feasibility of using power spectral density (PSD) analysis and cross-
correlation function (CCF) analysis to assess the healthy subjects and diabetics with mild, moderate and
severe autonomic neuropathy. Continuous cerebral blood flow velocity (CBFV) was measured using
transcranial Doppler ultrasound (TCD), and continuous arterial blood pressure (ABP) was measured using
Finapres device under supine, tilt-up and hyperventilation conditions. In PSD analysis, the results revealed
that the autonomic nervous balance to normal subjects declined in trend from supine to hyperventilation in
comparison with that of diabetics. The CCF analysis of mean ABP (MABP) and mean CBFV (MCBFV) for
each group of patients was calculated in three frequency bands, i.e., very low frequency (VLF), low
frequency (LF), and high frequency (HF). The maximum peak value of CCF (Max CCF) and its
corresponding standard deviation and time lag were obtained. Max CCF values at LF of normal subjects
and patients with diabetes without autonomic neuropathy in both supine and tilt-up positions were
significantly larger than that of diabetics with autonomic neuropathy. Max CCF values gradually increased
in hyperventilation at VLF from normal subjects to diabetics without autonomic neuropathy, diabetics with
mild autonomic neuropathy, and diabetics with severe autonomic neuropathy.
1 INTRODUCTION
The cerebral autoregulation (CA) mechanism refers
to the cerebral blood flow (CBF) tendency to retain
relatively constant in the brain despite changes in
mean arterial blood pressure (MABP) in the interval
from 50-170 mmHg (Lassen, 1959). Over the last
decade, considerable advances have been developed
in the safety and accessibility of noninvasive
equipment (Mitsis, 2009). A technique using a
transcranial Doppler (TCD) was introduced to
evaluate the dynamic response of CA in humans.
Rapid drops in arterial blood pressure (ABP) caused
by the release of thigh blood pressure cuffs were
used as an autoregulatory stimulus. The ABP and
CBF velocity (CBFV) were compared during the
autoregulatory process. ABP can also be acquired
noninvasively using a finger cuff device (Finapres
BP monitor). A high-speed servo system in the
Finapres inflates and deflates the cuff rapidly to
maintain the photoplethysmographic output constant
at the unloaded state. Using the autoregulatory curve
made by ABP and CBFV as a model to measure
whether the pressure is normal or impaired in
humans, CA is more a concept rather than a
physically measurable entity. Noninvasive CA
assessment has been developed and studied using
either static or dynamic methods. Most tests require
the introduction of variations in ABP using
traditional physiological or pharmacological
manipulation. It is a challenge to find appropriate
methods to assess CA non-invasively and reliably
using simple and acceptable procedures. Recent
investigations have shown that the autoregulatory
dynamic response can be identified from
spontaneous fluctuations in MABP and CBFV
(Panerai, 2000). Some investigators assessed the
dynamic relationship between spontaneous MABP
and CBFV using transfer function analysis in either
normal subjects or in autonomic failure patients
(Blaber, 1997). Some investigators used spontaneous
blood pressure changes as input signals to test CA
(Chiu, 2001; 2005). Spectral and transfer function
analyses of CBFV and ABP were performed using
fast Fourier transform (FFT) in their experiments.
However, the stationary property and time resolution
are two critical problems for spectral analysis.
302
Chiu C., Yeh S. and Kuo Y..
Quantitative Assessment of Diabetics with Various Degrees of Autonomic Neuropathy.
DOI: 10.5220/0004230003020305
In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS-2013), pages 302-305
ISBN: 978-989-8565-36-5
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
Another study was made to explore spontaneous
beat-to-beat fluctuations in MABP and breath-by-
breath variability in end-tidal CO
2
(EtCO
2
) in
continuous recordings obtained from healthy
subjects at rest to estimate the dynamic influences of
arterial blood pressure and CO
2
on CBFV (Panerai,
2000). The aim of this study is to investigate the
feasibility of using power spectral density (PSD)
analysis and cross-correlation analysis (CCF) to
assess the healthy subjects and diabetics with
different degrees of autonomic neuropathy.
2 METHODS
2.1 Subjects and Measurements
Four groups of subjects were recruited in this study,
and shown in Table 1 (NL: normal, DM: diabetics
with mild autonomic neuropathy, DAN1: diabetics
with moderate autonomic neuropathy, DAN2:
diabetics with severe autonomic neuropathy). The
subjects in the healthy group were included only if
they had no history of vascular disease, heart
problems, hypertension, migraine, epilepsy, cerebral
aneurysm, intra-cerebral bleeding or other pre-
existing neurological conditions. None of the
subjects were receiving any medication during the
time of the study. CBFV was measured in the right
middle cerebral artery using TCD (transcranial
Doppler ultrasound, EME TC2020) in conjunction
with a 5-MHz transducer fixed over the temporal
bones using an elastic headband. Continuous ABP
recordings were obtained through the Finapres
(Ohmeda, 2300) device with the cuff attached to the
middle finger of the right hand. Spontaneous ABP
and CBFV were recorded simultaneously to a PC for
off-line analysis. The acquisition periods were
approximately 5 minutes in supine, 5 minutes in tilt-
up, and 3 minutes in hyperventilation. The personal
computer combined with a general purpose data
acquisition board and LabVIEW environment for
acquiring signals correctly was developed in our
previous study (Chiu, 2001).
