Use of power-line interference for adaptive motion artifact removal in biopotential measurements

Motion artifacts (MA) have long been a problem in biopotential measurements. Adaptive filtering is widely used for optimal noise removal in many biomedical applications. However, the existing adaptive filtering methods involve the use of additional sensors, limiting the applicability of adaptive filtering for MA reduction. In the present study, a novel adaptive filtering method without need for additional sensors is proposed. In biopotential measurements, movement of the electrodes and their leads may cause variations not only in the skin and half-cell potential (motion artifacts), but also in the electrode-skin impedance. Such impedance variations may also cause power-line interference modulation (PLIM), resulting in additional spectral components around the power-line interference (PLI) in the frequency domain. Demodulation of the PLI may reflect the movement-induced electrode-skin impedance variation, and can therefore represent a reference signal for the adaptive filter. Preliminary validation on ECG measurements with seven volunteers showed a high correlation coefficient (R  =  0.97) between MA and PLIM, and excellent MA removal by the proposed adaptive filter, possibly leading to improved analysis of biopotential signals.

[1]  Heinz Jäckel,et al.  Continuous Monitoring of Electrode--Skin Impedance Mismatch During Bioelectric Recordings , 2008, IEEE Transactions on Biomedical Engineering.

[2]  C. Grimbergen,et al.  Investigation into the origin of the noise of surface electrodes , 2002, Medical and Biological Engineering and Computing.

[3]  Jan W. M. Bergmans,et al.  An Improved Adaptive Power Line Interference Canceller for Electrocardiography , 2006, IEEE Transactions on Biomedical Engineering.

[4]  Louis L. Scharf,et al.  A Multistage Representation of the Wiener Filter Based on Orthogonal Projections , 1998, IEEE Trans. Inf. Theory.

[5]  N V Thakor,et al.  Adaptive Filterng of Evoked Potentials , 1987, IEEE Transactions on Biomedical Engineering.

[6]  G. Reeder,et al.  Tremor-induced ECG artifact mimicking ventricular tachycardia. , 2000, Circulation.

[7]  C. A. Grimbergen,et al.  HIGH QUALITY RECORDING OF BIOELECTRIC EVENTS . I : INTERFERENCE REDUCTION , THEORY AND PRACTICE , 2009 .

[8]  J G Webster,et al.  60-HZ interference in electrocardiography. , 1973, IEEE transactions on bio-medical engineering.

[9]  Meltem Izzetoglu,et al.  Motion artifact cancellation in NIR spectroscopy using discrete Kalman filtering , 2010, Biomedical engineering online.

[10]  Fernando Lopes da Silva,et al.  Comprar Niedermeyer's Electroencephalography, 6/e (Basic Principles, Clinical Applications, and Related Fields ) | Fernando Lopes Da Silva | 9780781789424 | Lippincott Williams & Wilkins , 2010 .

[11]  David A. Tong,et al.  Adaptive reduction of motion artifact in the electrocardiogram , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[12]  Massimo Mischi,et al.  The effects of a 28-Hz vibration on arm muscle activity during isometric exercise. , 2009, Medicine and science in sports and exercise.

[13]  Shen Luo,et al.  Experimental study: brachial motion artifact reduction in the ECG , 1995, Computers in Cardiology 1995.

[14]  M. Mischi,et al.  Electromyographic assessment of muscle fatigue during isometric vibration training at varying frequencies , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[15]  Rik Vullings,et al.  Motion Artifacts in Capacitive ECG Measurements: Reducing the Combined Effect of DC Voltages and Capacitance Changes Using an Injection Signal , 2015, IEEE Transactions on Biomedical Engineering.

[16]  B. Widrow,et al.  Adaptive noise cancelling: Principles and applications , 1975 .

[17]  Pablo Laguna,et al.  Bioelectrical Signal Processing in Cardiac and Neurological Applications , 2005 .

[18]  J G Webster,et al.  MOTION ARTIFACT FROM ELECTRODES AND CABLES , 2010 .

[19]  Herbert Voigt,et al.  The Belgian Society for Medical and Biological Engineering and Computing , 2014 .

[20]  Wei Qiu,et al.  Adaptive filtering of evoked potentials with radial-basis-function neural network prefilter , 2002, IEEE Transactions on Biomedical Engineering.

[21]  Rik Vullings,et al.  Novel Bayesian Vectorcardiographic Loop Alignment for Improved Monitoring of ECG and Fetal Movement , 2013, IEEE Transactions on Biomedical Engineering.

[22]  J. Webster,et al.  The origin of skin-stretch-caused motion artifacts under electrodes. , 1996, Physiological measurement.

[23]  Ernst Fernando Lopes Da Silva Niedermeyer,et al.  Electroencephalography, basic principles, clinical applications, and related fields , 1982 .

[24]  Massimo Mischi,et al.  On the nature of the electromyographic signals recorded during vibration exercise , 2015, European Journal of Applied Physiology.

[25]  M. Mischi,et al.  Propagation of electrical activity in uterine muscle during pregnancy: a review , 2015, Acta physiologica.

[26]  J. Webster,et al.  Reducing skin potential motion artefact by skin abrasion , 2006, Medical and Biological Engineering and Computing.

[27]  Akif Ündar,et al.  Medical instrumentation: Application and design , 1997 .

[28]  J. Webster,et al.  Minimizing Electrode Motion Artifact by Skin Abrasion , 1977, IEEE Transactions on Biomedical Engineering.

[29]  B Freedman,et al.  Tremor-induced ECG artifact mimicking ventricular tachycardia. , 2001, Circulation.

[30]  S. Ödman,et al.  Movement-induced potentials in surface electrodes , 1982, Medical and Biological Engineering and Computing.

[31]  Chiara Rabotti,et al.  Characterization of a novel instrument for vibration exercise , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[32]  Juliane Junker,et al.  Medical Instrumentation Application And Design , 2016 .

[33]  G F Michaud,et al.  Physician interpretation of electrocardiographic artifact that mimics ventricular tachycardia. , 2001, The American journal of medicine.

[34]  Gregory F. Michaud,et al.  Physician interpretation of electrocardiographic artifact that mimics ventricular tachycardia. , 2001, The American journal of medicine.

[35]  G J Kemp,et al.  Electromyographic assessment of muscle fatigue in massive rotator cuff tear. , 2015, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[36]  M. Mischi,et al.  Novel Vibration-Exercise Instrument With Dedicated Adaptive Filtering for Electromyographic Investigation of Neuromuscular Activation , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[37]  S. Ödman Potential and impedance variations following skin deformation , 2006, Medical and Biological Engineering and Computing.

[38]  Jacob Benesty,et al.  New insights into the noise reduction Wiener filter , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[39]  N.V. Thakor,et al.  Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection , 1991, IEEE Transactions on Biomedical Engineering.

[40]  C A Grimbergen,et al.  High-quality recording of bioelectric events , 1991, Medical and Biological Engineering and Computing.