A new diagnostic test to distinguish tremulous Parkinson's disease from advanced essential tremor
Abstract
Background: Clinical distinction between advanced essential tremor and tremulous Parkinson's disease can be difficult. Methods: In selected power spectra of accelerometric postural tremor recordings on the more affected side of 41 patients with essential tremor and 39 patients with tremulous Parkinson's disease being indistinguishable by tremor frequency, peak power or number of harmonic peaks, waveform asymmetry (autocorrelation decay), and mean peak power of all harmonic peaks were computed. Cutoff for essential tremor–Parkinson's disease distinction was determined by receiver operating characteristics. Diagnostic yield was tested in 12 clinically unclear patients with monosymptomatic tremor, subsequently definitively diagnosed with essential tremor (n = 2) or Parkinson's disease (n = 10) by 123‐I FP‐CIT–single‐photon emission computed tomography, fluorodopa‐positron emission tomography, or clinical course. Results: By autocorrelation decay 64%, by mean harmonic peak power 94% (Parkinson's disease > essential tremor) of patients with a definite clinical diagnosis, and 11 of 12 clinically unclear patients were classified correctly. Conclusions: Mean harmonic power is a useful measure to separate clinically difficult cases of advanced essential tremor from tremulous Parkinson's disease. © 2011 Movement Disorder Society
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Although there is overlapping in the range of frequencies that PD and ET tremors exhibit, power spectrum analysis of accelerometer signals has proven to discriminate effectively between PD and ET.
“although there is overlapping in the range of frequencies that PD and ET tremors exhibit, power spectrum analysis of accelerometer signals has proven to discriminate effectively between PD and ET [3,11–14].”
From Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer (2017) · cites this paper as [11]
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The pathophysiology of essential tremor and parkinson's tremor
Helmich, R. C., Toni, I., Deuschl, G., & Bloem, B. R. (2013) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-013-0378-8 · Cited by 294 · see citing works
Self-citationSmart watch accelerometry for analysis and diagnosis of tremor
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Rest tremor revisited: Parkinson’s disease and other disorders
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- Authors
- Muthuraman, M., Hossen, A., Heute, U., Deuschl, G., & Raethjen, J.
- Affiliations
- Christian-Albrechts-Universität zu Kiel (DE)
- Sultan Qaboos University (OM)
- Corresponding author
- Raethjen, Jan
- Venue
- Movement Disorders
- Publisher
- Wiley
- Published
- 2011-04-25
- Volume
- 26
- Issue
- 8
- Pages
- 1548-1552
- ISSN
- 0885-3185 (ISSN-L)
- 1531-8257
- OpenAlex
- W2068800243
- Cited by
- 63
- References
- 2
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 3 · 2023: 8 · 2022: 9 · 2021: 4 · 2020: 4 · 2018: 2 · 2017: 5 · 2016: 3 · 2015: 4 · 2014: 4 · 2013: 6 · 2012: 2
- FWCI
- 2.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Movement Disorders (publishedVersion)
- PubMed (publishedVersion)
- OPUS (Augsburg University) (submittedVersion)
- Topics
- Health Sciences › Medicine › Neurology › Neurological disorders and treatments
- Health Sciences › Medicine › Neurology › Parkinson's Disease Mechanisms and Treatments
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Keywords
- essential tremor, Parkinson's disease, postural tremor, accelerometry, power spectrum, autocorrelation decay, tremor frequency, differential diagnosis, diagnostic thresholds
- MeSH terms
- Adult, Aged, Aged, 80 and over, Diagnostic Tests, Routine, Female, Humans, Male, Middle Aged, Parkinson Disease, Posture, ROC Curve, Severity of Illness Index, Spectrum Analysis, Essential Tremor
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