Table 1: Subjects recruited in this study.
NL DM DAN1 DAN2
Number of subjects
M=8
F=3
M=11
F=4
M=12
F=9
M=20
F=5
Age (Mean±SD) 56.4±8.1 50.8±15.7 61.8±9.0 61.4±10
Note: M stands for male, and F for female.
The sampling rate needed to acquire the analog data
from TCD and Finapres is adjustable in this system.
In the power spectral analysis of MABP and
MCBFV under supine and hyperventilation, the
power of high frequency (HF) and low frequency
(LF) bands are calculated relatively. Then the value
of LF/HF can be used to observe the sympathetic
changes.
2.2 Analysis Methods
2.2.1 Power Spectral Density
The spectral analysis of blood pressure was used to
explore the specific autonomic nervous system
activity. Spectral analysis of arterial blood pressure
and cerebral blood flow velocity signals were
performed for the very low frequency range (VLF:
0-0.04 Hz), low frequency range (LF: 0.04-0.15 Hz),
and high frequency range (HF: 0.15-0.4 Hz). Power
spectral density was calculated as follows.
1,,2,1,0,)()(
1
0
2
NkenxkX
N
n
kn
N
j
(1)
Where x(n) is a discrete-time signal. Then the power
spectral density can be calculated by:
1
|
|
1
∗
(2)
Where k is the frequency sample index and N is the
number of samples. S
xx
(k) is the power spectral
density function.
2.2.2 Cross-correlation Function
Before calculating the CCF between MABP and
MCBFV time series, MABP and MCBFV were
normalized by using their mean values. Assume that
the normalized MABP and MCBFV time series are
and , respectively. The normalized MABP
and MCBFV time series can be calculated as follows.
σ
(3)
Where MABP is the time series of mean arterial
blood pressure for each heartbeat,
is mean
MABP, and is the standard deviation of
MABP.
σ
(4)
Where MCBFV is the time series of mean arterial
blood pressure for each heartbeat,
is mean
MCBFV, and is the standard deviation of
MABP.
and signals were bandpass-filtered
QuantitativeAssessmentofDiabeticswithVariousDegreesofAutonomicNeuropathy
303
using a third-order digital bandpass Chebyshev filter
in the VLF, LF and HF ranges before applying the
CCF. Assume that the bandpass-filtered and
time series are
and respectively.
The CCF between
and is calculated as
follows:
2
1
)0()0(
)(
)(
ˆˆ
ˆˆ
ˆ
ˆ
i
gg
i
ff
i
gf
i
RR
kR
kCCF
(5)
,,2 ,1 ,0 ki=1 to N-W+1
(6)
Wi
ij
Wi
ij
i
gf
kjgkjf
W
kkjgjf
W
kR
,2- ,1- ,0 ),(
ˆ
)(
ˆ
1
,2 ,1 ,0 ),(
ˆ
)(
ˆ
1
)(
ˆ
ˆ
Wi
ij
i
ff
jf
W
R
2
ˆˆ
)](
ˆ
[
1
)0(
,
Wi
ij
i
gg
jg
W
R
2
ˆˆ
)](
ˆ
[
1
)0(
(7)
3 RESULTS AND DISCUSSION
3.1 Power Spectral Density
The results of power spectral density analysis of
MABP and MCBFV are listed in Table 2.
Table 2: The results power spectral density analysis of
MABP and MCBFV (HV: hyperventilation).
Normal
MCBFV MABP
supine HV supine HV
VLF 346.5±292.7 29.7±11.9 448.2±586.7 202.1±162.9
LF 66.9±22.7 27.3±15.1 80.4±39.7 86.8±8.2
HF 80.7±29.0 70.4±38.5 23.7±11.5 40.4±46.1
Mild DAN
MCBFV MABP
supine HV supine HV
VLF 383.0±654.6 52.4±77.7 264.0±295.7 200.1±239.6
LF 63.8±67.4 22.2±11.0 52.0±54.1 49.0±42.9
HF 91.1±84.7 41.7±17.5 34.6±29.1 36.8±44.5
Moderate DAN
MCBFV MABP
supine HV supine HV
VLF 326.3±312.8 46.8±44.0 262.0±250.2 128.7±102.4
LF 50.8±38.3 34.7±32.0 32.3±35.6 26.1±21.3
HF 102.4±101.6 80.1±58.6 43.5±34.1 38.0±44.6
Severe DAN
MCBFV MABP
supine HV supine HV
VLF 149.7±128.4 40.4±45.1 173.2±190.3 218.0±235.8
LF 36.9±25.0 19.3±9.6 28.7±30.2 35.9±51.0
HF 64.7±32.4 40.2±17.2 48.7±58.1 36.3±34.8
The values of LF/HF between supine and
hyperventilation are listed in Table 3. The
relationship of LF/HF reflects the sympathetic
activity.
