1

Abstract—ECG Signal is the measure of the Electrical Activity

of the heart. The electrical activities are detected through

electrodes attached to the surface of skin. For diagnosis and

proper interpretation from the ECG plot, the signal has to be free

from several artifacts which degrade the signal thus recorded. In

this paper, two of the phenomena are studied and attempted to

remove, viz. Baseline fluctuation-BLF (due to skin movement)

and Power line frequency interference 50Hz. Firstly the spectral

density is estimated for the power content of BLF. Based on the

study following filters are implemented viz. Multiple IIR notch

filter for removal of 50Hz frequency component (also harmonics

at 100Hz), Digital FIR High pass filter for attenuation of the

BLF. A linear phase response which is one of the primary

requirement of the ECG Signal is observed. The power line noise

in the ECG signal has also been considerably reduced.

Index Terms— Baseline Removal, Finite Impulse Response

Filter, IIR Filters, Spectral Analysis.

I. INTRODUCTION

HE Electrocardiogram (ECG) is process of recording the

electrical activity of the heart. A time plot of the recorded

ECG data sample as shown of the form Fig. 1, is of special

interest to the clinicians and doctors. The ECG signal is

recorded using several electrical devices and the signal is

captured by plotting the potential difference between the leads

of the ECG probe, which is kept in touch with the skin surface

of the patient. In the process of recording the signals, several

other forms of interfering signals are also recorded which

distorts the original signal, thereby showing an improper set of

samples. In order to extract useful information from the noisy

ECG signals, the raw ECG is pre-processed.[1]. Preprocessing

ECG signals helps in removing contaminants from the ECG

signals. Broadly speaking, ECG contaminants can be classified

into the following categories:

--Power line interference

--Electrode pop or contact noise

--Patient–electrode motion artifacts

--Electromyographic (EMG) noise

--Baseline wandering/Fluctuation.ss

Manuscript received December 4, 2012.

The Author is with the Department of Electrical and Computer Engineering,

University of Florida, Gainesville 32601, Florida, USA. (352-870-7208; e-

mail : ankan@ufl.edu)

The most prominent amongst the enlisted media of

contamination are the Baseline Fluctuation (BLF) and the

Power Line Interference (PLI). The BLF or Baseline Wander

as it may be called is inherent in the recorded signal due to the

muscular contraction and expansion of the patient. The second

artifact that is subjected to in this paper is the PLI, because of

the presence of 50Hz AC power line frequency components

and its higher Harmonics in the Electronic Systems. The goal

is attenuation of these prominent artifacts with special

emphasis to prevention of phase distortion.

Fig. 1.

PQRST Complex of an ideal ECG data recording.

Following the a small clinical interpretation of the Complex

shown in Fig. 1

--Atrial contractions shows P wave.

--Ventricular contractions show as QRS complex.

--Electrical activity produced when the ventricles are

recharging for the next contraction T wave. [3]

II. METHODOLOGY

A. Data Analysis

The sample has been recorded and experimented based on

the readings taken in EUROPE. Therefore the Power Line

frequency is 50Hz. The continuous time data has been

amplified through an Instrumentation Amplifier with a gain of

1,000 and digitized with a 12 bit A/D Converter. Sampling

frequency is maintained at 1,000 Hz. The time sample plot of

Baseline fluctuation attenuation and Power line

frequency removal in ECG Signal.

ANKAN ROYBARDHAN

T

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the signal is shown as in Fig. 2a. High frequency component is

present in the signal as depicted in the figure.

ECG standards shows that the maximum frequency

content in the ECG signal for a normal adult is about 150Hz.

(95% of the information is in-between 0.5Hz to 100Hz). So,

the signal is therefore down sampled to a sampling frequency

of 250Hz, the nyquist maximum frequency content being about

125Hz.

Fig. 2. ECG Signal Plot of the original sampled data.

B. Power Spectral Estimates and Analysis

Considering the Signal to be a Random Process, the time

domain sequence can be transformed to frequency domain

using Fourier Transform. The power content at each

frequency can be determined using the Power Spectrum

Density Plot.

