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Unobtrusive assessment of activity patterns associated with mild
cognitive impairment
Tamara L. Hayes
a,b,
*, Francena Abendroth
b,c
, Andre Adami
d
, Misha Pavel
a,b
,
Tracy A. Zitzelberger
b,c
, Jeffrey A. Kaye
a,b,c
a
Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
b
Oregon Center for Aging and Technology, Oregon Health & Science University, Portland, OR, USA
c
Department of Neurology, Oregon Health & Science University, Portland, OR, USA
d
Department of Computer Science, Universidade de Caxias do Sul, RS, Brazil
Abstract Background: Timely detection of early cognitive impairment is difficult. Measures taken in the
clinic reflect a single snapshot of performance that might be confounded by the increased variability
typical in aging and disease. We evaluated the use of continuous, long-term, and unobtrusive
in-home monitoring to assess neurologic function in healthy and cognitively impaired elders.
Methods: Fourteen older adults 65 years and older living independently in the community were
monitored in their homes by using an unobtrusive sensor system. Measures of walking speed and
amount of activity in the home were obtained. Wavelet analysis was used to examine variance in
activity at multiple time scales.
Results: More than 108,000 person-hours of continuous activity data were collected during periods
as long as 418 days (mean, 315 Ϯ 82 days). The coefficient of variation in the median walking speed
was twice as high in the mild cognitive impairment (MCI) group (0.147 Ϯ 0.074) as compared with
the healthy group (0.079 Ϯ 0.027; t
11
ϭ 2.266, P Ͻ .03). Furthermore, the 24-hour wavelet variance
was greater in the MCI group (MCI, 4.07 Ϯ 0.14; healthy elderly, 3.79 Ϯ 0.23; F ϭ 7.58, P Յ .008),
indicating that the day-to-day pattern of activity of subjects in the MCI group was more variable than
that of the cognitively healthy controls.
Conclusions: The results not only demonstrate the feasibility of these methods but also suggest
clear potential advantages to this new methodology. This approach might provide an improved
means of detecting the earliest transition to MCI compared with conventional episodic testing in a
clinic environment.
© 2008 The Alzheimer’s Association. All rights reserved.
Keywords: Assessment of cognitive disorders/dementia; MCI (mild cognitive impairment); Cognitive aging; Technology
and aging; In-home assessment
1. Background
Early detection of cognitive decline preceding the onset
of dementia or functional impairment is important for many
reasons [1,2]. Cognitive changes in the elderly might have
immediately remediable causes such as medication compli-
cations or unsuspected medical illnesses. Failure to recog-
nize some of these causes in a timely manner might lead to
irreversible damage. Mild cognitive decline can also be an
early indicator of dementia, and timely recognition of cog-
nitive impairment provides an opportunity to focus on strat-
egies for treatment, compensation, and coping [3,4] and
might allow an individual to maintain greater independence
than would otherwise be the case. In addition, early recog-
nition is an opportunity for those with irreversible decline to
proactively plan for their future and avoid being forced into
crisis management.
*Corresponding author: Tel.: 503-418-9315; Fax: 503-418-9311.
E-mail address: hayesta@ohsu.edu
Alzheimer’s & Dementia 4 (2008) 395– 405
1552-5260/08/$ – see front matter © 2008 The Alzheimer’s Association. All rights reserved.
doi:10.1016/j.jalz.2008.07.004