A Novel AMARS Technique for Baseline Wander Removal Applied to Photoplethysmogram

A new digital filter, AMARS (aligning minima of alternating random signal) has been derived using trigonometry to regulate signal pulsations inline. The pulses are randomly presented in continuous signals comprising frequency band lower than the signal's mean rate. Frequency selective filters are conventionally employed to reject frequencies undesired by specific applications. However, these conventional filters only reduce the effects of the rejected range producing a signal superimposed by some baseline wander (BW). In this work, filters of different ranges and techniques were independently configured to preprocess a photoplethysmogram, an optical biosignal of blood volume dynamics, producing wave shapes with several BWs. The AMARS application effectively removed the encountered BWs to assemble similarly aligned trends. The removal implementation was found repeatable in both ear and finger photoplethysmograms, emphasizing the importance of BW removal in biosignal processing in retaining its structural, functional and physiological properties. We also believe that AMARS may be relevant to other biological and continuous signals modulated by similar types of baseline volatility.

[1]  Dae-Geun Jang,et al.  A Knowledge-Based Approach to Arterial Stiffness Estimation Using the Digital Volume Pulse , 2012, IEEE Transactions on Biomedical Circuits and Systems.

[2]  Changchun Liu,et al.  Removing Baseline Drift in Pulse Waveforms by a Wavelet Adaptive Filter , 2008, 2008 2nd International Conference on Bioinformatics and Biomedical Engineering.

[3]  Dale Schuurmans,et al.  Detection of a and b waves in the acceleration photoplethysmogram , 2014, Biomedical engineering online.

[4]  S. Laurent,et al.  Aortic Stiffness Is an Independent Predictor of Primary Coronary Events in Hypertensive Patients: A Longitudinal Study , 2002, Hypertension.

[5]  C. Papaloukas,et al.  A knowledge-based technique for automated detection of ischaemic episodes in long duration electrocardiograms , 2006, Medical and Biological Engineering and Computing.

[6]  An‐Bang Liu,et al.  Endothelium function assessment with radial pulse wave signals , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  Gregory Y H Lip,et al.  Measurement of stiffness index by digital volume pulse analysis technique: clinical utility in cardiovascular disease risk stratification. , 2008, American journal of hypertension.

[8]  H. Nazeran,et al.  Comparison of Heart Rate Variability Signal Features Derived from Electrocardiography and Photoplethysmography in Healthy Individuals , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  Geevarghese Titus,et al.  Photoplethysmogram (PPG) signal analysis and wavelet de-noising , 2014, 2014 Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD).

[10]  U. Eisenberger,et al.  Arterial stiffness assessed by digital volume pulse correlates with comorbidity in patients with ESRD. , 2006, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[11]  Nigel H. Lovell,et al.  Spectral Analysis of Finger Photoplethysmographic Waveform Variability in a Model of Mild to Moderate Haemorrhage , 2008, Journal of Clinical Monitoring and Computing.

[12]  Dae-Geun Jang,et al.  A Robust Method for Pulse Peak Determination in a Digital Volume Pulse Waveform With a Wandering Baseline , 2014, IEEE Transactions on Biomedical Circuits and Systems.

[13]  Alan Murray,et al.  A prospective comparison of bilateral photoplethysmography versus the ankle-brachial pressure index for detecting and quantifying lower limb peripheral arterial disease. , 2008, Journal of vascular surgery.

[14]  Sneh Anand,et al.  Monitoring of reactive hyperemia using photoplethysmographic pulse amplitude and transit time , 2009, Journal of Clinical Monitoring and Computing.

[15]  J B Harness,et al.  Skin photoplethysmography--a review. , 1989, Computer methods and programs in biomedicine.

[16]  M. Elgendi On the Analysis of Fingertip Photoplethysmogram Signals , 2012, Current cardiology reviews.

