Pulse oximeters require artifact-free clean photoplethysmograph (PPG) signals obtained at red and infrared (IR) wavelengths for the estimation of the level of oxygen saturation (SpO2) in the arterial blood of a patient. Movement of a patient corrupts a PPG signal with motion artifacts and introduces large errors in the computation of SpO2. A novel method for removing motion artifacts from corrupted PPG signals by applying Fourier series analysis on a cycle-by-cycle basis is presented in this paper. Aside from artifact reduction, the proposed method also provides data compression. Experimental results indicate that the proposed method is insensitive to heart rate variation, introduces negligible error in the processed PPG signals due to the additional processing, preserves all the morphological features of the PPG, provides 35 dB reduction in motion artifacts, and achieves a data compression factor of 12. © 2008 IEEE.

Boby George

Department of Electrical Engineering

Varadarajan Jagadeesh Kumar

Biomedical signal processing

motion artifact

OXYGEN SATURATION

PHOTOPLETHYSMOGRAPH (PPG)

PULSE OXIMETER

Data reduction

Electric currents

ELECTRONIC MEDICAL EQUIPMENT

Fourier analysis

Fourier series

Harmonic analysis

OXIMETERS

Oxygen

signal processing

Signal reconstruction

Data compression

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Use of Fourier Series Analysis for Motion Artifact Reduction and Data Compression of Photoplethysmographic Signals

IEEE Transactions on Instrumentation and Measurement

We study the potential of reflectance photoplethysmography (PPG) in monitoring free flaps for arterial and venous thrombosis in post-surgical scenarios. Circulatory disruptions due to thrombosis were simulated using limb ischemia method on 30 volunteers. Arterial and venous occlusions were conducted in this study. The variation in blood flow in the region of interest was captured by a custom built sensor and data acquisition system using dual wavelength reflectance photoplethysmography. The main chromophores in blood, oxygenated and reduced hemoglobin, showed good variation to visible - near infrared wavelengths with concentration and volume changes. Sensitivity of the prototype device in detecting arterial and venous circulation disruptions was evaluated at various different threshold levels of signal parameters. The device showed strong capability to accurately detect circulatory disruptions and has potential in post-surgical monitoring of free flaps. © 2016 IEEE.

2016 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016 - Proceedings

A reflectance photoplethysmography based device to detect circulatory disruptions

Continuous long term monitoring of Photoplethysmogram (PPG) in home monitoring applications necessitates the need for data compression to reduce the storage requirement. Limited PPG data compression techniques are available which have fully exploited the signal redundancies. This paper presents a PPG data compression technique based on adaptive estimation of the useful band-limit from the individual signal characteristic. Each data block is then represented using the corresponding discrete Fourier transform coefficients, which are encoded by adaptive quantization and optimal bit allocation to further enhance the compression performance. The algorithm achieves an overall compression ratio of 35.95 with signal distortion maintained below 4%, as tested with 16 bit quantized PPG data sampled at 125 Hz. The algorithm is also implemented and validated on a microcontroller based Arduino board. High compression performance, implementation simplicity and noise robustness justifies the potentiality of the algorithm for its use with portable home monitoring devices. © 2018

Measurement: Journal of the International Measurement Confederation

Adaptive Band Limit Estimation based PPG data compression for portable home monitors

Photoplethysmographic (PPG) measurements are susceptible to motion artifacts (MA) due to movement of the peripheral body parts. In this paper, we present a new approach to identify the MA corrupted PPG beats and then rectify the beat morphology using artificial neural network (ANN). Initially, beat quality assessment was done to identify the clean PPG beats by a pretrained feedback ANN to generate a reference beat template for each person. The PPG data were decomposed using principal component analysis (PCA) and reconstructed using fixed energy retention. A weight coefficient was assigned for each PPG sample in such a way that when they are multiplied, the modified beat morphology matches the reference template. A particle swarm optimization-based technique was utilized to select the best weight vector coefficients to tune another feedback ANN, fed with a set of significant features generated by an auto-encoder from PCA reconstructed data. For real-Time implementation, this pretrained ANN was operated in feed-forward mode to directly generate the weight vectors for any subsequent measurements of PPG. The method was validated with PPG data collected from 55 human subjects. An average root-mean-square error of 0.28 and signal-To-noise ratio improvement of 14.54 dB were obtained, with an average improvement of 36% and 47% measurement accuracies on crest time and systolic to diastolic peak height ratio, respectively. With the IEEE Signal Processing Cup 2015 challenge database, Pearson's correlation coefficient between PPG-estimated and ECG-derived heart rates was 0.990. The proposed method can be useful for personal health monitoring applications. © 1963-2012 IEEE.

