IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion The International Symposium on Emerging Areas in Biotechnology & Bioengineering ( ISEABB ), 26 th -28 th Feb 2009, Mumbai, India. Wavelet Based Denoising for Suppression of Motion Artifacts in Impedance Cardiography By V.K. Pandey P.C. Pandey IIT Bombay, India

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Abstract Impedance cardiography is a noninvasive technique for monitoring the stroke volume and some other cardiovascular indices, based on sensing the changes in the electrical impedance of the thorax, caused by variation in the blood volume during the cardiac cycle. Respiratory and motion artifacts cause baseline drift in the sensed impedance waveform, particularly during or after exercise, and this drift results in errors in the estimation of the parameters. In the present study, we examine the applicability of FIR Meyer wavelet based linear denoising technique, investigated earlier for suppression of the respiratory artifact, for cancellation of the motion artifact, without smearing the beat-to-beat variations in the parameters.

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Presentation Overview ● Introduction ● Method ● Results ● Conclusion

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion ● Introduction ● Method ● Results ● Conclusion

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Impedance Cardiography A noninvasive technique for monitoring stroke volume & obtaining diagnostic information on cardiovascular functioning by sensing variation in thoracic impedance due to change in blood volume and based on a thoracic impedance model Established methods for SV measurement Electromagnetic flowmeter Thermodilution method Fick’s dye dilution method CO 2 rebreathing method Doppler Echocardiography Introduction

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Origin of the thoracic impedance (Sensing by 4 - electrode configuration) Conductive path way: vena cava & thoracic aorta Intercostal muscle & less conducting lungs tissues Non conducting ribs: perpendicular to the current path Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Contributions to changes in thoracic impedance Cardiovascular activity - pulsating blood flow: aorta & pulmonary artery Erythrocytes orientation - acceleration of blood Respiration - change in intra-thoracic pressure Motion - change in thoracic dimension Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Impedance model of the thorax Thoracic region modeled as a conductor of fixed length and variable cross-sectional area An increase in the volume of the blood in the region → decrease in its resistance Stroke volume ∆ V = stroke volume (mL), ρ = resistivity of blood (Ω-cm), L = the length of the modeled conductor (cm), Z o = the basal impedance (Ω), (- dz/dt) max = the maximum of the derivative of the impedance during the systole (Ω/s), T lvet = left ventricle ejection time (s) Cardiac output = SV х HR Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Impedance cardiograph technique  ICG : (- dz/dt ) waveform  Parameters for calculating the stroke volume : (- dz/dt) max and T lvet  Point B : aortic valve opening (1 st heart sound in PCG)  Point X : aortic valve closure (2 nd heart sound in PCG)  T lvet : time diff. between the point B & X Adopted from Malmivuo, J., and Plonsey, R. (1995). Bioelectromagnetism (2 nd ed., Oxford Univ. Press, New York). Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Instrumentation High freq. ( kHz) and low amplitude (1-5 mA) current injected Amplitude modulated voltage picked up Voltage signal  demodulated  processed to get SV and CO Z o ≈ 20 , z(t) < 0.2 , (-dz/dt) max < 1.5  /s Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Problems with impedance cardiography ● Simplified assumption in formulas for stroke volume estimation ● Presence of respiratory and motion artifacts in the sensed ICG Research objective Investigation of a technique for suppression of the artifacts from the thoracic impedance signal, for estimation of the stroke volume and other cardiovascular indices on beat-to-beat basis Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion ● Artifacts in the sensed thoracic impedance signal  Respiration  change in thoracic air volume & thoracic dimension  Motion  change in thoracic dimension  Respiratory & motion artifacts in ICG ◦ low frequency & large amplitude ◦ result in base line variation ◦ spectra partly overlap with that of ICG ◦ errors in detection of B and X points  error in calculating T lvet Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion ● Solutions ♦ Holding breath ◦ Change in SV ◦ Difficult during or after exercise ♦ Ensemble averaging of ICG (Qu et al, 1968; Zhang et al, 1986; Hurwitz et al, 1988; Riese et al, 2003) R-point synchronized time frames (  R-point – 1/8 * R-R interval, R-point + 3/4 * R-R interval) ◦ Beat-to-beat relation lost ◦ Smudging of ICG peaks ◦ Shifting, blurring or loss of B & X points ♦ Narrow band IIR filter, centered around HR (Yamamota et al, 1988) ◦ Nonlinear phase ◦ Attenuation of high freq. component of ICG Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion ♦ HP IIR digital filter with cardio-respiratory synchronization (Raza et al, 1992) : distortion of ICG signal during or after exercise ♦ Adaptive filter with scaled Fourier linear combiner (Barros et al, 1995) : may produce a distorted output due to variation in time difference between the electrical and mechanical activities of the heart ♦ Wavelet-based method based on soft thresholding (Ouyong et al, 1998) : uses soft thresholding, breath holding for 8 s is needed to construct the auto-regressive model of the cardiac signal ♦ Adaptive filter with sensed respiration as reference, simultaneously acquired with ICG (Pandey et al, 2005) ◦ Fail to suppress higher harmonics of the respiratory artifacts ◦ Not suitable for suppressing motion artifacts due to difficulty in sensing the references related to the sources of various motions ♦ Decomposition with specific orthonormal basis (Krivoshei et al, 2008) : can not track fast variation, no validation/ evaluation for this technique reported by authors Introduction (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion ● Introduction Method ● Method ● Results ● Conclusion