[17]  Kirk H. Shelley,et al.  A Novel Approach Using Time–Frequency Analysis of Pulse-Oximeter Data to Detect Progressive Hypovolemia in Spontaneously Breathing Healthy Subjects , 2011, IEEE Transactions on Biomedical Engineering.

[18]  Guang-Zhong Yang,et al.  Ratiometric Artifact Reduction in Low Power Reflective Photoplethysmography , 2011, IEEE Transactions on Biomedical Circuits and Systems.

[19]  N. Selvaraj,et al.  Feasibility of Photoplethymographic Signal for Assessment of Autonomic Response using Heart Rate Variability Analysis , 2007 .

[20]  Rangaraj M. Rangayyan,et al.  Biomedical Signal Analysis: A Case-Study Approach , 2001 .

[21]  Lin Yang,et al.  Removal of Pulse Waveform Baseline Drift Using Cubic Spline Interpolation , 2010, 2010 4th International Conference on Bioinformatics and Biomedical Engineering.

[22]  Roy D. Wallen,et al.  System Theory and Practical Applications of Biomedical Signals , 2004 .

[23]  David Zhang,et al.  Wavelet-based cascaded adaptive filter for removing baseline drift in pulse waveforms , 2005, IEEE Transactions on Biomedical Engineering.

[24]  P. Chowienczyk,et al.  Noninvasive Assessment of the Digital Volume Pulse: Comparison With the Peripheral Pressure Pulse , 2000, Hypertension.

[25]  Derek Abbott,et al.  Systolic Peak Detection in Acceleration Photoplethysmograms Measured from Emergency Responders in Tropical Conditions , 2013, PloS one.

[26]  Kejia Li,et al.  A Wireless Reflectance Pulse Oximeter With Digital Baseline Control for Unfiltered Photoplethysmograms , 2012, IEEE Transactions on Biomedical Circuits and Systems.

[27]  K. Nakajima,et al.  Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique. , 1996, Medical engineering & physics.

[28]  A. Murray,et al.  Modelling the relationship between peripheral blood pressure and blood volume pulses using linear and neural network system identification techniques , 1999, Physiological measurement.

[29]  Lucas J. van Vliet,et al.  The digital signal processing handbook , 1998 .

[30]  Ki H. Chon,et al.  Estimation of Respiratory Rate From Photoplethysmogram Data Using Time–Frequency Spectral Estimation , 2009, IEEE Transactions on Biomedical Engineering.

[31]  K. Chellappan,et al.  Age-related Upper Limb Vascular System Windkessel Model using Photoplethysmography , 2007 .

[32]  Vaidotas Marozas,et al.  Photoplethysmography-Based Method for Automatic Detection of Premature Ventricular Contractions , 2015, IEEE Transactions on Biomedical Circuits and Systems.

[33]  Nigel H. Lovell,et al.  Classification of low systemic vascular resistance using photoplethysmogram and routine cardiovascular measurements , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[34]  Respiration-induced changes in ear photoplethysmography relates to relative blood volume during hemodialysis , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[35]  Hartmut Ewald,et al.  An optical device to measure blood components by a photoplethysmographic method , 2005 .

[36]  Suzanne Wendelken,et al.  Noninvasive Detection of the Hemodynamic Stress of Exercise Using the Photoplethysmogram , 2008, Journal of Clinical Monitoring and Computing.

[37]  P. Chowienczyk,et al.  Contour analysis of the photoplethysmographic pulse measured at the finger , 2006, Journal of hypertension.

[38]  Stephen R. Alty,et al.  Median Filter Approach for Removal of Baseline Wander in Photoplethysmography Signals , 2013, 2013 European Modelling Symposium.

[39]  E.J. Delp,et al.  Impulsive noise suppression and background normalization of electrocardiogram signals using morphological operators , 1989, IEEE Transactions on Biomedical Engineering.

[40]  P A Oberg,et al.  Photoplethysmography. Part 2. Influence of light source wavelength. , 1991, Medical & biological engineering & computing.

