Literature DB >> 15124730

An automatic method for scoring leg movements in polygraphic sleep recordings and its validity in comparison to visual scoring.

Thomas C Wetter1, Gerhard Dirlich, Jonathan Streit, Claudia Trenkwalder, Andreas Schuld, Thomas Pollmächer.   

Abstract

STUDY
OBJECTIVES: The study presents an automatic method for scoring leg movements in polysomnographic recordings and describes an empirical investigation of its validity.
DESIGN: Leg movements measured by means of the surface electromyogram activation of the right and left tibialis anterior muscle contained in 24 digitally recorded all-night polysomnograms were analyzed visually according to the American Sleep Disorders Association guidelines by 2 experienced raters and automatically scored using a newly developed electromyogram-based analytical method. Two visual scorings and the automatic scoring were compared in pairs using descriptive and confirmative statistical methods.
SETTING: N/A. PARTICIPANTS: All-night polysomnograms of adaptation nights at the sleep laboratory of 10 patients with idiopathic restless legs syndrome (RLS) according to the International RLS Study Group.
INTERVENTIONS: N/A. MEASUREMENTS AND
RESULTS: Agreement rates between the 2 well-trained scorers and the automatic method were comparable. Based on the first scorer's results (100%) 92.5% of the movements were detected by the second scorer and 94.3% by the automatic method. When the visual scorings were compared, the rate of false-positive and false-negative errors were 7% and 3%, respectively. Comparing both visual scorings with the results of the automatic scoring yielded false-positive and false-negative rates in the range from 3% to 8%.
CONCLUSIONS: The degree of accordance between the 2 visual scorings and between the visual and the automatic scorings were comparable. Therefore, this method is valid and may be used for the automatic detection of leg movements in future studies.

Entities:  

Mesh:

Year:  2004        PMID: 15124730     DOI: 10.1093/sleep/27.2.324

Source DB:  PubMed          Journal:  Sleep        ISSN: 0161-8105            Impact factor:   5.849


  9 in total

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Journal:  Med Biol Eng Comput       Date:  2016-02-13       Impact factor: 2.602

4.  Elevated estradiol plasma levels in women with restless legs during pregnancy.

Authors:  Andrea Dzaja; Renate Wehrle; Marike Lancel; Thomas Pollmächer
Journal:  Sleep       Date:  2009-02       Impact factor: 5.849

5.  A Data-Driven Analysis of the Rules Defining Bilateral Leg Movements during Sleep.

Authors:  Raffaele Ferri; Mauro Manconi; Francesco Rundo; Marco Zucconi; Debora Aricò; Oliviero Bruni; Luigi Ferini-Strambi; Stephany Fulda
Journal:  Sleep       Date:  2016-02-01       Impact factor: 5.849

6.  MATPLM1, A MATLAB script for scoring of periodic limb movements: preliminary validation with visual scoring.

Authors:  Andy S Huang; Patrick Skeba; Myung S Yang; Francis P Sgambati; Christopher J Earley; Richard P Allen
Journal:  Sleep Med       Date:  2015-04-24       Impact factor: 3.492

7.  Validation of a leg movements count and periodic leg movements analysis in a custom polysomnography system.

Authors:  Ambra Stefani; Anna Heidbreder; Heinz Hackner; Birgit Högl
Journal:  BMC Neurol       Date:  2017-02-23       Impact factor: 2.474

8.  Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring.

Authors:  Merel M van Gilst; Johannes P van Dijk; Roy Krijn; Bertram Hoondert; Pedro Fonseca; Ruud J G van Sloun; Bruno Arsenali; Nele Vandenbussche; Sigrid Pillen; Henning Maass; Leonie van den Heuvel; Reinder Haakma; Tim R Leufkens; Coen Lauwerijssen; Jan W M Bergmans; Dirk Pevernagie; Sebastiaan Overeem
Journal:  BMJ Open       Date:  2019-11-25       Impact factor: 2.692

9.  Design and validation of a periodic leg movement detector.

Authors:  Hyatt Moore; Eileen Leary; Seo-Young Lee; Oscar Carrillo; Robin Stubbs; Paul Peppard; Terry Young; Bernard Widrow; Emmanuel Mignot
Journal:  PLoS One       Date:  2014-12-09       Impact factor: 3.240

  9 in total

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