ArticleScientific reports2021
Real-time estimation of phase and amplitude with application to neural data.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Predictability of sleep slow oscillation emergence and spatial extent from pre-onset neural dynamics.Scientific reports · 2026Article
- Optimizing real-time phase detection in diverse rhythmic biological signals for phase-specific neurostimulation.Journal of neural engineering · 2025Article
- Feedback Control of Coupled Nonlinear Oscillators with Uncertain Parameters.Systems & control letters · 2025Article
- Neural signal analysis in chronic stroke: advancing intracortical brain-computer interface design.Frontiers in human neuroscience · 2025Article
- A Miniature Wireless Device for Closed-Loop Auditory Sleep Modulation.International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering · 2025Article
- Feedback control of collective dynamics in an oscillator population with time-dependent connectivity.Frontiers in network physiology · 2024Article
- Open Hardware Implementation of Real-Time Phase and Amplitude Estimation for Neurophysiologic Signals.Bioengineering (Basel, Switzerland) · 2023Article
- Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement.Frontiers in neuroscience · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computation of the instantaneous phase and amplitude via the Hilbert Transform is a powerful tool of data analysis. This approach finds many applications in various science and engineering branches but is not proper for causal estimation because it requires knowledge of the signal's past and future. However, several problems require real-time estimation of phase and amplitude; an illustrative example is phase-locked or amplitude-dependent stimulation in neuroscience. In this paper, we discuss and compare three causal algorithms that do not rely on the Hilbert Transform but exploit well-known physical phenomena, the synchronization and the resonance. After testing the algorithms on a synthetic data set, we illustrate their performance computing phase and amplitude for the accelerometer tremor measurements and a Parkinsonian patient's beta-band brain activity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.