Apparatus for pattern recognition of ECG signals for detecting fibrillation

Physiological electrical signals such as electrocardiograph signals ae converted to digital form, amplified to a standard maximum amplitude and analyzed by a computer. The analysis may calculate the ratios of energies above and below an isoelectric line, the statistical distribution of gradients, the frequency of a maximum negative gradient and the zero content of the signal. The analysis may be used for detecting ventricular fibrillation.

DESCRIPTION OF THE INVENTION 
This invention relates to methods and apparatus for pattern recognition of 
electrical signals of physiological origin. The invention may be used for 
automatic diagnosis of heart conditions, especially for detection of 
conditions which may require defibrillation. 
Ventricular fibrillation often occurs during a heart attack and is commonly 
fatal unless treatment is applied rapidly. Ventricular fibrillation is a 
condition in which the heart has ceased to pump or has spasmodically 
irregular contractions, accompanied by chaotic electrical activity. 
The operation of a patient's heart may be monitored using an 
electrocardiograph, which receives electrical signals from the heart 
through a pair of electrodes, commonly attached to the patient's chest, 
and displays the electric pulses received on a display screen, usually a 
cathode ray tube, using a suitable time-base. The trace obtained can be 
inspected by a physician and indicates the behaviour of the heart. However 
correct interpretation of an electrocardiograph (ECG) trace requires 
considerable training because of the variety of heart conditions giving 
rise to different traces, some of which are superficially similar. An 
incorrect diagnosis from an ECG trace could have very grave consequences. 
It is desirable to process the signals from an ECG automatically to 
distinguish the normal electrical behaviour of the heart (normal sinus 
rhythm) from abnormal behaviour, especially to identify fibrillation which 
will generally require very rapid treatment. Such processing might be 
carried out using a series of electronic circuits which together form a 
pattern recognition system. However such an arrangement has the 
disadvantage that the characteristics of the signal received from the 
patient, as evident from the shape of the ECG trace when displayed on a 
screen, are liable to be distorted by the electronic circuits, including 
RC circuits, used so that a false diagnosis of certain heart conditions 
may be obtained. This difficulty is exacerbated by the fact that no single 
measured criterion can be used to distinguish reliably ventricular 
fibrillation from other heart conditions and so several parameters must be 
analyzed. This makes the circuitry required complicated, bulky and 
expensive and increases the probability of distortion. 
The present invention is intended to provide a method and apparatus for 
analyzing electric signals in which distortion of the signal by the 
apparatus itself is reduced to a minimum. 
It is applicable to automatic analysis of physiological electrical 
activity, especially the electrical behaviour of the heart, particularly 
to distinguish ventricular fibrillation from normal sinus rhythm and from 
other conditions such as ventricular tachycardia. 
According to one aspect of the invention there is provided pattern 
recognition apparatus comprising a pair of electrodes adapted to be 
connected to the body of a patient to receive an electric signal 
fluctuating about an isoelectric line, means for sampling the signal 
received at intervals and converting the magnitudes of the samples from 
analogue to digital form, automatic gain control means for standardising 
the magnitudes of the digitised samples to a predetermined maximum value, 
and a computer arranged to analyze the standardised samples to detect an 
abnormal physiological condition. 
Embodiments of the invention will be described below as applied to an 
electrocardiograph, although it will be understood that the invention in 
its broadest aspect may be applied to the pattern recognition of electric 
signals from other sources.

In one embodiment the apparatus of the present invention, when applied as 
an electrocardiograph comprises a pair of electrodes which may be attached 
to the patient's body in order to detect the electrical activity 
associated with the heart beat. The electrodes may be implanted but it is 
generally more desirable to use external electrodes which are attached to 
the chest. The electrodes are connected by suitable leads to the remainder 
of the apparatus which processes the signals received. 
The signals received through the electrodes are fed to an 
analogue.fwdarw.digital converter in which they are expressed in digital 
form and the digitised signals are then analyzed. Once expressed in 
digital form, the information obtained from the ECG will not be altered by 
subsequent circuitry. The analogue-digital converter samples the signal 
received from the electrodes at suitable intervals, for example 0.004 
seconds and the information thus derived may be stored in a digital 
memory. 
