Validating accelerometry as a measure of physical activity and energy expenditure in chronic stroke.
Accelerometers can objectively measure steps taken per day in individuals without gait deficits, but accelerometers also have the ability to estimate frequency, intensity, and duration of physical activity. However, thresholds to distinguish varying levels of activity intensity using the Actical brand accelerometer are standardized only for the general population and may underestimate intensity in stroke.



To derive Actical activity count thresholds specific to stroke disability for use in more accurately gauging time spent at differing activity levels.



Men (n = 18) and women (n = 10) with chronic hemiparetic gait (4 ± 2 years latency, 43% Caucasian, 56% African-American, ages of 47-83 years, BMI 19-48 kg/m2) participated in the study. Actical accelerometers were placed on the non-paretic hip to obtain accelerometry counts during eight activities of varying intensity: (1) watching TV; (2) seated stretching; (3) standing stretching; (4) floor sweeping; (5) stepping in place; (6) over-ground walking; (7) lower speed treadmill walking (1.0 mph at 4% incline); and (8) higher speed treadmill walking (2.0 mph at 4% incline). Simultaneous portable monitoring (Cosmed K4b2) enabled quantification of energy cost for each activity in metabolic equivalents (METs, or oxygen consumption in multiples of resting level). Measurements were obtained for 10 min of standard rest and 5 min during each of the eight activities.



Regression analysis yielded the following new stroke-specific Actical minimum thresholds: 125 counts per minute (cpm) for sedentary/light activity, 667 cpm for light/moderate activity, and 1546 cpm for moderate/vigorous activity.



Our revised cut points better reflect activity levels after stroke and suggest significantly lower thresholds relative to those observed for the general population of healthy individuals. We conclude that the standard, commonly applied Actical thresholds are inappropriate for this unique population.
a Research Service , Baltimore VA , Baltimore , MD , USA.|b Department of Medicine, Division of Gerontology and Geriatric Medicine , University of Maryland School of Medicine , Baltimore , MD , USA.
Monica C
MC
Serra
b Department of Medicine, Division of Gerontology and Geriatric Medicine , University of Maryland School of Medicine , Baltimore , MD , USA.
Elizabeth
E
Balraj
b Department of Medicine, Division of Gerontology and Geriatric Medicine , University of Maryland School of Medicine , Baltimore , MD , USA.
Beth L
BL
DiSanzo
a Research Service , Baltimore VA , Baltimore , MD , USA.|d Department of Neurology , University of Maryland School of Medicine , Baltimore , MD , USA.
Frederick M
FM
Ivey
c GRECC , Baltimore VA , Baltimore , MD , USA.|d Department of Neurology , University of Maryland School of Medicine , Baltimore , MD , USA.
Charlene E
CE
Hafer-Macko
e Department of Kinesiology , University of Maryland Eastern Shore , Princess Anne , MD , USA.
Margarita S
MS
Treuth
a Research Service , Baltimore VA , Baltimore , MD , USA.|b Department of Medicine, Division of Gerontology and Geriatric Medicine , University of Maryland School of Medicine , Baltimore , MD , USA.
Alice S
AS
Ryan
D015502:Absorptiometry, Photon; D061725:Accelerometry / Q000379:methods*; D000203:Activities of Daily Living; D000368:Aged; D000369:Aged, 80 and over; D001823:Body Composition / Q000502:physiology; D002151:Calorimetry; D002908:Chronic Disease; D004734:Energy Metabolism / Q000502:physiology*; D015444:Exercise / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010101:Oxygen Consumption / Q000502:physiology; D012044:Regression Analysis; D015203:Reproducibility of Results; D020521:Stroke / Q000503:physiopathology*
Accelerometry; Chronic stroke; Physical activity