(1)

2 (2)

Eq. (2) gives the power density spectrum at a given frequency

. This called the periodogram estimate. In other words, the

signal is considered to be Wise Sense Stationary, thus its

Power density spectrum is given by –

(3)

Which is the Fourier transform of the Auto-correlation

function of the input signal, X(n) in this case (Sampled version

of X(t)).[7] A plot of the spectral density has been shown in

Fig. 3, the estimate helps to determine the Power content at the

specific points of interests of that of BLF and PLI. Sampling

frequency is 250Hz, therefore 50Hz corresponds to 0.4π. Its

harmonics at 100Hz (0.8π) is also present in the signal. The

150Hz part(3rd

harmonic) is attenuated since the signal is down

sampled at 250Hz.

Fig. 3. Power Spectral Density of the down sampled data

The peaks at 0.4π, 0.8π are prominent in the figure. These

correspond to the PLI.

The frequency content for the BLF corresponds to a

maximum of 0.5Hz. But during Bradycardia, the heart

pumping may go down to 40beats/mins leading to 0.675Hz as

the lowest frequency content in the ECG Signal data. So, our

objective for BLF removal is to attenuate frequency contents

lesser than 0.5Hz (0.004π) by designing a High Pass filter. The

same is also evident by a peak shown in the lower part of

PSD.[4]

A passband of 0.5Hz (0.004π) till 105Hz (0.84 π) is

attained, since the maximum information is limited between

0.5Hz through 100Hz. Frequency higer than 0.84 π is thus

attenuated by passing through a Low Pass Filter.

III. FILTER DESIGN ALGORITHM

The objective is to preserve the phase response of the data

recorded. So, the use of FIR filter is of main concern in this

paper. FIR Symmetric filter co-efficients are calculated by

firstly approximating a window, where the signal is passed

through and arbitrarily truncate and shift (to make it causal)

the window length so as to get the best possible frequency

response of the filtered output. It has been observed that filter

co-efficients and thus the filter order pertaining to this

windowing technique results in order of filter to approximately

1500 to get the desired cutoff. [2]

(4)

where ,

(5)

[5]

The Parks-McClellan algorithm is therefore chosen to design

the High Pass and the Low Pass filter. The PM Filter is an

iterative algorithm for finding the optimal Chebyshev finite

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impulse response (FIR) filter. This means, due to the inherent

ripple quality of Chebyshev design, the PM filter also comes

with pass band and stop band ripple. The reason to choose PM

filter is that, with a given filter specifications viz. band

attenuations, least filter co-efficients and best tradeoff between

Mainlobe width and side lobe height, the iterative algorithm

helps calculating the least order of the FIR filter.

To remove PLI frequency content, we use 02 nos. 2nd

order

IIR notch filters with specifications as mentioned in the

subsequent design section of this paper.

A. Design of Digital Filters.

1. Design of Low Pass Filter- The frequency content

above 105Hz (0.84 π) is removed by passing the down

sampled version of the signal through a Low Pass filter of

cutoff frequency at 106.25Hz (0.86 π) with 217 order. The

frequency reponse of the filter is shown in fig. 4.

Fig. 4. Parks-McClellan Low Pass filter with cutoff at 0.86π.

2. Design of High Pass Filter- The pass-band of 0.5Hz to

100Hz is preserved as it is. A high-pass filter with transition

band of 0.25Hz to 0.5Hz (0.002π to 0.004π) is designed with

Parks-McClellan algorithm. The filter order comes up to be

1156. The frequency response is shown in fig. 5

Fig. 5. Parks-McClellan High Pass filter for BLF removal.

3. IIR Notch – The wires carrying the electrical pulses

from the patient’s body till the recording device is prone to the

power line frequency interference. The use of IIR notch filter

is justified based on the unsatisfactory performance shown by

Equiripple FIR multi band stop filter. Firstly, the filter order

goes up to the order of 800 for a sharp cutoff at 50Hz and its

harmonics at 100Hz, and secondly, the ripples in the pass-band

induces humming in the signal information part.

2 notch filters, one at 50Hz and one at 100Hz are applied to

attenuate the PLI at 50Hz and its harmonics as well. The

frequency response of each notch filter is shown in fig. 6a and

fig. 6b

Fig. 6a. IIR Notch filter with cutoff at 0.4π and -3dB bandwidth of 2Hz.