[41]  Nigel H. Lovell,et al.  Photoplethysmographic variability analysis in critical care — Current progress and future challenges , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[42]  D. Silverman,et al.  Impact of central hypovolemia on photoplethysmographic waveform parameters in healthy volunteers. Part 1: time domain Analysis , 2011, Journal of Clinical Monitoring and Computing.

[43]  Lu Wang,et al.  Automatic detection of left ventricular ejection time from a finger photoplethysmographic pulse oximetry waveform: comparison with Doppler aortic measurement , 2007, Physiological measurement.

[44]  W Zidek,et al.  Increased arterial vascular tone during the night in patients with essential hypertension , 2007, Journal of Human Hypertension.

[45]  J. Spigulis,et al.  Multilaser photoplethysmography technique , 2008, Lasers in Medical Science.

[46]  Izzet Kale,et al.  Interference Resilient Sigma Delta-Based Pulse Oximeter , 2016, IEEE Transactions on Biomedical Circuits and Systems.

[47]  S. Hargittai Efficient and fast ECG baseline wander reduction without distortion of important clinical information , 2008, 2008 Computers in Cardiology.

[48]  Brief,et al.  Pulse Wave Analysis Digital Plethysmography Finger Plethysmography Accelerated Plethysmography Clinical Bottom Line-The Simple Explanation , 2013 .

[49]  Fei Zhang,et al.  QRS Detection Based on Multiscale Mathematical Morphology for Wearable ECG Devices in Body Area Networks , 2009, IEEE Transactions on Biomedical Circuits and Systems.

[50]  Toshiyo Tamura,et al.  Wearable Photoplethysmographic Sensors—Past and Present , 2014 .

[51]  Mohd Alauddin Mohd Ali,et al.  Analysis of the Effect of Ageing on Rising Edge Characteristics of the Photoplethysmogram using a Modified Windkessel Model , 2007, Cardiovascular engineering.

[52]  P. Laguna,et al.  Time-varying spectral analysis for comparison of HRV and PPG variability during tilt table test , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[53]  Kirk H. Shelley,et al.  Early detection of spontaneous blood loss using amplitude modulation of Photoplethysmogram , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[54]  Myoungho Lee,et al.  Adaptive threshold method for the peak detection of photoplethysmographic waveform , 2009, Comput. Biol. Medicine.

[55]  Surekha Palreddy Signal Processing Algorithms , 1997 .

[56]  V. S. Murthy,et al.  Analysis of photoplethysmographic signals of cardiovascular patients , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[57]  L.S. Xu,et al.  Pulse baseline wander removal using wavelet approximation , 2003, Computers in Cardiology, 2003.

[58]  P. Chowienczyk,et al.  Determination of age-related increases in large artery stiffness by digital pulse contour analysis. , 2002, Clinical science.

[59]  John G. Webster,et al.  Design of Pulse Oximeters , 1997 .

[60]  George T. Blike,et al.  Identifying Airway Obstructions Using Photoplethysmography (PPG) , 2008, Journal of Clinical Monitoring and Computing.

[61]  Eugene N. Bruce,et al.  Biomedical Signal Processing and Signal Modeling , 2000 .

[62]  Westgate Road,et al.  Photoplethysmography and its application in clinical physiological measurement , 2007 .

[63]  Kayvan Najarian,et al.  A Hierarchical Method for Removal of Baseline Drift from Biomedical Signals: Application in ECG Analysis , 2013, TheScientificWorldJournal.

[64]  K. Takazawa,et al.  Assessment of vasoactive agents and vascular aging by the second derivative of photoplethysmogram waveform. , 1998, Hypertension.

[65]  H. Asada,et al.  Utility of the Photoplethysmogram in Circulatory Monitoring , 2008, Anesthesiology.

[66]  J. Sinex Pulse oximetry: principles and limitations. , 1999, The American journal of emergency medicine.

[67]  Ammar Y. K. Timimi,et al.  Sensor factors influencing photoplethysmography , 2014, 2014 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS).