EMD: A novel technique for the study of tremor time series

Eduardo Rocon de Lima*, A. O. Andrade, Jose L Pons, P. Kyberd, S. J. Nasuto

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper introduces the Hilbert Analysis (HA), which is a novel digital signal processing technique, for the investigation of tremor. The HA is formed by two complementary tools, i.e. the Empirical Mode Decomposition (EMD) and the Hilbert Spectrum (HS). In this work we show that the EMD can automatically detect and isolate tremulous and voluntary movements from experimental signals collected from 31 patients with different conditions. Our results also suggest that the tremor may be described by a new class of mathematical functions defined in the HA framework. In a further study, the HS was employed for visualization of the energy activities of signals. This tool introduces the concept of instantaneous frequency in the field of tremor. In addition, it could provide, in a time-frequency-energy plot, a clear visualization of local activities of tremor energy over the time. The HA demonstrated to be very useful to perform objective measurements of any kind of tremor and can therefore be used to perform functional assessment.

Original languageEnglish (US)
Pages (from-to)992-996
Number of pages5
JournalIFMBE Proceedings
Volume14
Issue number1
StatePublished - 2007
Event10th World Congress on Medical Physics and Biomedical Engineering, WC 2006 - Seoul, Korea, Republic of
Duration: Aug 27 2006Sep 1 2006

Keywords

  • Empirical mode decomposition
  • Time-frequency analysis
  • Tremor

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering

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