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International Conference on Machine Learning, Image Processing, Network Security and Data Sciences

MIND 2020: Machine Learning, Image Processing, Network Security and Data Sciences pp 44–57Cite as

An Automated Algorithm for Estimating Respiration Rate from PPG Signals

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1241))

Abstract

Objective: This paper presents a simple automated method to estimate respiration rate (RR) from the photoplethysmography (PPG) signals. Methods: The method consists of preprocessing, extremely low-frequency two-pole digital resonator, fast Fourier transform, spectral magnitude computation, prominent spectral peak identification and respiration rate computation. Validation Dataset: The proposed RR estimation method is evaluated using standard PPG databases including MIMIC-II and CapnoBase. Results: The proposed method had estimation accuracy with absolute error value (median, 25th–75th percentiles) of 0.522 (0, 1.403) and 0.2746 (0, 0.475) breaths/minute for the PPG recordings from the MIMIC-II and CapnoBase databases, respectively for the 30 s segment. Results showed that the proposed method outperforms the existing methods such as the empirical mode decomposition and principal component analysis (EMD-PCA), ensemble EMD-PCA, and improved complete EEMD with adaptive noise-PCA methods. Conclusion: Results demonstrate that the proposed method is more accurate in estimating RR with less processing time of 0.0296 s as compared to that of the existing methods. This study further demonstrate that the two-pole digital resonator with extremely low-frequency can be simple method to estimate the RR from the PPG signals.

This research work is carried out with the support of IMPRINT-II and MHRD Grant, Government of India.

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Authors and Affiliations

  1. Biomedical System Lab, School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Jatani, Khordha, 752050, India

    Kinjarapu Manojkumar, Srinivas Boppu & M. Sabarimalai Manikandan

Authors
  1. Kinjarapu Manojkumar
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  2. Srinivas Boppu
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  3. M. Sabarimalai Manikandan
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Corresponding authors

Correspondence to Kinjarapu Manojkumar , Srinivas Boppu or M. Sabarimalai Manikandan .

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Editors and Affiliations

  1. National Institute of Technology Silchar, Silchar, India

    Arup Bhattacharjee

  2. National Institute Of Technology Silchar, Silchar, India

    Samir Kr. Borgohain

  3. National Institute of Technology Silchar, Silchar, India

    Badal Soni

  4. National Institute of Technology Kurukshetra, Kurukshetra, India

    Gyanendra Verma

  5. University of Eastern Finland, Kuopio, Finland

    Xiao-Zhi Gao

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Manojkumar, K., Boppu, S., Manikandan, M.S. (2020). An Automated Algorithm for Estimating Respiration Rate from PPG Signals. In: Bhattacharjee, A., Borgohain, S., Soni, B., Verma, G., Gao, XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. MIND 2020. Communications in Computer and Information Science, vol 1241. Springer, Singapore. https://doi.org/10.1007/978-981-15-6318-8_5

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  • DOI: https://doi.org/10.1007/978-981-15-6318-8_5

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  • Print ISBN: 978-981-15-6317-1

  • Online ISBN: 978-981-15-6318-8

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