Fig. 6a. IIR Notch filter with cutoff at 0.8π and -3dB bandwidth of 2Hz

Here is a tradeoff been presented between the usage of IIR

notch and FIR notch. With FIR notch of following filter

specifications, we get the filter frequency response as shown in

fig. 7

s1=0.388 π, p1=0.392 π, p2=0.408π, s2=0.412 π,

These frequencies correspond to 48.5Hz, 49Hz, 51Hz,

51.5Hz. The filter order comes up to be 918 using the Formula

given as eq. (4). We observe in the fig. 7. that even though the

ripples being quite low in pass-band, the filtered output using

the FIR filter is not as prominent as by using IIR. In addition

to it, this sharp cutoff at 50 Hz and its harmonics calls for such

a high order of FIR filter. A comparison has been drawn

between the filtered output using an IIR and FIR which has

been depicted in fig. 8a and fig. 8b.

4

.

Fig 8a. IIR 2nd order Notch filter at 0.4π (50Hz) and 0.8π (100Hz)

Fig 8b. FIR 918 order Notch filter at 0.4π (50Hz) and 0.8π (100Hz)

It is clearly observed that frequency content around 50Hz is

attenuated (Notched) to a major extent and such a high order

FIR filter is preferable avoided when such a sharp cutoff

response is of major concern.

An algorithm has been devised for such filtering process

which is shown in fig. 9. Where firstly Signal is down-sampled

to 250Hz, then it is low pass, so as to attenuate the frequency

content above 105Hz. This is quite justified since, from the

data and the abstract presented, the signal is considered to be

band limited and thereby down sampling to such extent will

not necessarily introduce aliasing. Although, essentially the

higher frequency content does not contains information, so it is

attenuated through a low pass here. Next, the signal is passed

through 2 IIR notches to remove the PLI frequencies. Finally,

the BLF is suppressed by implementing an FIR High pass filter

with a cutoff frequency around 0.5Hz.

Experimentations have shown that instead, using IIR

Chebyshev filter of order 7, the time plot of the output is a

close approximation of the required PQRST complex. This

response is obtained at the cost of distorting the phase of the

ECG signal thereby introducing different group delay for

different frequencies. Also, in literature, several other

sophisticated methods has been proposed for removal of PLI

and BLF viz. Wavelet Co-efficient method[8], Simplified

Lattice based adaptive filter [9], Subtraction [10], PLI

detector[11] etc. which primarily stresses upon symmetrical

impulse response filters with much lower order.

Studying the pole zero plot of the IIR notch that is used,

shows, there are 2 complex conjugate poles and zeros. The

zeros in the unit circle is at angles of (50Hz) and

(100Hz). The steep ness of the notch filter is controlled

by the proximity of the poles to the zeroes.

(6)

, Gain considered being unity.

Here, =72o

for =0.4π and =144o for =0.8π. fig. 9a,b

shows the pole zero plot of the notch filters.

Fig 9a. IIR 2nd order Notch filter at 0.4π (50Hz) Pole zero plot.

Fig 9b. IIR 2nd order Notch filter at 0.8π (100Hz) Pole zero plot

The in the second notch filter is different from that used in

notch1. The motive is, if we closely observe fig. 8a, the

frequency content around 50Hz has peaky distribution. Having

a sharp notch at that location will attenuate the 50Hz, but will

show the nearby frequency response as in fig. 8b. So, we have

less sharper -3dB band with for 50Hz attenuation as compared

to that in 100Hz.

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After applying the LPF, Notch and the HPF, a set of

following responses we get from fig. 10, 11, 12,13.

Fig 10. Original Signal (Fs=1000Hz) frequency response. Peaks at 0.1π,0.2π,

0.3π, 0.4π etc.

Fig 11. Down sampled signal (Fs=250Hz) frequency response Peaks at 0.4π,

0.8π.

Fig 12. Signal Passed through 2 Notch filter and LPF filter. Freq. resp. Notch

at 0.4π and 0.8π

Fig 13. Filtered signal passed through HPF for BLF removal.

The power spectral density shows the proper attenuation of the

BLF and PLI as in fig. 14a,14b.

Fig 14a. PSD of the downsampled signal. Noise at 0.5Hz, 50Hz and 100Hz.

Fig 14b. PSD of the filtered signal. BLF and PLI removed.

Clearly, the spectrum density at normalized frequency at

0.4π and 0.8π (PLI) and frequency content less than 0.004π

(0.5Hz BLF) are smoothened. A sharp dip at frequencies

above 0.84π (105Hz) is due to Low pass filter which removed

unnecessary high frequency content, which automatically

removed the most prominent (3rd

harmonic at 150Hz) PLI

harmonic.

