Application of EMD as a novel technique for the study of tremor time series
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.
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Empirical mode decomposition (EMD) can be used to isolate tremor movements from non-oscillatory movements.
“Second, the empirical mode decomposition (EMD) can be used to isolate tremor movements from non oscillatory movements [74].”
From Neurological Tremor: Sensors, Signal Processing and Emerging Applications (2010) · cites this paper as [74]
Cites
Deuschl, G., Raethjen, J., Lindemann, M., & Krack, P. (2001) · Muscle & Nerve · doi:10.1002/mus.1063 · Cited by 508 · cited 3× · see citing works
“Although the disorder is not life-threatening, it can be responsible for functional disability and social embarrassment [2].”
BackgroundMethodCharacteristics of hand tremor time series
Timmer, J., Gantert, C., Deuschl, G., & Honerkamp, J. (1993) · Biological Cybernetics · doi:10.1007/bf00202568 · Cited by 112 · see citing works
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Neurological Tremor: Sensors, Signal Processing and Emerging Applications
Grimaldi, G., & Manto, M. (2010) · Sensors · doi:10.3390/s100201399 · Cited by 138 · see citing works
“Second, the empirical mode decomposition (EMD) can be used to isolate tremor movements from non oscillatory movements [74].”
Method
- Authors
- Rocon, E., Pons, J. L., Andrade, A. O., & Nasuto, S. J.
- Affiliations
- University of Reading (GB)
- Venue
- 2006 International Conference of the IEEE Engineering in Medicine and Biology Society
- Publisher
- IEEE
- Published
- 2006
- Volume
- Suppl
- Pages
- 6533-6536
- ISSN
- 2375-7477 (ISSN-L)
- OpenAlex
- W2147887049
- Cited by
- 19
- References
- 2
- Citations by year
- 2023: 1 · 2022: 1 · 2020: 1 · 2017: 3 · 2016: 1 · 2015: 1 · 2014: 3 · 2013: 1 · 2012: 1
- FWCI
- 2.67
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Keywords
- tremor, empirical mode decomposition, Hilbert spectrum, tremor detection, instantaneous frequency, functional assessment
- MeSH terms
- Algorithms, Humans, Signal Processing, Computer-Assisted, Software, Tremor
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