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Cited by 35Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlECG Monitoring and Analysis

Comparison of different signal processing methods for reducing artifacts from photoplethysmograph signal

Naraharisetti, Kali Vara Prasad, Bawa, Manan·2011·2011 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY
DOI 10.1109/eit.2011.5978571
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Abstract

Measurement of photoplethysmograph signal plays an important role in medical applications. PPG is measured by an equipment named pulse oximeter which gives the oxygen saturation of arterial blood. The PPG signal measured by the pulse oximeter sensor is likely to be corrupted by motion artifacts created by hand movement or any other type of movement in the body. Movement artifacts become a major obstacle when measuring the oxygen saturation (SpO2) level. In recent years, many methods have been developed to reduce motion artifacts from PPG signal. This paper gives a comparison of five different signal processing methods implemented towards motion artifact reduction which include Adaptive Noise Cancellation (ANC), Wavelet Transform (WT), Independent Component Analysis (ICA), Singular Value Decomposition (SVD) and Cycle by Cycle Fourier Series Analysis (FSA). The results obtained after implementing the five methods revealed that SVD and FSA methods have given better results in terms of artifact reduction and also signal restoration. Performances of the five methods have been evaluated in terms of heart rate (HR) estimation error, mean ±standard deviation of peak to peak values of the enhanced PPG signal obtained after implementing all the five different methods.

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  • Several data mining techniques are applied for these tasks: wavelet analysis for artifact reduction and data compression, rule-based methods for data summarizing and transmitting, and Gaussian process for secure authentication.

    “In order to conduct these problems, several data mining techniques are applied such as wavelet analysis for artifact reduction [53] and data compression [54], rule-based methods for data summarizing and transmitting [55,56], and Gaussian process for secure authentication [57].”

    From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [53]

  • Other general statistical parameters and probability functions have been used for data mining techniques in the literature.

    “Aside from the above mentioned techniques, other general statistical parameters and probability functions have been used for data mining techniques in the literature [39,53].”

    From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [53]

  • Another group of papers focused on small scale of subjects (maybe one or at most 10 persons) to investigate the accuracy and correctness of results in the proposed model.

    “Due to the type of data mining tools, another group of papers focused on small scale of subjects (maybe one or at most 10 persons) in order to investigate the accuracy and correctness of results in proposed model [27,53].”

    From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [53]

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Authors
Naraharisetti, K. V. P., & Bawa, M.
Affiliations
Northern Illinois University (US)
ORCID
Naraharisetti, Kali Vara Prasad
Venue
2011 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY
Publisher
IEEE
Published
2011-05
Pages
1-8
ISSN
2154-0357 (ISSN-L)
DOI
10.1109/eit.2011.5978571
OpenAlex
W2130042109
Cited by
35
References
21
Citations by year
2025: 1 · 2023: 3 · 2022: 4 · 2021: 3 · 2020: 2 · 2019: 2 · 2018: 3 · 2017: 3 · 2016: 5 · 2015: 2 · 2014: 3 · 2013: 3 · 2012: 1
FWCI
4.73
Type
conference paper
Language
en
Open access
closed
Locations
IEEE International Conference on Electro Information Technology (publishedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
Keywords
photoplethysmography, motion artifact reduction, pulse oximetry, signal denoising, adaptive noise cancellation, wavelet transform, independent component analysis, singular value decomposition, Fourier series analysis, heart rate estimation, oxygen saturation

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