Skip to main content
. 2019 Aug 30;21(8):e12785. doi: 10.2196/12785

Table 2.

Summary of 6 studies that included data from dedicated wearable sensors: accelerometers and GPSa-based solutions (Group 2).

First author (year), country Technology description Study description: design; number and type of subjects (number living aloneb, if relevant) and setting; duration Cognitive status and number of participants; age; number of male and/or female participants Main results
Westerberg (2010), United States [27] Sleep monitoring with a wrist-worn activity sensor device Comparative observational study; 20 volunteers; 2 weeks 10 aMCIc patients (MMSEd=27.8), 10 controls (MMSE=29.3); mean age 71.1 and 72.5 years, respectively; 8 and 7 females, respectively Actigraphy parameters failed to reveal significant differences between groups.
Shoval (2011), Israel [28] Tracking using a location kit: a GPS with radio frequency identification Observational study; 41 community-dwelling participants; 28 days 13 healthy, 21 MCIe, 7 mild dementia (MMSE and CDRf NCg); mean age 72.9, 78.3, and 81.9 years, respectively; 54% female The spatial range of the mobility of elderly people with cognitive impairment is severely restricted, with most out-of-home time spent in close proximity.
Tung (2014), Canada [29] GPS-enabled mobile phone Observational comparative study; 52 older adults; 3 days 19 mild-to-moderate ADh (MMSE=23.1), 33 controls (MMSE NC); mean age 70.7 and 73.7 years, respectively; 40% and 64% female, respectively GPS-derived area, perimeter, and mean distance from home were significantly smaller in the AD group compared to controls.
Wettstein (2015), Germany and Israel [30] Mobility data: questionnaires and GPS receiver with a global system for mobile communications modem and a monitoring unit in the home Observational comparative study; 257 older adults; 4 weeks 35 mild AD (mean MMSE=24.1), 76 MCI (mean MMSE=27.0), 146 healthy persons (mean MMSE=28.6); age 74.1, 72.9, and 72.5 years, respectively; 49% female Questionnaire-based cognitively demanding activities showed a significant difference between MCI and cognitively healthy participants, and a significant difference between AD and cognitively healthy participants.
Takemoto (2015), United States [31] GPS and accelerometer Observational study; 279 older adults; 6 days MMSE NC; mean age 83 years; 71% female Number, distance, and minutes of pedestrian trips, as well as vehicle trips were not associated with cognitive functioning.
Mancini (2016), United States [32] Quality and quantity of turning during normal daily activities by wearing three inertial sensors (one on their belt and two on shoes) during the day Observational study; 35 elderly adults: 16 nonfallers, 12 one-time fallers, and 7 recurrent fallers; 7 days Nonfallers (MMSE=28.3), one-time fallers (MMSE=28.9), recurrent fallers (MMSE=28.0); age 83.9, 86.0, and 88.4 years, respectively; 66% female Visuospatial and memory function scores were associated with quality of turning.

aGPS: global positioning system.

bThe number of participants living alone is specified when the information is relevant; for example, for ambient sensors but not for wearables devices.

caMCI: amnestic MCI.

dMMSE: Mini Mental State Examination.

eMCI: mild cognitive impairment.

fCDR: Clinical Dementia Rating.

gNC: not communicated.

hAD: Alzheimer disease.