For a heart rate of 40 bpm, the RR cycle (𝑇) is 1.5 s and the

first harmonic has a frequency of (1/1.5) 0.67 Hz. The

remaining harmonics have frequencies that are integer

multiples of this fundamental frequency (in this case, the

second harmonic 0 . 6 7 × 2 = 1 . 3 4 Hz, the third harmonic 0 .

6 7 × 3 = 2 . 0 1 Hz, etc.). According to this and assuming that

physiological heart rates are normally above 40 bpm, no

biological components or signals attributable to an ECG will

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exist below 0.67 Hz. So cutoff of 0.5Hz is chosen to be

correct.

IV. RESULTS

Following is a tabulated (Table 1) data sheet of the

specifications been followed for designing the above

mentioned filters – TABLE I

FILTER DESIGN SPECIFICATIONS-ECG SIGNAL PROCESSING

Symbol

Description Data

Fs1 Original Sampling Frequency

1000Hz

Fs Downsampled Frequency

250Hz (Normalized to

LOW PASS FILTER SPECIFICATIONS

Ftype FIR Parks-McClellan 217 Order

Cutoff Frequency

105Hz (Normalized to 0.84 )

Stopband Frequency 110Hz (Normalized to 0.88 )

Passband ripple 0.001

Stopband ripple 0.001 (-60dB)

NOTCH FILTER SPECIFICATIONS (PLI removal)

Ftype IIR Notch 2

Cutoff Frequency 1

50Hz (Normalized to 0.4 )

1 -3dB Cutoff 4Hz (Normalized to 0.0032 )

Cutoff Frequency 2

50Hz (Normalized to 0.4 )

2 -3dB Cutoff 3Hz (Normalized to 0.0024 )

HIGH PASS FILTER SPECIFICATIONS (BLF removal)

Ftype FIR Parks-McClellan 1156 Order

Cutoff Frequency

0.5Hz (Normalized to 0.004 )

Stopband Frequency 0.25Hz (Normalized to 0.002 )

Passband ripple 0.1

Stopband ripple 0.02 (-34dB)

The Passband ripple in High pass filter is sufficiently large

as compared to that for Low pass filter, since having a stricter

attenuation in Passband for HPF, calls for FIR filter order of

2100. The performance is not satisfactory at the cost of 2100

order FIR filter. Stopband attenuation of the HPF is kept

considerably low, since having attenuation of the order of -

40dB or -50db, the order of the filter shoots up again to 1900

and the PQ complex of the time plot is disrupted. So, a trade-

off occurs for this critical BLF removal filter.

Fig. 15 shows the time plot of the downsampled signal. A

zoomed version of the signal is shown in the figure, where the

signal mixed with PLI and BLF is prominent. Fig. 16 shows

the filtered output signal. Note, with such traded off filtered

specifications, the PQ complex is preserved to a major extent.

Also, the ST complex is clear High frequency content is

removed by the LPF and the intermediate PLI is also removed.

All filtration causes attenuation (amplitude response,

decrease of sinusoidal wave peak-to-peak amplitude) and/or

phase shifts (phase response, phase shifting of the waves) that

will affect one or other components according to the cut-off

frequency of the filter used (Figure 2). Attenuations or phase

shifts are produced from the cut-off frequency up to

approximately 10 times this value. In our case, the attenuation

caused by high-pass filtering with 0.5 Hz is minimal and only

affects the first harmonic.

Fig 15. Time Plot of the Original Signal

Fig 16. Time Plot of Filtered ECG Signal.

Fig 17. PQRST of the filtered Signal indicated.

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V. CONCLUSION

A filter with linear phase is desirable in order to avoid phase

distortion that can alter various temporal relationships in the

cardiac cycle. The use of IIR filters obviously reduced the

number of co-efficients of the filter, but introduces several

drawbacks –

--Difficult to realize in real time

--At higher Sampling rates, the application becomes

difficult, since the poles moves close to unit circle,

resulting in instability.

Moreover, Linear Phase Filtering is highly required to

preserve the ST Segment of the ECG Signal. [12]. In practice,

in case of IIR filters, they are using as forward backward

configuration to get a zero phase response and magnitude

response equivalent to that of FIR Filters. [13]

Fig 18. Power Spectral Density of the filtered signal using IIR Filter.

PSD of the IIR filtered signal is compared with FIR filtered

signal (fig. 14b). The lower frequency content is pre-dominant.

