Photoplethysmogram (PPG) signal can provide vital diagnostic information on cardiovascular functions of the human body. In this paper, a lossless, real-time compression technique based on combination of second-order delta and the Huffman encoding is proposed for the PPG signal. The algorithm was validated with 10-bit quantized PPG data collected from multiparameter intelligent monitoring in intensive care-II database under Physionet and healthy volunteers using Biopac Systems at 125-Hz sampling frequency. Using a block size of 48 samples, the average compression ratio, percentage root-mean-squared difference (PRD), and PRD normalized achieved was 2.223, 0.127, and 0.187 respectively with 30 sets of volunteers' data. Three prime clinical features, systolic amplitude, systolic upstroke time, and pulse width from the decompressed PPG waveform were evaluated with less than 1% distortion on the diagnostic measures. A study was also done to estimate the compression efficiency for different sample block size, wave morphology, and sampling frequency of raw data. The low time complexity of the proposed algorithm encourages its implementation for development low-cost real-time PPG measurement application in patient monitoring. © 1963-2012 IEEE.

RAJARSHI GUPTA

Applied Physics

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Lossless Compression Technique for Real-Time Photoplethysmographic Measurements

IEEE Transactions on Instrumentation and Measurement

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

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

Electrocardiogram (ECG) compression finds wide application in various patient monitoring purposes. Quality control in ECG compression ensures reconstruction quality and its clinical acceptance for diagnostic decision making. In this paper, a quality aware compression method of single lead ECG is described using principal component analysis (PCA). After pre-processing, beat extraction and PCA decomposition, two independent quality criteria, namely, bit rate control (BRC) or error control (EC) criteria were set to select optimal principal components, eigenvectors and their quantization level to achieve desired bit rate or error measure. The selected principal components and eigenvectors were finally compressed using a modified delta and Huffman encoder. The algorithms were validated with 32 sets of MIT Arrhythmia data and 60 normal and 30 sets of diagnostic ECG data from PTB Diagnostic ECG data ptbdb, all at 1 kHz sampling. For BRC with a CR threshold of 40, an average Compression Ratio (CR), percentage root mean squared difference normalized (PRDN) and maximum absolute error (MAE) of 50.74, 16.22 and 0.243 mV respectively were obtained. For EC with an upper limit of 5 % PRDN and 0.1 mV MAE, the average CR, PRDN and MAE of 9.48, 4.13 and 0.049 mV respectively were obtained. For mitdb data 117, the reconstruction quality could be preserved up to CR of 68.96 by extending the BRC threshold. The proposed method yields better results than recently published works on quality controlled ECG compression. © 2016, Springer Science+Business Media New York.

Journal	Data powered by TypesetIEEE Transactions on Instrumentation and Measurement
Publisher	Data powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
ISSN	0018-9456
Open Access	No