2013
DOI: 10.3233/jad-130272
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Detecting the Effect of Alzheimer's Disease on Everyday Motion Behavior

Abstract: Our findings suggest that changes of everyday behavior are detectable in accelerometric behavior protocols even in the absence of major clinical behavioral impairments in AD.

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Cited by 52 publications
(31 citation statements)
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“…A trained medical student placed the sensors on the dyads on the first day and would then remove them on the third day, allowing for continuous monitoring of the subjects. The novel algorithm was able to discern unlabeled Alzheimer’s patients from healthy control subjects 91% of the time; this coincides with a higher rate than the conventional Cohen-Mansfield Agitation Inventory [52]. The author’s state that the higher accuracy denoted in this study suggests that the spectral structure is associated with clinical diagnosis of AD.…”
Section: Introductionsupporting
confidence: 58%
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“…A trained medical student placed the sensors on the dyads on the first day and would then remove them on the third day, allowing for continuous monitoring of the subjects. The novel algorithm was able to discern unlabeled Alzheimer’s patients from healthy control subjects 91% of the time; this coincides with a higher rate than the conventional Cohen-Mansfield Agitation Inventory [52]. The author’s state that the higher accuracy denoted in this study suggests that the spectral structure is associated with clinical diagnosis of AD.…”
Section: Introductionsupporting
confidence: 58%
“…Pathologically, these patients undergo degeneration of the suprachiasmatic nucleus, which effects circadian pace makers, which lead to an impairment of temporal structure with motion behavior. Researchers from Computer Science and Electrical Engineering of Rostock University and the German Center for Neurodegenerative Diseases (DZNE) Rostock, placed three-axis accelerometers on the ankles of 23 dyads (n = 46) consisting of diagnosed Alzheimer’s patients and healthy control subjects [52]. The subjects were chosen from a sample of community dwelling individuals and were matched according to age, gender and education.…”
Section: Introductionmentioning
confidence: 99%
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“…The upcoming complementary use of hybrid motion sensors is an especially important methodological advancement evaluating the association between disrupted motor activity and behavioural symptoms in dementia [46]. Wrist-worn accelerometers, logging and analysing the periodicity of limb movements on the basis of activity counts, are usually used to investigate movement behaviour and circadian rhythm disruptions [52].…”
Section: Discussionmentioning
confidence: 99%
“…The analysis of circadian rhythms in motor behaviour will be conducted according to Witting et al [45] by calculating inter-daily stability, intra-daily variability and relative amplitude. Advanced time series analysis of the patients’ daily activity patterns will be developed in accordance with recent developments by Kirste et al [46]. Analysis of the patients’ characteristics and outcome criteria will be realised using SPSS (version 22) and Matlab (version R2014b).…”
Section: Methodsmentioning
confidence: 99%