ArticleScientific reports2022
Nonlinear frequency analysis of COVID-19 spread in Tokyo using empirical mode decomposition.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Hilbert-Huang transform based pupil changes analysis for concentration assessment in skilled mowing.Scientific reports · 2025Article
- Adaptive Fourier Decomposition of the First Three SARS-CoV-2 Infection Waves with Epidemic Intervention - London, UK, 2020-2022.China CDC weekly · 2024Article
- Biomechanical Analysis of Golf Swing Motion Using Hilbert-Huang Transform.Sensors (Basel, Switzerland) · 2023Article
- Daily fluctuations in COVID-19 infection rates under Tokyo's epidemic prevention measures - new evidence from adaptive Fourier decomposition.Frontiers in public health · 2023Article
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3 authors.
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Abstract
Empirical mode decomposition (EMD) was adopted to decompose daily COVID-19 infections in Tokyo from February 28, 2020, to July 12, 2021. Daily COVID-19 infections were nonlinearly decomposed into several monochromatic waves, intrinsic mode functions (IMFs), corresponding to their periodic meanings from high frequency to low frequency. High-frequency IMFs represent variabilities of random factors and variations in the number of daily PCR and antigen inspections, which can be nonlinearly denoised using EMD. Compared with a moving average and Fourier transform, EMD provides better performance in denoising and analyzing COVID-19 spread. After variabilities of daily inspections were weekly denoised by EMD, one low-frequency IMF reveals that the average period of external influences (public health and social measures) to stop COVID-19 spread was 19 days, corresponding to the measures response duration based on the incubation period. By monitoring this nonlinear wave, public health and social measures for stopping COVID-19 spread can be evaluated and visualized quantitatively in the instantaneous frequency domain. Moreover, another low-frequency IMF revealed that the period of the COVID-19 outbreak and retreat was 57 days on average. This nonlinear wave can be used as a reference for setting the timeframe for state of emergency declarations. Thus, decomposing daily infections in the instantaneous frequency domain using EMD represents a useful tool to improve public health and social measures for stopping COVID-19 spread.
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