Computational Intelligence - February 2014 - 54

Table 1 Comparison of related works with the proposed method.

MeThod

Fiducial
deTecTion

no. oF
TesTed
subjecTs

RecogniTion
RaTe*

daTa souRce

Biel et al. [22]

PCa

Yes

20

$ 95%

Mit-BiH

standard leads
(i,ii,iii)

sHen et al. [23]

teMPl. MatCHing
+ dBnn

Yes

20

$ 95%

Mit-BiH

standard lead i

israel et al. [24]

lda

Yes

29

$ 90%

ColleCted froM laB.

standard 12-leads

agrafioti et al. [26]

lda + PCa

no

56

$ 95%

Mit-BiH/PtB

standard lead ii

Wang et al. [27]

aC/dCt + Knn

no

13

$ 95%

Mit-BiH/PtB

standard 12-leads

CHan et al. [28]

Wavelet distanCe

no

50

$ 90%

ColleCted froM laB.

lead i (tWo
ContaCt Points)

KHalil et al. [29]

HigH-order legendre
PolYnoMials

no

10

$ 90%

ColleCted froM laB.

lead i (tWo
ContaCt Points)

fateMian et al. [30]

Wavelet + lda

no

14

$ 95%

Mit-BiH/PtB

standard 12-leads

CHiu et al. [31]

Wavelet distanCe

no

35

$ 95%

Mit-BiH

standard lead i

loong et al. [32]

lPC + WPd

no

15

$ 90%

ColleCted froM laB.

standard lead i

CoutinHo et al. [33]

Cross Parsing + Mdl

no

19

$ 90%

ColleCted froM laB.

standard lead i

silva et al. [25]

fse

Yes

26

$ 90%

ColleCted froM laB.

standard lead i

tHis researCH

CHaos tHeorY + BPnn

no

19

$ 90%

ColleCted froM laB.

lead i (tWo
ContaCt Points)

elecTRode
oRienTaTion

[*] value ClaiMed in tHe PaPer

In 2001, Biel et al. [22] proposed the
QRS detection algorithm and applied
fractal and cross-correlation to classify
three types of ventricular arrhythmia,
who conducted an experiment to the
purpose with 12-lead ECG measurement (see [34] for the configuration of
measurement). A feature selection algorithm based on simple analysis of correlation matrix was employed to reduce
the dimensionality of features and a
multivariate analysis-based method was
used for classification. The preliminary
result showed that only lead I was
enough to identify a person. In 2002,
Shen et al. [23] used lead I's ECG measurement to carry out identity verification with template matching and a decision-based neural network (DBNN). A
template matching method was first
used to compute the correlation coefficient (CCORR) for comparison of two
QRS complexes. A DBNN approach
was then applied to complete the verifi-

54

cation from the possible candidates
selected with template matching. In
2005, Israel et al. [24] proposed a methodology for ECG recognition by introducing a set of 15 temporal features,
using the Wilks' Lamda as the feature
selector and the linear discriminate analysis (LDA) for dimensionality reduction
and classification. The peaks were established by finding the local maximum in
a region surrounding each of the P, R, T
complexes, and minimum radius curvature was used to find the onset and end
of P and T waves. In 2008, Agrafioti et
al. [26] performed a template matching
with the correlation coefficient metric
and using autocorrelation (AC) as a basis
framework followed by the LDA. Further, Wang et al. [27] proposed a method
based on AC in conjunction with discrete cosine transform (DCT) to completely relax the detection of fiducial
points. Chan et al. [28] used three measures which were percent residual differ-

IEEE ComputatIonal IntEllIgEnCE magazInE | FEbruary 2014

ence (PRD), CCORR and a novel
wavelet distance measure (WDIST) to
identity of signals. Khalil et al. [29]
applied high-order Legendre Polynomials based on QRS complex for biometric authentication. In 2009, Fatemian et
al. [30] proposed a wavelet based framework for analysis of lead I ECG for
application in human recognition.
Chiuc et al. [31] further combined
wavelet transform with Euclidean distance measure to improve the verification rate. In 2010, Loong et al. [32] used
the linear predictive coding (LPC) to
compute the spectral coefficients of
ECG in frequency domain. Coutinho et
al. [33] used data compression techniques for ECG-based personal identification. All the literature mentioned were
based on the precise time derivatives for
P, QRS complex and T wave delineation. The paper here intends to propose
a more robust, convenient, and portable
way to conduct the biometric personnel



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