Project Development - ISVR 6071 1

Removing Movement Artifacts from ECG Signals Recorded from Human

Subjects

Eirini Nikolaou

Supervisors: Dr. David Simpson, Dr. Emiliano Rustighi

14 June 2012

Project Development - ISVR 6071 2

ContentsIntroductionPurposeBackgroundMethodsExperimental Set-UpSignal Processing MethodsAssessment Methods for the ECG’s

qualitySummaryReferences

14 June 2012

Project Development - ISVR 6071 3

IntroductionElectrocardiogram (ECG): Willem

Einthoven - 1903Electrical potentials generated by the heart’s function amplified small electrical signalMovement artifacts or other

sources.Critical evaluation of cardiac

health depends on the ECG (e.g. Athletes, Soldiers, Patients)

14 June 2012

Project Development - ISVR 6071 4

Introduction

14 June 2012

Example of an ECG distorted by noise from electrical devices and the electrodes’ connection to the skin.

Project Development - ISVR 6071 5

PurposeInvestigation of the relationship

between the movement artifact and the movement itself

Removal of those artifacts without degrading the original ECG

14 June 2012

Project Development - ISVR 6071 6

BackgroundAdaptive noise cancelling: [1]

LMS algorithmRLS algorithm

Artifacts were introduced to the signal:Physical activities (running, walking etc)

Methods of assessing the quality of the ECGs:Coherence [2]Mean Square Error

14 June 2012

Project Development - ISVR 6071 7

BackgroundPrevious Experimental Results [3],[4]:

14 June 2012

RLS

LMS

Project Development - ISVR 6071 8

MethodsCapturing a clean ECGECG capture when hand/arm

vibration is introduced through shakers

Signal Analysis – 3-axis accelerometers for adaptive cancellers

Filtering for removing artifactsEvaluation of quality of

reconstructed signal14 June 2012

Project Development - ISVR 6071 9

Experimental Set-Up

14 June 2012

Block Diagram of the Equipment Used

Project Development - ISVR 6071 10

Signal Processing Methods

Filtering – Using MATLABWiener FiltersAdaptive Filters: - Least Mean Square Algorithm

- Recursive Least Square Algorithm

Nonlinear Filters

14 June 2012

Project Development - ISVR 6071 11

Assessment Methods for the ECG’s qualityQualitative and quantitative

criteriaComparison with Baseline ECG

Chest electrodes, without large muscle activity

Averaged standard deviation comparison

14 June 2012

Project Development - ISVR 6071 12

SummaryTechniques to remove ECG

movement artifacts:Non adaptiveAdaptiveNonlinear

Artificial motion artifacts:Shakers1-axis and 3-axis accelerometers

Assessment the ECG quality.

14 June 2012

Project Development - ISVR 6071 13

References:1. Milanesi, M. et al., 2006. Multichannel Techniques for Motion

Artifacts Removal from Electrocardiographic Signals. New York, IEEE.

2. Carse, A., 2010. Removing Movement Artefacts in ECG Signals from Human Subjects, Southampton: University of Southampton.

3. Lee, J.-W. & Lee, G.-K., 2005. Design of an Adaptive Filter with Dynamic Structure for ECG Signal Processing. International Journal of Control, Automation and Systems, Volume 3, pp. 137-142.

4. Dromer, O., Alata, O. & Bernard, O., 2009. Impedance Cardiography Filtering using Scale Fourier Linear Combiner based on RLS algorithm. 31st Annual International Conference of the IEEE EMBS, 2-6 September, pp. 6930-6933.

5. E. Nikolaou, Removing Movement Artifacts from ECG Signals Recorded from Human Subjects, Literature Review, Southampton: University of Southampton, 2012.

14 June 2012

Project Development - ISVR 6071 14

Thank You!

14 June 2012