Cookies Policy
X

This site uses cookies. By continuing to browse the site you are agreeing to our use of cookies.

I accept this policy

Find out more here

Analysis of pathological tremors using the autoregression model

No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.

Brill’s MyBook program is exclusively available on BrillOnline Books and Journals. Students and scholars affiliated with an institution that has purchased a Brill E-Book on the BrillOnline platform automatically have access to the MyBook option for the title(s) acquired by the Library. Brill MyBook is a print-on-demand paperback copy which is sold at a favorably uniform low price.

Access this article

+ Tax (if applicable)
Add to Favorites
You must be logged in to use this functionality

The usefulness of analysis of acceleration data using an autoregression model (AR) for differential diagnosis of Parkinson's disease and other diseases with tremors was investigated. The order of the AR model used in this study was 7, in accordance with Akaike's final prediction error criterion. The subjects included 19 patients with Parkinson's disease; 21 patients with essential tremor, which mainly appears in old people, as well as Parkinson's disease; and 13 healthy old people as a control group. The results of analysis of acceleration data showed that the first prediction coefficient, just as the main tremor frequency, was a useful parameter for differentiating patients in the Parkinson's disease patient group and essential tremor patient group. The seventh prediction coefficient was found to be a useful parameter for distinguishing pathological tremors observed in Parkinson's disease and essential tremor disease from physiological tremors observed in healthy people. Although the usefulness of other prediction coefficients for differential diagnosis of Parkinson's disease and other diseases with tremors has not yet been clarified, the results of this study showed that information obtained from AR model parameters in addition to information on main tremor frequency is useful for the diagnosis of Parkinson's disease.

10.1163/15685570152772487
/content/journals/10.1163/15685570152772487
dcterms_title,pub_keyword,dcterms_description,pub_author
6
3
Loading
Loading

Full text loading...

/content/journals/10.1163/15685570152772487
Loading

Data & Media loading...

http://brill.metastore.ingenta.com/content/journals/10.1163/15685570152772487
Loading

Article metrics loading...

/content/journals/10.1163/15685570152772487
2001-09-01
2016-12-09

Sign-in

Can't access your account?
  • Tools

  • Add to Favorites
  • Printable version
  • Email this page
  • Subscribe to ToC alert
  • Get permissions
  • Recommend to your library

    You must fill out fields marked with: *

    Librarian details
    Your details
    Why are you recommending this title?
    Select reason:
     
    Frontiers of Medical and Biological Engineering — Recommend this title to your library
  • Export citations
  • Key

  • Full access
  • Open Access
  • Partial/No accessInformation