Irena Jekova

R Abächerli

Vessela Krasteva

CiteSeerX

Detection of Electrode Interchange in Precordial and Orthogonal ECG Leads 
Irena Jekova1, Vessela Krasteva1, R Abächerli2 
1Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia,Bulgaria 
2Biomed Research and Signal Processing, Schiller AG, Baar, Switzerland 
Abstract 
This study presents methods for automated detection of 
interchanged precordial and orthogonal ECG leads that 
may prevent from incorrect diagnosis and treatment. For 
precordial leads V1-V6, correlation coefficients of QRS-T 
patterns and time-alignment of R and S-peaks are 
assessed. For orthogonal leads (X,Y,Z), analysis of QRS 
loops in the frontal plane, a set of correlation coefficients 
and a time-alignment of leads are implemented. The 
methods are elaborated using 15-lead ECG databases - 
77 healthy control recordings from PTB database 
(training), and the total set of 1220 ECGs in CSE 
database with various arrhythmias (test). The specificity 
(Sp) for detection of the correct precordial leads 
configuration (V1 to V6) is 93.5% (training) and 91% 
(test) and the mean sensitivity (Se) for 23 simulated most 
common chest electrode swaps is 95.7% (training) and 
95% (test). Sp for detection of the correct orthogonal 
leads X,Y,Z is 98.7% (training) and 93.3% (test), while 
mean Se for 47 reversals of electrode couples A/I, F/H, 
M/E is 98.5%, equal for both training and test databases. 
1. Introduction
Misplacement of electrodes in multichannel 
electrocardiogram (ECG) is reported in 0.4-4% of all 
clinical recordings – a severe cause of erroneous 
diagnosis due to simulated false or concealed true ECG 
abnormalities [1]. The mobile e-health, which is advert as 
the biggest breakthrough in health systems improvement 
[2] raises the need for automated detection of electrodes 
interchange, considering the potential use of portable 
ECG devices by non-specialists. 
Batchvarov et al. [3] review the most common cases 
for interchange of peripheral and chest leads and their 
effect on P-QRS-T patterns alteration, together with basic 
principles for detection of different leads reversals. Most 
of the published studies elaborate methods for limb leads 
analysis – recognition of left arm (LA) and left leg (LL) 
reversal by assessment of P wave amplitude [4] and 
analysis of QRS and P wave axes [5]; right arm (RA) – 
right leg (RL) swap alarm by search for flat line ECG in 
lead II [6]; detection of different LA/LL/RA reversals by 
direction of inscription of the P loop and/or the frontal P 
axis [7], analysis of the frontal QRS axis [8], comparison 
between a composed lead aVF/I and V6 [9], 
reconstruction of a lead using redundancy of information 
in the 8 independent leads [10]. Xia et al. [11] propose a 
combination of features from [5] and [10] to yield a more 
robust and accurate performance. 
Much less studies are found to detect precordial leads 
reversals. Among above referred methods for limb leads 
interchange, only two analyse precordial leads – Hedén et 
al. [5] address 5 adjacent leads reversals (V1/V2, V2/V3, 
V3/V4, V4/V5, V5/V6), Kors and van Herpen [10] 
evaluate 9 leads reversals (5 adjacent leads and V1/V3, 
V4/V6, V4/V5/V6/V1/V2/V3, V6/V5/V4/V3/V2/V1). 
Recently, Dotsinsky [12] reports preliminary results for 
detection of 5 chest leads swaps (V1/V3/V2, V2/V1/V3, 
V4/V6/V5, V5/V4/V6, V1/V2/V4/V3/V5/V6) based on 2 
criteria – absolute error of the middle lead vs. averaged 
sum of the surrounding leads; QRS amplitude evolution 
(increase from V1 to V3, decrease from V4 to V6).  
Possibly because orthogonal ECG leads are seldom 
recorded in the clinical routine [13], no methods 
regarding the correct placement of the Frank orthogonal 
ECG leads (X,Y,Z) are found in the literature.  
This study aims to present methods that may prevent 
from incorrect diagnosis and treatment by automated 
detection of precodrial and orthogonal leads interchanges. 
2. ECG databases
This study uses ECG signals from two independent 
ECG databases – the publicly-available Physikalisch-
Technische Bundesanstalt (PTB) diagnostic ECG 
database [14] and the Common Standards for 
Electrocardiography (CSE) database [15]. Both databases 
provide 15 simultaneously measured ECG leads (the 
conventional 12 leads together with the 3 Frank leads), 
sampled at 1000 Hz, 0.5 μV/LSB.  
The developed methods for electrode interchange 
detection are trained with 77 ECG recordings from 
healthy controls in PTB and are tested with 1220 ECGs 
from CSE, containing various arrhythmias. 
ISSN 2325-8861 Computing in Cardiology 2013; 40:519-522.519
3. Methods 
The methods for detection of precordial and 
orthogonal leads interchange are developed in Matlab 
(MathWorks Inc.). The preprocessing stage includes ECG 
filtering in the range (0.64-150) Hz, an automated 
detection of QRS boundaries [16] and selection of QRS-T 
pattern (QRS onset to QRS offset + 350 ms) of a 
normal/predominant beat within a 10-second episode. 
 