When analyzing an ECG signal it is desirable to study the QRS complex of 
the signal obtained, which is the component characteristic of normal sinus 
rhythm. However the QRS complex is generally accompanied by other signal 
components which may be considerable amplitude, such as P and T 
components. In order to eliminate these components it is possible to 
attenuate all frequencies from the original signal below 3 HZ and above 
about 18 HZ, the frequency range in which the QRS complex is situated. 
This may be achieved by inserting low- and high-pass filters in the 
circuit between the electrodes and the analogue-digital converter. A 
suitable filter arrangement is a Sallen and Key band pass filter. The RC 
elements in such a filter will introduce a small distortion in the 
wave-form received by the converter, but it has been found that this 
distortion is small enough not to interfere seriously with subsequent 
analysis of the signal. 
When the real-time digitised signals have been stored they are first 
subjected to an Automatic Gain Control (AGC) sub-routine to standardise 
their amplitude: this step is required because the amplitude of an ECG 
signal may vary considerably from patient to patient. The AGC sub-routine 
takes the greatest value from a suitable number of successive sample 
values (such as 250) and deduces from the value a scale factor by which 
all the samples are then multiplied. The scale factor is chosen such that 
the highest value, after multiplication, corresponds to a maximum limit 
which is determined by the operator. Reference is made to FIG. 1, in which 
the trace shown is that of an unmultiplied ECG trace and the maximum limit 
set by the operator is shown: FIG. 2 shows the appearance of the trace 
after multiplication of all the samples by the scale factor. Thus: 
##EQU1## 
This procedure is repeated for successive batches of samples until a 
suitable total number of successive samples (such as 1000 samples) have 
been processed. The multiplied samples are then stored in a memory. 
After the AGC stage the multiplied samples may then be subjected to a 
series of tests to detect an abnormal physiological condition. These tests 
may be carried out using a computer installation containing a programme 
comprising a series of sub-routines to carry out the various tests. The 
following description describes a series of tests which may be used to 
detect ventricular fibrillation. 
One such test depends on the presence of a substantial amount of zero 
content (isoelectric segments) in the normal sinus rhythm wave-form, 
whereas the zero content in ventricular fibrillation is very small. This 
is evident from FIG. 3a, which is an ECG trace of normal sinus rhythm, and 
from FIG. 4a which is an ECG trace from ventricular fibrillation. If the 
computer carries out a sub-routine to measure the proportion of the 
samples having a zero value, a proportion above a predetermined amount may 
be considered as "normal" whereas a proportion below this amount is taken 
as indicating possible fibrillation. 
As may be seen from FIG. 3a the base-line of a normal sinus rhythm signal 
is not perfectly isoelectric owing to noise and the presence of P and T 
waves, which may have passed the pass-band filter in an attenuated state. 
This base-line irregularity may be avoided by using a floating zero which 
may be set by the operator at a suitable value, e.g. 20% of the maximum 
limit above the true base-line. FIGS. 3b and 4b, show the effect of this 
operation on the traces of FIGS. 3a and 4a respectively. It can be seen 
that the zero content of the normal sinus rhythm (NSR) trace is increased 
by a large amount and that of ventricular fibrillation (VF) while being 
increased somewhat, is still much less than that of NSR. 
Using this test, a proportion of zero content of at least 680 samples from 
every 1000 (68%) is regarded as normal. 
The validity of this test may be affected by distortion introduced by the 
band-pass filter. Some types of ECG trace may be distorted to produce 
trace elements of shape shown in FIG. 5 and the presence of these elements 
will reduce the zero content of the trace. In order to eliminate this 
effect it is possible to invert the signal and repeat the above-mentioned 
test, still using the floating zero. In most cases inversion of the signal 
gives an increased zero content and the signal is again classed as normal. 
Distortion of the original signal caused by the filter can be removed by 
omitting the filter and introducing a further sub-routine into the 
programme to remove the undesired frequencies. However use of such a 
sub-routine makes the programme much more complex and consumes computer 
time which is valuable in an "on-line" system of this nature. 
The above-described test can be ambiguous on its own because of other 
possible heart conditions, such as ventricular tachycardia, which also 
have a low zero content but are distinct from fibrillation. A portion of 
an ECG trace showing ventricular tachycardia is shown in FIG. 6. 
