Literature DB >> 24777169

Accelerometer-based quantitative analysis of axial nocturnal movements differentiates patients with Parkinson's disease, but not high-risk individuals, from controls.

Maartje Louter1, Walter Maetzler2, Jos Prinzen3, Rob C van Lummel3, Markus Hobert2, Johan B A M Arends4, Bastiaan R Bloem5, Johannes Streffer6, Daniela Berg2, Sebastiaan Overeem1, Inga Liepelt-Scarfone2.   

Abstract

INTRODUCTION: There is a need for prodromal markers to diagnose Parkinson's disease (PD) as early as possible. Knowing that most patients with overt PD have abnormal nocturnal movement patterns, we hypothesised that such changes might occur already in non-PD individuals with a potentially high risk for future development of the disease.
METHODS: Eleven patients with early PD (Hoehn & Yahr stage ≤2.5), 13 healthy controls and 33 subjects with a high risk of developing PD (HR-PD) were investigated. HR-PD was defined by the occurrence of hyperechogenicity of the substantia nigra in combination with prodromal markers (eg, slight motor signs, olfactory dysfunction). A triaxial accelerometer was used to quantify nocturnal movements during two nights per study participant. Outcome measurements included mean acceleration, and qualitative axial movement parameters, such as duration and speed.
RESULTS: Mean acceleration of nocturnal movements was lower in patients with PD compared to controls. Frequency and speed of axial movements did not differ between patients with PD and controls, but mean size and duration were lower in PD. The HR-PD group did not significantly differ from the control group in any of the parameters analysed.
CONCLUSIONS: Compared with controls, patients with PD had an overall decreased mean acceleration, as well as smaller and shorter nocturnal axial movements. These changes did not occur in our potential HR-PD individuals, suggesting that relevant axial movement alterations during sleep have either not developed or cannot be detected by the means applied in this at-risk cohort. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Entities:  

Keywords:  MOVEMENT DISORDERS; PARKINSON'S DISEASE; SLEEP

Mesh:

Substances:

Year:  2014        PMID: 24777169     DOI: 10.1136/jnnp-2013-306851

Source DB:  PubMed          Journal:  J Neurol Neurosurg Psychiatry        ISSN: 0022-3050            Impact factor:   10.154


  9 in total

Review 1.  Wearable sensor-based objective assessment of motor symptoms in Parkinson's disease.

Authors:  Christiana Ossig; Angelo Antonini; Carsten Buhmann; Joseph Classen; Ilona Csoti; Björn Falkenburger; Michael Schwarz; Jürgen Winkler; Alexander Storch
Journal:  J Neural Transm (Vienna)       Date:  2015-08-08       Impact factor: 3.575

2.  Effects of Levodopa on quality of sleep and nocturnal movements in Parkinson's Disease.

Authors:  Eva Schaeffer; Thomas Vaterrodt; Laura Zaunbrecher; Inga Liepelt-Scarfone; Kirsten Emmert; Benjamin Roeben; Morad Elshehabi; Clint Hansen; Sara Becker; Susanne Nussbaum; Jan-Hinrich Busch; Matthis Synofzik; Daniela Berg; Walter Maetzler
Journal:  J Neurol       Date:  2021-02-05       Impact factor: 4.849

3.  Instrumented functional reach test differentiates individuals at high risk for Parkinson's disease from controls.

Authors:  Sandra E Hasmann; Daniela Berg; Markus A Hobert; David Weiss; Ulrich Lindemann; Johannes Streffer; Inga Liepelt-Scarfone; Walter Maetzler
Journal:  Front Aging Neurosci       Date:  2014-10-24       Impact factor: 5.750

4.  Unraveling the Relationship between Motor Symptoms, Affective States and Contextual Factors in Parkinson's Disease: A Feasibility Study of the Experience Sampling Method.

Authors:  Martijn P G Broen; Vera A M Marsman; Mark L Kuijf; Robert J Van Oostenbrugge; Jim van Os; Albert F G Leentjens
Journal:  PLoS One       Date:  2016-03-10       Impact factor: 3.240

Review 5.  Mobility Deficits Assessed With Mobile Technology: What Can We Learn From Brain Iron-Altered Animal Models?

Authors:  Franziska Hopfner; Markus A Hobert; Corina Maetzler; Clint Hansen; Minh Hoang Pham; Caroline Moreau; Daniela Berg; David Devos; Walter Maetzler
Journal:  Front Neurol       Date:  2019-08-08       Impact factor: 4.003

6.  Technological evaluation of strategies to get out of bed by people with Parkinson's disease: Insights from multisite wearable sensors.

Authors:  Jirada Sringean; Chusak Thanawattano; Roongroj Bhidayasiri
Journal:  Front Med Technol       Date:  2022-08-25

Review 7.  A Viewpoint on Wearable Technology-Enabled Measurement of Wellbeing and Health-Related Quality of Life in Parkinson's Disease.

Authors:  Janet M T van Uem; Tom Isaacs; Alan Lewin; Eros Bresolin; Dina Salkovic; Alberto J Espay; Helen Matthews; Walter Maetzler
Journal:  J Parkinsons Dis       Date:  2016-03-10       Impact factor: 5.568

Review 8.  Shedding Light on Nocturnal Movements in Parkinson's Disease: Evidence from Wearable Technologies.

Authors:  Alessandro Zampogna; Alessandro Manoni; Francesco Asci; Claudio Liguori; Fernanda Irrera; Antonio Suppa
Journal:  Sensors (Basel)       Date:  2020-09-10       Impact factor: 3.576

Review 9.  The Home-Based Sleep Laboratory.

Authors:  Yael Hanein; Anat Mirelman
Journal:  J Parkinsons Dis       Date:  2021       Impact factor: 5.568

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.