Download BIOMEDICAL SIGNAL PROCESSING

Multimodal Signal Recording
BIOMEDICAL
SIGNAL
PROCESSING
Leif Sörnmo, 2015
ECG
Blood
pressure
EEG
Nasal
respiration
Abdominal
respiration
Eye
movements
EMG
electrical / pressure signal
Noisy ECG data which is likely to cause false alarms.
Contents
Electrical activity of the heart, arrhythmias
Lead configurations for recording the ECG
Signal processing, filtering, noise reduction
Clean blood pressure data which can be accurately analyzed.
Ensemble averaging in ECG analysis
Heart rate turbulence
Multimodal analysis can help to improve detection in the above situation
T wave alternans
Atrial activity extraction
Heart rate variability
The Heart...
THE
ELECTRICAL
ACTIVITY OF
THE HEART
is a muscle which is a pump with a
capacity of ~7 liter/min.
has 4 chambers: 2 atria and 2 ventricles.
contracts thanks to electrical coordination
of the muscle cells.
has a conducting system for fast
activation.
is paced by the sinoatrial node, i.e., Conduction System of the Heart
Cardiac Excitation
ventricular excitation
atrial excitation
completes
begins
Electrical Vectors of the Heart
The vector
associated with
each group of cells
in the myocardium
is summed into a
dominant vector
describing the
main direction of
the electrical
impulse.
begins
completes
The Cardiac Cycle & Wave Shape
a
b
c
d
e
f
g
h
lead V5 "views" outer left ventricle
The Cardiac Cycle & Wave Shape
The Cardiac Cycle & Wave Shape
a
b
c
a
b
c
d
e
f
d
e
f
g
h
lead V5 "views" outer left ventricle
g
h
lead V5 "views" outer left ventricle
The Cardiac Cycle & Wave Shape
The Cardiac Cycle & Wave Shape
a
b
c
a
b
c
d
e
f
d
e
f
g
g
h
h
lead V5 "views" outer left ventricle
lead V5 "views" outer left ventricle
The Cardiac Cycle & Wave Shape
The Cardiac Cycle & Wave Shape
a
b
c
a
b
c
d
e
f
d
e
f
g
g
h
h
lead V5 "views" outer left ventricle
lead V5 "views" outer left ventricle
The Cardiac Cycle & Wave Shape
a
b
Extremity Leads – I, II, III
c
I
d
g
f
e
h
lead V5 "views" outer left ventricle
Right
+
II
III
-
-
Left
+
+
Augmented Leads
I, II, III + Augmented Leads
These leads can be computed from I and II
Precordial Leads – V1 to V6
V1
The Standard 12-lead ECG
V2
V3
V4 V5 V6
The Standard 12-lead ECG
The Vectorcardiogram (VCG)
ECG Waves: P-QRS-T
R-wave
Normal Sinus Rhythms
RR-interval
Normal sinus rhythm
T-wave
P-wave
ST-segment
Respiratory sinus rhythm
Q-wave
S-wave
Pduration
PQ- interval
QRSduration
QT- interval
ECG normality is related to PQRST amplitudes and durations
Heart Rate Variability
Arrhythmias: Ectopic Beats
Supraventricular ectopic beat
gradually slower regular breathing
oppos
it
polari e
ty
Ventricular ectopic beats
Arrhythmias: Bi- & Trigeminy
Arrhythmias: Atrial Flutter/
Fibrillation
Bigeminy
Atrial flutter (“organized”)
Trigeminy
Atrial fibrillation (“unorganized”)
Arrhythmias: Ventricular Flutter/
Fibrillation
Ventricular flutter
Clinical ECG Applications
Resting ECG
Intensive care monitoring
Ambulatory monitoring
Ventricular fibrillation
Exercise stress testing
High-resolution ECG
Defibrillation
ECG Signal Processing
ECG Filtering Techniques...
Noise and artifact cancellation (eg by filtering)
QRS detection
Baseline wander is narrowband activity which is
confined to frequencies below 1 Hz.
Noise reduction by averaging
Data compression
Classification of QRS complex morphology
Analysis of heart rate variability
50/60 Hz interference is common in environments
with electrical devices. Shielded recording
equipment is important.
EMG noise overlaps with the spectral content of
the ECG, notably the QRS complex.
Detection of micropotentials
And much more!
ECG Baseline Wander
4000
2000
0
-2000
-4000
-6000
0
50
100
150
time (s)
2000
0
-2000
-4000
time (s)
-6000
0
2
4
6
8
10
12
14
16
18
20
Baseline Filtering: Phase Aspects
Baseline Filtering: Phase Aspects
Note
t
serio he
u
disto s
rsion
the T
o
wave f
Baseline Filtering: Phase Aspects
Undis
signa torted
l
this t with
y
filterin pe of
g
Visa med ST-sänkningar Figur 7.3 i boken...
Baseline Wander:
A Filter Design Example
Linear time-invariant filters with finite impulse
response (FIR), see page 460
Filter length considerations
Infinite impulse response (IIR) filters combined
with forward/backward filtering
50/60 Hz LTI Notch Filter
Powerline Noise
Electromagnetic fields caused by a electrical outlet
is a common noise source in the ECG.
50 or 60-Hz sinusoidal interference, often
accompanied by a number of harmonics.
ECG analysis becomes more difficult since spurious
waveforms may be introduced making delineation
unreliable.