3.1. Precordial leads interchange 
We develop a method for detection of precordial lead 
swaps by assessment of 2 criteria over V1-V6: 
  Matrix R (6x6)  with correlation coefficients of the 
QRS-T patterns between each pair of leads: 











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





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

1)6,6()5,6()4,6()3,6()2,6()1,6(
)6,5(1)5,5()4,5()3,5()2,5()1,5(
)6,4()5,4(1)4,4()3,4()2,4()1,4(
)6,3()5,3()4,3(1)3,3()2,3()1,3(
)6,2()5,2()4,2()3,2(1)2,2()1,2(
)6,1()5,1()4,1()3,1()2,1(1)1,1(
VVrVVrVVrVVrVVrVVr
VVrVVrVVrVVrVVrVVr
VVrVVrVVrVVrVVrVVr
VVrVVrVVrVVrVVrVVr
VVrVVrVVrVVrVVrVVr
VVrVVrVVrVVrVVrVVr
R
 
r(Vn,Vm) stands for the correlation coefficient between 
leads Vn and Vm, calculated as: 
 

 

end
begini
end
begini
ii
end
begini
ii
VmVn
VmVn
VmVnr
22
),(
, 
where i is the sample number between begin (QRS onset) 
and end (QRS offset+350 ms). 
Analyzing rows and columns of Matrix R, any deviation 
from the trend for gradual increase of the correlation 
coefficients towards the cell where a lead is compared to 
itself is suspected as incorrect lead.  
 Time-alignment of positive R-peaks and negative S-
peaks with monotonically increasing time-shift from V1 
to V6 (see Figure 1).  
0 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.225 0.25 0.275 0.3 0.325 0.35 0.375 0.4
-2200
-2000
-1800
-1600
-1400
-1200
-1000
-800
-600
-400
-200
0
200
400
600
800
1000
1200
1400
Time (s)
A
m
pl
itu
de
 (
uV
)
S(V1)
S(V2)
S(V3)
S(V4)
R(V4)
R(V5)
R(V6)
V1
V2
V3
V4
V5
V6
 
Figure 1. QRS-T pattern presenting the time-alignment of 
the high-amplitude peaks – S for V1-V4; R for V4-V6. 
 
A threshold-based decision rule warns for precordial 
leads interchange when a number of suspicious Matrix R 
correlations and abnormal time-alignments is exceeded.  
3.2. Orthogonal leads interchange 
We develop a method for detection of Frank bipolar 
leads interchange based on 4 criteria over 15-lead ECG:  
 Difference between the angles of the maximal vectors of 
the QRS loops in the frontal plane ([I,avF] vs. [X,Y]) – 
the angle difference is normally <60o (Figure 2).  
 
Figure 2. QRS loops in the frontal plane [I,avF], [X,Y]: 
Normal configuration for correct position of Frank leads. 
 
 Correlation coefficients between measured leads and 
leads calculated from X, Y, Z by Dower transform (DT) 
– r(I,IDT), r(II,IIDT), r(V1-6,V1-6DT). High correlations 
are expected for correct placement of X, Y, Z (Figure 3).  
 
Figure 3. QRS-T pattern in I vs. IDT, II vs. IIDT for correct 
position of Frank leads. 
 
 Correlation coefficient relations: r(I,X)>r(I,Y), r(V2,-
Z)>0 in normal configuration of X,Y,Z (Figure 4).  
Figure 4. Lead I, vs. X,Y and V2 vs. -Z for correct X,Y,Z. 
 