Table 3: The results of LF/HF in each group.
MABP NL DM DAN1 DAN2
Supine LF/HF 3.68±1.78 1.66±0.97 0.87±0.70 0.65±0.43
Tilt-up LF/HF 3.71±2.35 2.29±1.87 1.12±0.91 0.55±0.41
HV
LF/HF
2.49±1.59 1.68±0.96 1.08±0.83 1.01±0.77
MCBFV NL DM DAN1 DAN2
Supine LF/HF 0.91±0.43 0.66±0.26 0.59±0.25 0.67±0.57
Tilt-up LF/HF 1.01±0.54 0.63±0.34 0.45±0.2 0.38±0.31
HV LF/HF 0.41±0.19 0.56±0.26 0.41±0.15 0.49±0.17
It can be observed that the value of LF/HF with
MABP in normal group during supine position is
higher than that in hyperventilation, but it
’s lower
than that in tilt-up. However, the values of diabetic
groups in supine position are lower than that in
hyperventilation. This result indicates the autonomic
nervous balance decreases from supine to
hyperventilation in normal group. It might be that
when hyperventilation induces higher blood pressure,
cerebral autoregulation (CA) mechanism begins to
maintain blood pressure being constant and
autonomic nervous balance became less active.
In diabetic groups, the value of LF/HF in
hyperventilation is higher than that in supine. In the
group of severe autonomic neuropathy in
hyperventilation, the value of LF/HF is lower than
that in supine. The difference between supine and
hyperventilation in the group of severe autonomic
neuropathy is more obvious than those in the other
two diabetic groups. It can be speculated that
autonomic neuropathy becomes more serious, the
function of cerebral autoregulation (CA) tends to be
more imbalance.
The values of LF/HF in CBFV during supine are
higher than those in hyperventilation in all groups.
Due to hyperventilation made oxygen increased in
the brain, the cerebral artery diameter was increased,
too. Therefore, the cerebral blood flow velocity
(CBFV) becomes a slower while sympathetic
activity decreasing to make CBFV increased.
3.2 Cross-correlation Function
In CCF analysis, the maximum peak value (Max
CCF) of CCF, its corresponding standard deviation,
and time lag were obtained. Max CCF values at LF
of normal subjects and patients with different
autonomic neuropathy are shown in Table 4.
It is observed that Max CCF values at LF of
normal subjects and patients with diabetes without
BIOSIGNALS2013-InternationalConferenceonBio-inspiredSystemsandSignalProcessing
304
autonomic neuropathy in both supine and tilt-up
positions were significantly larger than that of
diabetics with autonomic neuropathy.
Table 4: Max CCF values at LF in each group.
LF
Max CCF
NL DM DAN1 DAN2
Supine 0.52±0.09 0.48±0.08 0.42±0.09 0.45±0.1
Tilt-up 0.6±0.13 0.59±0.13 0.46±0.08 0.48±0.16
HV 0.45±0.08 0.43±0.1 0.4±0.09 0.41±0.11
The results were especially significant in tilt-up
position. It indicates that the cerebral autoregulation
(CA) of normal subjects and diabetics without
autonomic neuropathy is superior to that of diabetics
with autonomic neuropathy.
Figure 1: Comparison of Max CCF values at VLF in each
group.
Max CCF values at LF of normal subjects and
patients with different autonomic neuropathy are
shown in Table 5.
Table 5: Max CCF values at VLF in each group.
VLF MAX
CCF
NL DM DAN1 DAN2
Supine 0.5±0.15 0.5±0.13 0.46±0.18 0.41±0.19
Tilt-up 0.56±0.17 0.54±0.19 0.55±0.15 0.53±0.18
HV 0.56±0.13 0.49±0.16 0.54±0.15 0.6±0.16
Max CCF values gradually increased in
hyperventilation at VLF from normal subjects to
diabetics without autonomic neuropathy, diabetics
with mild autonomic neuropathy, and diabetics with
severe autonomic neuropathy shown in Figure 1. It
reveals that the diabetes have worse vascular
compliance in comparison with the normal subjects.
4 CONCLUSIONS
In this study, the power spectral density (PSD)
analysis and cross-correlation function (CCF)
analyses were applied to demonstrate
hyperventilation can help us to assess the normal
subjects and diabetics with various degrees
autonomic neuropathy. On the contrary, the opposite
results could be obtained in tilt-up position.
ACKNOWLEDGEMENTS
The authors would like to thank the National
Science Council, Taiwan, R.O.C., for supporting this
research under Contract No. NSC-99-2221-E-035-
054-MY3.
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0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
NL DM DAN1 DAN2
Supine
Tilt‐up
HV
QuantitativeAssessmentofDiabeticswithVariousDegreesofAutonomicNeuropathy
305
