Literature DB >> 7710652

Quantitative assessment of movement in Alzheimer's disease.

B R Ott1, S A Ellias, M C Lannon.   

Abstract

To determine whether bradykinesia in patients with Alzheimer's disease is different from the slowing of movement seen in normal aging, 25 patients with mild to moderately severe Alzheimer's disease and 25 normal controls, matched for age and sex, were studied. The measures of motor performance included two computerized tests of finger tapping, one test of point-to-point arm movements, and one test of gait cadence. Patients performed significantly more slowly than controls on all three types of motor speed measurements, with average decrements of 9% to 19%. Right index finger tapping, right arm point-to-point, and left arm point-to-point tests produced the most significant discrimination of patients from controls. One month test-retest reliability in patients was high for these measures. Bradykinesia measured by these tests was correlated with cognitive tests requiring concentration and executive functions, suggesting a relationship to frontal lobe disease. Bradykinesia in Alzheimer's disease differs quantitatively from the effects of normal aging on movement. Motor function can be reliably measured in Alzheimer's disease patients by simple and rapid tests of tapping speed, which may be useful as functional parameters in studying disease progression and response to pharmacologic intervention.

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Mesh:

Year:  1995        PMID: 7710652

Source DB:  PubMed          Journal:  J Geriatr Psychiatry Neurol        ISSN: 0891-9887            Impact factor:   2.680


  11 in total

1.  Measuring motor speed through typing: a surrogate for the finger tapping test.

Authors:  Daniel Austin; Holly Jimison; Tamara Hayes; Nora Mattek; Jeffrey Kaye; Misha Pavel
Journal:  Behav Res Methods       Date:  2011-12

2.  Peripheral reaching in Alzheimer's disease and mild cognitive impairment.

Authors:  Alexandra G Mitchell; Stephanie Rossit; Suvankar Pal; Michael Hornberger; Annie Warman; Elise Kenning; Laura Williamson; Rebecca Shapland; Robert D McIntosh
Journal:  Cortex       Date:  2022-01-31       Impact factor: 4.027

3.  Advanced analysis of finger-tapping performance: a preliminary study.

Authors:  Cağatay Barut; Erhan Kızıltan; Ethem Gelir; Fürüzan Köktürk
Journal:  Balkan Med J       Date:  2013-06-01       Impact factor: 2.021

4.  Quantitative assessment of finger tapping characteristics in mild cognitive impairment, Alzheimer's disease, and Parkinson's disease.

Authors:  David R Roalf; Petra Rupert; Dawn Mechanic-Hamilton; Laura Brennan; John E Duda; Daniel Weintraub; John Q Trojanowski; David Wolk; Paul J Moberg
Journal:  J Neurol       Date:  2018-04-04       Impact factor: 4.849

Review 5.  The role of higher-level cognitive function in gait: executive dysfunction contributes to fall risk in Alzheimer's disease.

Authors:  Pamela L Sheridan; Jeffrey M Hausdorff
Journal:  Dement Geriatr Cogn Disord       Date:  2007-07-04       Impact factor: 2.959

6.  Older women with dementia can perform fast alternating forearm movements and performance is correlated with tests of lower extremity function.

Authors:  Eva Bramell-Risberg; Gun-Britt Jarnlo; Sölve Elmståhl
Journal:  Clin Interv Aging       Date:  2013-02-15       Impact factor: 4.458

7.  Sensory and motor secondary symptoms as indicators of brain vulnerability.

Authors:  Nava Levit-Binnun; Michael Davidovitch; Yulia Golland
Journal:  J Neurodev Disord       Date:  2013-09-24       Impact factor: 4.025

8.  Quantification of Finger-Tapping Angle Based on Wearable Sensors.

Authors:  Milica Djurić-Jovičić; Nenad S Jovičić; Agnes Roby-Brami; Mirjana B Popović; Vladimir S Kostić; Antonije R Djordjević
Journal:  Sensors (Basel)       Date:  2017-01-25       Impact factor: 3.576

9.  Strategic Variations in Fitts' Task: Comparison of Healthy Older Adults and Cognitively Impaired Patients.

Authors:  Céline Poletti; Rita Sleimen-Malkoun; Leslie Marion Decker; Frédérique Retornaz; Patrick Lemaire; Jean-Jacques Temprado
Journal:  Front Aging Neurosci       Date:  2017-01-20       Impact factor: 5.750

10.  Visualizing and Evaluating Finger Movement Using Combined Acceleration and Contact-Force Sensors: A Proof-of-Concept Study.

Authors:  Hitomi Oigawa; Yoshiro Musha; Youhei Ishimine; Sumito Kinjo; Yuya Takesue; Hideyuki Negoro; Tomohiro Umeda
Journal:  Sensors (Basel)       Date:  2021-03-09       Impact factor: 3.576

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