Ventricular tachycardia has a high beat rate but is distinguished from 
fibrillation in that it is essentially regular, so that the ratio of the 
energies contained in the ECG trace above and below the isoelectric line 
is essentially constant. Thus, if the energies above and below the 
isoelectric line for a suitable number of successive samples are measured, 
and the ratio of these energies calculated, and this calculation repeated 
for successive groups of samples, the energy ratios of the successive 
groups or "windows" may be compared. If these ratios are substantially the 
same, then fibrillation may be eliminated as a possible condition. 
It has been found that the energy ratio prepared as above is appreciably 
affected by the presence of base-line noise, which is random and cannot be 
controlled. The effect of base-line noise can be eliminated by setting 
amplitude limits above and below the base-line and eliminate the signals 
between these limits from the energy totals above and below the 
isoelectric point. These limits are chosen experimentally. Elimination of 
the effect of noise in this way reduces the variability of the energy 
ratios obtained from normal sinus rhythm. 
A suitable duration for each "window" is 2 seconds, corresponding to 500 
successive ECG readings at 0.004 second intervals. It has been found that 
durations much shorter than this (e.g. 1 second) do not allow analysis of 
very low heart beat rates. Periods of 3 seconds or above tend to even out 
the energy ratio even in the event of irregular heart activity so that a 
"normal" result may be obtained when fibrillation is actually occurring. 
Using 2-second "windows" and elimination of noise as mentioned above a 
result from this test is considered "normal" if the energy ratio is within 
20% of the mean ratio for at least 7 out of 10 windows. 
An alternative way of carrying out this test is to measure the energy 
ratios of successive windows as described above and calculate the 
variance. However this procedure is less reliable as a ratio from a single 
window which differs widely from the others has a very big effect on the 
variance. 
A third test for distinguishing normal sinus rhythm from ventricular 
fibrillation comprises analyzing statistically the slopes of the ECG 
signal. It will be seen from FIGS. 3a and 4a that the NSR trace has a high 
proportion of zero gradient and that most of the non-zero gradients are 
relatively steep. On the other hand the VF trace has little zero gradient 
and a more or less random distribution of non-zero gradient. If the traces 
are differentiated and a histogram is plotted showing the statistical 
distribution of the slopes of each trace, the histogram for SNR shows a 
much narrower distribution of slopes than VF. 
The width of these histograms may be expressed algebraically as the 
variance (the square of the standard deviation) of the population of the 
gradients of the traces. The variance of a trace may be calculated using a 
programme sub-routine by differentiating the ECG trace by suitable 
processing of the samples stored in the computer and slotting the 
gradients obtained in a series of "pigeon-holes" (e.g. +20, +10, +5, 0, 
-5, -10, -20). The variance .sigma..sup.2 is then calculated by the 
sub-routine from the following equations: 
##EQU2## 
where 
x=mean value of the gradients obtained 
N=number of gradients obtained, 
xn=value of a gradient, 
fn=frequency of xn, 
n=number of pigeon-holes. 
It is considered that a variance of below 75 is representative of SNR and a 
variance above this figure indicates ventricular fibrillation. 
The above-mentioned tests together give a reliable detection of ventricular 
fibrillation but there are certain types of tachycardia for which they can 
give a false indication of fibrillation as the zero content and variance 
values may be outside the above-mentioned limits. Some types of 
tachycardia which may result in such a false detection are shown as ECG 
traces in FIGS. 7a-d and they can fulfil at least two of the 
above-mentioned criteria to indicate fibrillation. 
However it will be noted that all the traces 7a-d contain at least a weak 
or distorted QRS complex occurring at regular intervals and this complex 
is associated with the steepest negative slope of the whole cycle of 
operation of the heart. If this slope is detected and the interval between 
successive detections (the R--R interval) measured, comparison of the 
intervals will indicate the presence or absence of a regular QRS complex. 
This comparison can be carried out by differentiating a suitable number of 
successive samples (such as 250) and taking the steepest negative slope as 
a reference value. The remainder of the stored samples are then 
differentiated and scanned and the time intervals at which like slopes 
occur are recorded. A "like" slope is one which is with a predetermined 
range on either side of the reference value: a suitable range is 20%. 
This scanning is continued until a suitable number of like slopes (such as 
8) have been detected. The R--R intervals between them are then compared 
and if a predetermined proportion (such as 5 out of 8) are equal within 
predetermined limits absence of fibrillation is recorded. If this 
criterion is not met, "rate irregular" is indicated and if no detections 
at all are made in a given period, such as 3 seconds, "no rate detected" 
is indicated. 
