학술논문

Fourier Analysis Based Respiration Rate Estimation Using Corrupted Photoplethysmogram Signal
Document Type
Conference
Source
2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT) Multimedia, Signal Processing and Communication Technologies (IMPACT), 2022 5th International Conference on. :1-5 Nov, 2022
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Signal Processing and Analysis
Time-frequency analysis
Databases
Estimation
Signal processing algorithms
Benchmark testing
Photoplethysmography
Physiology
Photoplethysmography (PPG)
Fourier decomposition method (FDM)
Respiratory signal
Fast Fourier transform (FFT)
Respiration rate (RR)
Language
Abstract
This work proposes a Fourier series-based Fourier decomposition method (FDM) technique to analyze the photoplethysmography (PPG) signals to estimate respiration rate (RR). The proposed method consists of data acquisition, preprocessing, signal decomposition into Fourier intrinsic band function (FIBFs), Superposition of clean FIBFs, fast Fourier transform, spectral peak identification, and estimation of RR. The efficacy of the proposed FDM-based RR estimation method is evaluated using the CapnoBase database, a benchmark RR estimation database. The proposed method improves estimation accuracy with a mean absolute error (MAE) value of 1.02 breaths per minute (BPM) and a root mean square error value (RMSE) of 1.22. The proposed method can accurately estimate vital physiological parameter RR from the PPG signal.