  Time-alignment of (Y,Z): the maximal positive peak in 
Y usually becomes apparent after the minimal negative 
peak in Z in normal configuration of X,Y,Z.  
600 300 0 300 600 900 1200 1500 1800 2100 2400 2700 3000
-600
-300
0
300
600
900
1200
1500
1800
2100
2400
2700
3000
- 0.3       0      0.3       0.6       0.9        1.2      1.5 [mV]
Y 
-0.3 
.15 
0 
0.15 
0.3 
0.45 
0.6 
0.75 
0.9 
1.05 
1.20 
1.35 
[m
V
] 
QRSLoop 
[X;Y] QRSLoop 
 [I; avF] 
I 
  avF 
MaxQRSVector  
[X;Y] 
MaxQRSVector 
[I;avF] 
0 ÷ 60 
X 
0 100 200 300 400
-0.1
0
0.1
0.2
0.3
0.4
0 100 200 300 400
-0.2
0
0.2
0.4
0.6
0.8
Time [ms] Time [ms] 
[mV] [mV] 
Lead I 
Lead IDT  Lead IIDT 
Lead II 
0 100 200 300 400
2
0
2
4
6
8
0 100 200 300 400
Time [ms] 
Lead I 
Lead X 
Lead I 
Lead Y [m
V
] 
0 100 200 300 4000 100 200 300 400 0 100 200 300 400
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
             1 
0.8 
0.6 
0.4 
0.2 
   0 
-0.2
Lead -Z 
Lead V2  
520
4. Results 
The developed methods are tested by simulation of the 
following lead interchanges:  
 Precordial leads: 23 different swaps between V1 to V6, 
including 2 adjacent leads reversals, and various 
interchanges of 3 and more leads. The simulated V1 to 
V6 swaps together with the obtained accuracy are 
presented in Table 1. 
 Orthogonal leads: we are able to simulate 47 erroneous 
combinations of the Frank orthogonal leads, including 
full swap of X, Y, Z and polarity inversion (-X, -Y, -Z), 
the later simulating the reversal of the electrodes in the 
respective electrode couples A/I, F/H, M/E.  
 
Table 1. Precordial leads interchange detection: accuracy 
calculated for the training and test databases. The first 
row (Test No0) shows the specificity for the correct 
combination of chest leads V1,V2,V3,V4,V5,V6. The 
following rows show the sensitivity for 23 different 
precordial leads swaps (highlighted in grey). 
 
Precordial Leads  
V1 V2 V3 V4 V5 V6 
Training 
PTB 
77 files 
Test 
CSE 
1220 files 
Test 
No 
Grey cells show the 
swapped electrodes 
Accuracy 
(%) 
Accuracy 
(%) 
0 V1 V2 V3 V4 V5 V6 93.5 91.8 
1 V2 V1 V3 V4 V5 V6 100 90.7 
2 V1 V3 V2 V4 V5 V6 98.7 90.6 
3 V3 V1 V2 V4 V5 V6 100 96.6 
4 V1 V2 V4 V3 V5 V6 100 94.6 
5 V1 V2 V3 V5 V4 V6 88.3 91.3 
6 V1 V2 V3 V4 V6 V5 77.9 84.6 
7 V1 V2 V3 V6 V4 V5 85.7 93.9 
8 V6 V2 V3 V4 V5 V1 100 98.9 
9 V3 V2 V1 V4 V6 V5 100 99.3 
10 V3 V2 V1 V4 V5 V6 100 93.9 
11 V1 V4 V3 V2 V5 V6 100 96.8 
12 V1 V2 V5 V4 V3 V6 100 97.7 
13 V1 V2 V3 V6 V5 V4 83.1 93.0 
14 V4 V2 V3 V1 V5 V6 100 97.5 
15 V1 V5 V3 V4 V6 V2 100 99.0 
16 V1 V2 V6 V4 V5 V3 97.4 97.6 
17 V5 V2 V3 V4 V1 V6 100 98.8 
18 V1 V6 V3 V4 V5 V2 100 99.1 
19 V3 V4 V1 V2 V5 V6 100 98.9 
20 V1 V4 V5 V2 V3 V6 100 99.3 
21 V1 V2 V5 V6 V3 V4 100 98.0 
22 V4 V5 V6 V1 V2 V3 77.9 90.2 
23 V6 V5 V4 V3 V2 V1 94.8 84.9 
Se-mean (Test No 1 to 23) 95.7 95.0 
 
Table 2. Orthogonal leads interchange detection: 
specificity for correct X,Y,Z (Test No0), sensitivity for 47 
erroneous X,Y,Z combinations (Test No 1 to 47). 
 