This IIR has the same passband and stopband attenuation with

Elliptic Filter of order 6. 50Hz PLI is still present.

With filter order below 1000, the PQ and the ST complex is

quite unclear and this poses a serious implication to the

interpretation

In contrast, if we choose 0.05 Hz as cutoff for high-pass

filters, it produce phase-shift harmonics up to approximately

0.5 Hz, a range where no intrinsic bioelectric signals exist,

and, therefore, the shape of the ST segment remains unaffected

(the first harmonic of our ECG was found at 0.9 Hz). But,

eventually, in the system presented in this paper, no

sophisticated instruments are used to reject other noises as

presented in Introducing section, having a stricter cutoff shoots

up the order of the FIR filter to about 2450, which is much

more complex, simulation takes sufficiently large time and

results are similar to what has been observed in this case

(Results has been analyzed with Personal PC screen

resolution.).[14]

The trade of between the IIR notch and FIR has been

discussed with illustrations as in fig. 8a and 8b, which shows

with an order of 918 FIR, a bandwidth of about 8-10Hz is

being attenuated in the region of 50Hz. IIR notch in that case,

shows fine performance with respect to sharp dip in the 50Hz

and 100Hz region without affecting much of the important

information.

VI. REFERENCES

[1] LabVIEW for ECG Signal Processing-National Instruments. Document

Type: Tutorial; Publish Date: Aug 16, 2012

[2] 1L Harika Bommadevara, 2 B. Surya Prasada Rao, 3 P.Rajesh kumar, 4

P.Rajesh Kumar “Interference Reduction in ECG using Digital FIR Filters”

ISSN : 2230-7109(Online) | ISSN : 2230-9543(Print) , India.

[3] Ambulance technician study ,

http://www.ambulancetechnicianstudy.co.uk/ecgbasics.html#.ULsjj4NlWSo

[4] LEIF SO¨ RNMO, Lund University, Sweden, PABLO LAGUNA,

Zaragoza University, Spain “ELECTROCARDIOGRAM (ECG) SIGNAL

PROCESSING” Wiley Encyclopedia of Biomedical Engineering, Copyright

& 2006 John Wiley & Sons, Inc

[5] Alan V. Oppenheim, Ronal W. Schafer, John R. Buck, “Discrete Time

Signal Processing” 2nd Edition Pearson Publications.

[6] http://en.wikipedia.org/wiki/Parks-McClellan_filter_design_algorithm

[7] Biomedical Signal and Image Processing Second Edition

By Kayvan Najarian, Robert Splinter.

[8] INSTITUTE OF PHYSICS PUBLISHING PHYSIOLOGICAL

MEASUREMENT Physiol. Meas. 26 (2005) R155–R199 doi:10.1088/0967-

3334/26/5/R01.

[9] Dhillon, S.S., Chakrabarti, S, Dept. of Electr. Eng., Indian Inst. of

Technol., Kharagpur,India “Power line interference removal from

electrocardiogram using a simplified lattice based adaptive IIR notch filter”

IEEE-Explore Digital Library.

[10] Mihov, G. , Dept. of Electron. Eng., Tech. Univ. of Sofia, Sofia,

Bulgaria “Subtraction procedure for removing powerline interference from

ECG: Dynamic threshold linearity criterion for interference suppression” ,

IEEE Explore Digital Library.

[11] US National Library of Medicine National Institute of Health "Power-

line interference detection and suppression in ECG signal processing” IEEE

Trans Biomed Eng. 2008 Jan;55(1):354-7.

[12] S Hargittai, Innomed Medical Inc, Budapest, Hungary “Efficient and

Fast ECG Baseline Wander Reduction without Distortion of Important

Clinical Information”

[13] V´ıctor Barbero Romero; Profesor director: David Atienza Alonso;

Profesora colaboradora: Nadia Khaled, UC3M, Madrid “ECG baseline

wander removal and noise suppression analysis in an embedded platform”.

[14] “High-Bandpass Filters in Electrocardiography: Source of Error in the

Interpretation of the ST Segment.” ISRN Cardiology; Volume 2012 (2012),

Article ID 706217, 10 pages; doi:10.5402/2012/706217

Fig. 19a. PQRST with FIR filter

order 1156

Fig. 19b. PQRST with FIR

filter order 900

Fig. 19a. PQRST with FIR filter order 750