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Wavelet based denoising (WBD) technique Removal of respiratory & motion artifacts, for preserving beat-to-beat variation in the estimated SV and other indices, without using a reference signal ♦ Application of wavelet based denoising for suppression of respiratory artifact (Pandey & Pandey, 2007) 1. Processing of signals with simulated respiratory artifact (-9 to 9 dB): SNR improvement of 21.8 dB. 2. Application for beat-to-beat SV estimation with Doppler echocardiography as a reference technique on post-exercise recordings (9 subjects): correlation coefficients changed to ♦ Application of the technique for suppression of motion artifact Method

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion DWT based linear denoising (scale dependent thresholding) ♦ Decomposition of signal (S.R. = 500 Hz) using dyadic multiresolution analysis into details and the approximation, using. Daubechies. Coiflets. Symlets. FIR Meyer ♦ FIR based Meyer wavelet analysis (10 scales): ICG & z ( t ) captured in first 8 scales while the artifact in higher scales ♦ Basic steps: 1) Calculate the DWT coefficients up to 10 scales 2) Reconstruction of signal with D1- D8. Method (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Experimental Set-up ♦ Acquisition of ICG, z(t), Zo, & ECG ◦ ICG instrument (developed at IIT Bombay) and 4-electrode configuration Injecting a current (≈ 100 kHz, < 5 mA) through the outer electrode pair (upper part of the neck, abdomen) & sensing the resulting AM voltage across inner electrode pair (lower part of neck, level of xiphoid and sternum) ◦ USB based signal acquisition unit. Sampling rate : 500 Sa/s. Quantization : 12 bit. Recording length : 5 min.  Recordings: Taken with breath hold to avoid respiratory artifact  Subjects 7 professional swimmers (age years, with no known cardiovascular disorders) Method (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion ● Introduction ● Method Results ● Results ● Conclusion

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Processing of ICG from subject ‘JJ’ taken with the breath held for 30 s and left hand movement (a) recorded ICG (in Ω/s), (b) estimated artifact (in arbitrary units), (c) processed ICG (in Ω/s). Results

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Results (contd) Processing of ICG from subject ‘SY’ taken with the breath held for 20 s and jogging at slow pace (a) recorded ICG (in Ω/s), (b) estimated artifact (in arbitrary units), (c) processed ICG (in Ω/s).

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion Distortion in the artifact-free output: dB Denoised ICG. No visible motion artifacts. Stable ICG peaks and characteristic points. Improved estimation of parameters from ICG Result Summary Results (contd)

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion ● ● Introduction ● Method ● Results Conclusion ● Conclusion

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion ● Wavelet based denoising suppresses respiratory & motion artifacts present in ICG, with negligible distortion. ● Technique enables cycle-by-cycle stroke volume (& cardiac output) calculation, useful during exercise or post-exercise recordings, where cardiac activity is rapidly changing. Conclusion

IIT Bombay ● Introduction ● Method ● Results ● ConclusionIntroductionMethodResultsConclusion