This test may give a false result if any artifact occurs during the 
"learning" period in which the reference value is established. Any 
artifact is likely to produce a negative slope which is greater than that 
of the QRS complex and consequently becomes selected as the reference 
value. This possibility may be eliminated by following the procedure for 
establishing a reference value twice over adjacent 250-sample batches and 
taking the lower of the two values thus established as the reference 
value. 
In the accompanying drawings, FIG. 8 shows schematically a flow diagram of 
a pattern recognition system intended to carry out the above-mentioned 
functions. 
Referring to the diagram, a conventional ECG unit comprising electrodes to 
receive electric signals from a patient feeds the signals directly to a 
filter unit 2. Unit 2 comprises a Sallen and Key band-pass filter, the 
circuit of which is shown in FIG. 9 together with the values of the 
circuit components. The frequency response of this filter is approximately 
as shown in FIG. 10. 
The filtered signal is then passed to an analogue.fwdarw.digital converter 
of conventional type 3 in which the signal is sampled at intervals of 
0.004 seconds and the samples are expressed in digital form. The digitised 
signals are then passed to a computer installation for subsequent 
processing. 
In one suitable arrangement the analogue.fwdarw.digital converter is an 
8-bit converter interfaced with a CA1 naked mini ALPHA 16 mini-computer 
and all processing of the samples from the converter is carried out 
numerically by sub-routines of the computer programme. 
The digitised signals are first multiplied in the automatic gain control 
stage 4 by a scale factor related to the maximum value observed in 250 
successive signals to give standardised values as explained above: the 
maximum limit value may be determined by an operator. The standardised 
samples are stored in a memory and when the memory contains 1000 
successive samples the samples are subjected to a series of tests as 
described below. 
The samples from stage 4 are fed to an energy ratio calculation stage 5 in 
which an energy ratio for batches of 500 samples, representing periods of 
2 seconds, are calculated as described above. The steps in this operation 
are shown in the flow chart 11. After setting up the initial registers the 
batches of samples are fed into them and compared with positive and 
negative values, pre-set by the operator, corresponding to amplitude 
limits above and below the isoelectric line (stage 5a). The samples above 
this positive value are stored and added together for the batch of 500 
successive samples (stage 5b) and the samples below the negative value are 
likewise stored and added together (stage 5c). The total obtained from 
stage 5b is then divided from that from stage 5c (stage 5d) and the ratio 
is itself stored (5e). This process is repeated for successive batches of 
samples, to give a series of energy ratios, until the samples from 12 
successive seconds of ECG signal have been processed (stage 7). A set of 6 
energy ratios, derived from 6 successive batches of 500 samples each, is 
thus obtained. 
The samples from the automatic gain control stage 4 are also passed to a 
zero content and slope variance stage 6, which is shown in greater detail 
in flow diagram 12. After setting up the initial registers required the 
samples from stage 4 are fed into them. The samples are then compared with 
a floating zero set by the operator, for example at a value of 20% above 
the base-line of the maximum limit (stage 6a). Stage 6b determines whether 
each sample is above or below the floating zero: if a sample is above the 
floating zero the sample is stored as such and if it is below it is the 
floating zero value which is stored (stages 6c and 6d). Stage 6e causes 
this procedure to be continued until a batch of 1000 samples have been 
processed and stored in this manner. 
The successive samples of the batch are then differentiated with respect to 
time, using a differentiation factor of 7 (stage 6f) to produce a series 
of gradients from successive groups of stored samples. The gradients 
obtained from groups of samples from stage 6d, which in fact are samples 
from the floating zero, are zero: the ECG samples from stage 6c give 
non-zero gradients. All these gradients are processed at stage 6g in which 
the proportion of zero gradients in the total number of gradients obtained 
is calculated. The proportion of zero gradients is then stored. 
The gradients obtained are also processed at stage 6h in which the 
gradients are allocated or "slotted" into a series of pigeon holes having 
values, 20, 10, 5, 0, -5, -10 and -20. The number of gradients in each 
slot is then totalled (stage 6i) and the statistical variance of the 
frequency distribution thus obtained is calculated (stage 6j). The 
variance value obtained for the batch of 1000 samples is then stored. 