Fulltext

Improving Photoplethysmographic Measurements under Motion Artifacts Using Artificial Neural Network for Personal Healthcare

In this paper, a high performing, reliable and robust Photoplethysmogram (PPG) compression and encryption method is proposed for efficient, safe and secure storage and transmission. PPG signals are acquired inside the laboratory using Biopac® data acquisition module and also downloaded from MIMIC database. Digitized PPG samples are passed through an IIR Butterworth Low-pass filter for high frequency noise elimination, down-sampled and then those samples are truncated up to 2nd-decimal places of accuracy. Second difference of those truncated PPG samples (SDPPG) are evaluated and amplified. Amplified integers are grouped using various techniques, encrypted using a symmetric key to convert plain text into cipher text and finally stored in the output file in form of American Standard Code for Information Interchange (ASCII) characters. Since the algorithm is completely reversible, PPG signal is reconstructed using just the reverse algorithm. The algorithm attains an attractive compression performance (Compression Ratio = 122.24, Percent Root Mean Square Difference = 0.02%, Cross Correlation Coefficient = 0.998845, etc.) which is superior to existing PPG compression methods reported to date. © 2017 Elsevier Ltd

An efficient data compression and encryption technique for PPG signal

Computerized acquisition and analysis of Photoplethysmogram (PPG) can provide vital information on various cardiovascular functions. In this paper, we introduce a quality controlled PPG compression technique using principal component analysis to keep the local and global distortion of the reconstructed data within pre-specified limits. To achieve this, optimum number of eigenvectors (EV) and principal components (PC) along with their quantization level (Q) were selected for compression. The technique was validated with pre-recorded 2 min and 10 min PPG data collected from 35 healthy volunteers (N) and 35 cardiovascular patients (CVP) under fully resting condition. At limiting PRD of 5% and absolute error of 8%, for N group (CVP group) an average compression ratio (CR), PRD and MAE of 5.65 (6.76), 2.41% (3.33%) and 6.1% (7.3%) were obtained respectively. Relaxing the control criteria up to clinically acceptable limits, a CR of 13.28 for N and 13.31 for CVP group were achieved. Most of the clinical features had an average deviation of less that 6% from their original values. The method yielded lower CR, PRDN and MAE with noisy (motion artifact and Gaussian noise) PPG. With two different stress levels, the compression parameters were found to vary. The reconstruction results were clinically validated by experts. A successful real-time data streaming in computer proved the usefulness of the technique for continuous monitoring applications. © 2018 Elsevier Ltd

Quality controlled compression technique for Photoplethysmogram monitoring applications

Artifact-free clean photoplethysmographic (PPG) signals obtained at red and infrared (IR) wavelengths are requiredfor the estimation of the level of oxygen saturation (SpO2) in arterial blood of a patient. Movement of a patient corrupts a PPG signal with motion artifacts and introduces large errors in the computation of SpO2. A novel method to remove motion artifacts from corrupted PPG signals by applying Fourier series analysis on a cycle by cycle basis is presented in this paper. Over and above artifact reduction, the proposed method also provides data compression. Experimental results indicate that the proposed method is insensitive to heart rate variation, introduces negligible error in the processed PPG signals due to the additional processing, preserves all the morphological features of the PPG, provides 35 dB reduction in motion artifact and achieves a data compression factor of 12. © 2008 IEEE.

Conference Record - IEEE Instrumentation and Measurement Technology Conference

Motion artifact reduction and data compression of photoplethysmo-graphic signals utilizing cycle by cycle fourier series analysis

IEEE Signal Processing Letters

Use of Independent Component Analysis to Reduce Motion Artifact in Pulse Transit Time Measurement

2006 IEEE Instrumentation and Measurement Technology Conference Proceedings

Virtual Instrument for the Measurement of Haemo-dynamic Parameters Using Photoplethysmograph

IEEE Transactions on Biomedical Engineering

Motion Artifact Reduction in Photoplethysmography Using Independent Component Analysis

Biomedical Signal Processing and Control

Comparison of wavelet transformation and adaptive filtering in restoring artefact-induced time-related measurement

Use of Fourier series analysis for motion artifact reduction and data compression of photoplethysmographic signals

Journal	IEEE Transactions on Instrumentation and Measurement
ISSN	00189456
Open Access	No