50/60 Hz Filtering
Original signal
Notch filtering
Nonlinear filtering
QRS Detection
Simple Filters: Frequency Response
Preprocessing of the ECG
Linear
filter
Nonlinear transformation
How to decide the
frequency response
of the filter?
Which type:
Squarer,
rectifier,...
Decision
rule
(K,L)
Choice of thresholds:
Only amplitude
threshold?
Fixed or adaptive?
H(z) = (1
z
K
)(1 + z 1)L
Envelope Examples
Envelope-based Detection
ECG
Hilberttransformed
ECG
Envelope
QRS Detection: Decision Rule
detection threshold
Refractory period
Comparison with Annotations
QRS Detector Performance
Annotated Signal for Evaluation
the labels “N” and “V” indicate
whether the beat is of normal or
ventricular origin.
Receiver
operating
characteristic
(ROC)
3 different
detectors
High-Resolution ECG Requires
Ensemble Averaging
High-Resolution ECG and
Cardiac Late Potentials
noisy simulated signals
Ensemble averaging made the discovery of late potentials possible. Their
presence is a risk factor in patients with heart attack.
Model for Ensemble Averaging
Noise Assumptions
I.
fixed shape
II.
III.
Ensemble Averaging
Alignment and Ensemble Averaging
The ensemble average is defined by
Signal model:
xi(n) = s(n
The more familiar (scalar)
expression for ensemble
averaging is given by
θi) + vi(n)
lowpass filtered signal
Lowpass Filtering of the Signal
The expected value of the ensemble average, in
the presence of latency variations, is given by:
Alignment and
Lowpass Filtering Effect
Gaussian PDF
Uniform PDF
or, equivalently, in the frequency domain:
The Exercise Stress Test
ergometer
Exercise usually starts
at a low workload.
Exponential averaging
The ensemble average can be
computed recursively because:
The load is thereafter
increased progressively.
Exercise is terminated
when the patient
experiences fatigue or
chest pain.
To be fighted: EMG noise
and baseline wander
assuming
Exponential averaging results from
replacing the weight 1/M with alpha:
Exponential averaging
Stress Testing and Ischemia –
ECG Reaction
ST amplitude
Normal subject
Patient with ischemia
Stress Testing and Ischemia –
ECG Reaction
Heart Rate Turbulence (HRT)
The short-term fluctuation in heart rate following a VEB is referred to as HRT.
2000
ST amplitude in lead V5
1500
Rest
Work
Recovery
1000
500
acceleration
deceleration
0
local drop in
blood pressure
-500
Time (min)
Ventricular ectopic beat (VEB)
-1000
0
0.5
1
1.5
2
2.5
3
4
x 10
Heart Rate Turbulence
•
In healthy subjects there is an acceleration in
heart rate after a ventricular ectopic beat, followed
by a deceleration and then normal heart rate.
•
The absence of acceleration and/or deceleration
after a ventricular ectopic beat is a powerful risk
indicator in infarct patients.
Individual VEBs and Averaging
RR interval
beat number
Atrial Fibrillation
Heart Rate Turbulence
compensatory pause after VEB
Flera ”pacemakers”.
Förmak och kammare ej synkade.
TO and TS are common clinical parameters.
Atrial Fibrillation
Atrial Fibrillation Characterization
ventricular activity
ventricular activity
measured
inside
the heart
signal
separation
atrial activity
atrial activity
noise
noise
Atrial Fibrillation
Average Beat Subtraction
ventricular activity
signal
separation
atrial activity
noise
How to design this block?
measured on
the body
surface
24-hour
RR interval
trend
Heart Rate and Respiration
RR interval
length (ms)
566
800
Heart Rate Variability (HRV)
indirect measure on autonomic nerve function,
reflects interaction with:
cardiac activity
ECG
respiration
blood pressure
body temperature
Lung
volume
The Interval Tachogram: A Simple Heart Rhythm Representation
Heart Rhythm Representations
The interval tachogram
(previous slide)
The inverse interval
tachogram
The interval function
Advantage: simple to compute
Disadvantage: beat series, spectrum is not in Hz
The inverse interval
function
Heart Rhythm Representations
The Inverse Interval Function and
Regular Sampling
ECG
Inverse
interval
function
Interp
olatio
to the n applies
funct inter val
ion as
well
Interval tachogram
Inverse interval tachogram
Interpolated
inverse
interval
function
Interval function
Inverse interval function
Interpolation by holding the current value until the next occurs
Lowpass Filtered Event Series
Why Spectral Analysis of HRV?
temperature
respiration
blood pressure
Comparator
Modulation
function
Integrator
output
Event series
inverse interval
function
IPFM model
interval
tachogram
Integrator
0.16
0.16
0.16
0.16
event series
Power Spectrum with One
Modulation Frequency (0.16 Hz)
Integral Pulse Frequency Modulation (IPFM) Model
Ectopic Beat Correction
inverse interval
function
event series
interval
tachogram
Power Spectrum with Two
Modulation Frequencies (0.12, 0.16)
Ectopic Beat Correction, cont’
Any Remarkable Characteristic?
Conclusion: It is essential to remove ectopic beats
before performing HRV analysis.
If many ectopic beats occur, HRV analysis should not
be performed at all. An ECG recording is usually
discarded if more than 5% of all beats are ectopic.
Detection of T Wave Alternans
Significance
increased risk of
sudden cardiac death
increased risk of
developing a
potentially lethal
cardiac arrhythmia
Task: Detect the
presence of alternans
T wave Alternans Analysis
T wave Alternans:
Local and Global Analysis
Thank You!