When 12 seconds of ECG signal have been analyzed as above the stored 
magnitudes obtained are compared with predetermined criteria. The 
proportion of zero gradients obtained from stage 6g is compared with a set 
limit which is set at 68% (stage 8) and if it exceeds this value the ECG 
signal is classed as normal using this criterion: if it is less, an 
"abnormal" signal is generated. The variance value from stage 6j is 
compared with the set limit of 75 (stage 9) and if it is less than this 
value the ECG signal is classed as normal using this criterion: if it is 
greater an "abnormal" signal is generated. 
The mean of the energy ratios from stage 5d is calculated (stage 9) and the 
number of ratios which is within 20% of this mean is calculated (stage 
10). The ECG signal is classed as normal by this criterion if at least 4 
out of 6 of the energy ratios are within these limits: if 3 or less are 
outside these limits an "abnormal" signal is generated. 
If any 2 of these 3 criteria indicate a normal ECG signal, i.e. only one or 
no "abnormal" signal is generated (stage 11) an output signal indicating 
absence of fibrillation is emitted (stage 12). However if at least 2 of 
these criteria indicate an abnormal ECG signal a rate detection routine 13 
is initiated to confirm the presence of fibrillation. 
The rate detection routine is shown in flow chart 13. After setting up the 
initial registers required the samples from the automatic gain control 4 
are stored and 250 successive samples are differentiated and the steepest 
negative slope from the gradients obtained is determined (stage 13a ) to 
give a reference value. Limits of .+-.20% of this reference value are then 
set (13b). The remainder of the samples are differentiated (13c) and in 
stage 13d the gradients are scanned for values within the limits 
determined at stage (13b). If no gradient within these limits is detected 
within 3 seconds (i.e. within 750 samples) stage 13d causes a "no rate 
detected" signal to be emitted. If a gradient within the limits a counter 
13e is started to measure the time elapsing before the next slope within 
these limits is detected. If no such slope is detected within the 3 
seconds following the first slope detected a "no rate detected" signal is 
again emitted (stage 13f): if the time elapsed is less than 3 seconds the 
time recorded is stored (13g). The counter is then set to zero (13h) and 
the procedure of stages 13e to 13h is repeated until a total of 8 times 
between gradients has been accummulated. 
The mean of these times is then calculated (13i) and limits of .+-.20% of 
this mean are set (13j). The number of individual times within these 
limits is then deduced (13k) and if at least 5 out of the 8 times are 
within the limits an "ECG normal" signal is emitted by stage 12. If 4 or 
less of the times are outside these limits a "ventricular fibrillation 
detected" signal is emitted. 
The rate detection routine thus indicates fibrillation when either the 
maximum negative gradient is not repeated for 3 seconds or when at least 
half of the intervals between these gradients differ from the mean by more 
than 20%. 
In order to avoid a false result because of artifact the procedure of 
stages 13a and 13b may be repeated on successive batches of 250 samples 
and the lesser of the reference gradients obtained taken as a standard. 
The arrangement described above is capable of analyzing an ECG signal and 
indicating possible fibrillation within 15 seconds and may be used in a 
hospital ward, especially an intensive care unit, to indicate malfunction 
of a patient's heart rapidly. Instead of or in addition to a visual or 
acoustic output the apparatus could be connected to a defibrillator to 
administer a defibrillation shock to the patient when fibrillation is 
indicated. 
The above-described procedure for detecting ventricular fibrillation may be 
operated using a computer of known type which contains a programme to 
carry out the necessary logic operations. The computer may be connected to 
a graphic terminal to display the fluctuating signal from the patient 
visually when a signal indicating fibrillation is emitted by the computer, 
and to a hand copy unit to print out a permanent record of the signal from 
the patient if required. The computer may comprise one or more 
microprocessors, suitably programmed, and microprocessors which may be 
used include those available commercially under the following 
designations. Motorola 6800, Intel 8080, 8085, 8086 and 8048, Zilog Z80 
and Z8000, Mostck/Fairchild 3870, Texas Instruments 9900 series and RCA 
1802. The use of a microprocessor may enable a fully portable unit capable 
of detecting fibrillation and administering a defibrillation shock to be 
provided, for use in emergency situations in the field as well as in 
hospitals.