Application of EMD as a novel technique for the study of tremor time series. Rocon, E; Pons; L, J; Andrade; a O; Nasuto; and J, S Conference proceedings : ‥. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, Suppl:6533--6, January, 2006.
Application of EMD as a novel technique for the study of tremor time series. [link]Paper  doi  abstract   bibtex   
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.
@article{ Rocon2006a,
  title = {{Application of EMD as a novel technique for the study of tremor time series.}},
  author = {Rocon, E and Pons, J L and Andrade, a O and Nasuto, S J},
  journal = {Conference proceedings : ‥. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference},
  year = {2006},
  month = {January},
  pages = {6533--6},
  volume = {Suppl},
  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.},
  doi = {10.1109/IEMBS.2006.260871},
  issn = {1557-170X},
  keywords = {Algorithms,Computer-Assisted,Humans,Signal Processing,Software,Tremor,Tremor: physiopathology},
  pmid = {17959445},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/17959445}
}
Downloads: 0