Input Frank bipolar Leads  Training
 PTB  
77 files
Test
 CSE 
1220 filesX Y Z 
Test
No
Grey cells show not correct 
Frank leads
Accuracy
(%)
Accuracy
(%)
0 X Y Z 98.7 93.3
1 -X Y Z 100 99.9
2 X -Y Z 94.8 92.5
3 X Y -Z 77.9 83.2
4 -X -Y Z 100 100
5 X -Y -Z 100 100
6 -X Y -Z 100 100
7 -X -Y -Z 100 100
8 X Z Y 96.1 91.1
9 -X Z Y 100 100
10 X -Z Y 100 94.2
11 X Z -Y 100 98.6
12 -X -Z Y 100 100
13 X -Z -Y 81.8 89.7
14 -X Z -Y 100 100
15 -X -Z -Y 100 100
16 Y X Z 79.2 88.3
17 -Y X Z 100 100
18 Y -X Z 100 100
19 Y X -Z 100 99.5
20 -Y -X Z 100 100
21 Y -X -Z 100 100
22 -Y X -Z 100 100
23 -Y -X -Z 100 100
24 Z X Y 100 99.3
25 -Z X Y 100 99.9
26 Z -X Y 100 100
27 Z X -Y 100 99.9
28 -Z -X Y 100 100
29 Z -X -Y 100 100
30 -Z X -Y 100 99.9
31 -Z -X -Y 100 100
32 Y Z X 100 99.4
33 -Y Z X 100 100
34 Y -Z X 100 99.9
35 Y Z -X 100 99.8
36 -Y -Z X 100 99.8
37 Y -Z -X 100 99.5
38 -Y Z -X 100 100
39 -Y -Z -X 100 100
40 Z Y X 100 96.1
41 -Z Y X 100 99.7
42 Z -Y X 100 100
43 Z Y -X 100 99.4
44 -Z -Y X 100 100
45 Z -Y -X 100 100
46 -Z Y -X 100 98.8
47 -Z -Y -X 100 100
Se-mean (Test No 1 to 47) 98.5 98.5
 
521
5. Discussion and conclusions 
In this study we present methods for automated 
detection of precordial and orthogonal leads interchange 
which may prevent both ECG readers and conventional 
ECG interpretation programs from misdiagnosis and 
improper treatment. The methods are trained and tested 
over two independent datasets that provides unbiased 
accuracy reported for the test dataset.  
The performance of our method for precordial leads 
interchange detection is compared to the results reported 
in [5,10,12] – see Table 3. The specificity (Sp) for correct 
placement of V1 to V6 as reported in [5,10] is about 8% 
higher than Sp achieved in this study (99.9% vs. 91.8%). 
Besides, the mean values of sensitivity (Se) for swapped 
configurations of precordial leads as reported in [5,10,12] 
are in the range 71.8% to 93.3%, while our method is 
outperforming with mean value Se-mean=95%. Although 
a decade ago a higher Sp was mandatory [10], the rapid 
progress in distant ECG registration and interpretation 
with potential use of portable ECG devices by persons 
with different amount of training becomes a precondition 
for more frequent errors, and therefore raises 
requirements for higher Se. The comparative study in 
Table 3 suggests that methods based on correlations 
between leads ([10], the presented method) are favorable 
in respect to Se than methods which rely only on 
conventional ECG measurements, such as amplitudes, 
areas and axes [5,12]. The most difficultly detected 
reversals of precordial leads are swaps between two 
adjacent leads V2/V3, V5/V6, as well as V4/V6.  
 
Table 3. Precordial leads interchange detection: 
performance of our method vs. published studies for the 
test databases. The values of Sp, Se-mean, Se-range are 
shown as reported by the authors, replaced by ‘-’ mark 
where missing. 
 
Study Sp 
(%) 
Se-mean 
(%) 
Se-range 
(%) 
Lead reversal 
with min(Se) 
Our 91.8 95 84.6 to 99.3 V5/V6 
[5] 99.9 71.8 44.5 to 83 V2/V3 
[10] 99.9 93.3 78 to 99.3 V4/V6 
[12] - 87 - - 
 
This study presents the first report of a method for 
detection of orthogonal leads interchange with Sp of 
93.3% (correct X, Y, Z configuration), and Se of 98.5% 
(mean value), 83.2 to 100% (min-max range) for all 
simulated 47 configurations of swapped Frank leads. It 
appears that the polarity inversion of Z-lead (Test No3: 
X,Y,-Z) is the most difficultly detected configuration with 
minimal Se of 83.2%. The relatively rare clinical use of 
orthogonal ECG leads predisposes to low experience and 
higher probability for human errors in lead arrangement. 
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Address for correspondence. 
 
Irena Jekova  
Institute of Biophysics and Biomedical Engineering 
Acad. G. Bonchev str., bl.105, 1113, Sofia, Bulgaria 
irena@biomed.bas.bg 
522


Detection of Electrode Interchange in Precordial and Orthogonal ECG Leads

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Detection of Electrode Interchange in Precordial and Orthogonal ECG Leads

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