Research that uses accelerometers to measure physical activity has expanded exponentially over the past decade. There were approximately 90 papers per year published in 2003 and 2004 compared with fewer than 10 per year in 1993 and 1994 (6). Since the beginning of the development and application of accelerometers for physical activity assessment, there has been a desire to translate the output data from the devices into information on caloric estimates of energy expenditure (5). This interest in using accelerometers to measure energy expenditure is apparent even in the naming of some accelerometer devices, such as the Caltrac and Actical. Accelerometer data, commonly expressed as the dimensionless unit,“counts,” are inherently neither meaningful nor interpretable. Translating counts into a quantitative estimate of caloric expenditure or the related categorical measure of time spent in moderate-or vigorous-intensity activity makes the data more useful for multiple applications. Translation of counts to caloric expenditure benefits epidemiological studies of disease and physical activity because energy expenditure is theorized to be physiologically related to mechanisms of diabetes, cancer, and other chronic conditions. Current public health guidelines for physical activity are expressed in terms of time spent above intensity criteria (7), so accelerometry is most useful for surveillance of adherence to these recommendations only if raw counts can be translated into time spent in moderate and vigorous activity. An indication of calories expended or minutes per day of moderate or vigorous activity has the potential to motivate behavioral change. These goals are linked because they all require conversion of counts into units of energy expended.

In general, the approach to translate accelerometer counts into energy expenditure has been to compare activity counts and oxygen consumption measured during performance of a series of activities that reflect activities of daily living. Some studies concentrated on ambulatory activities of walking and running, which represent the type of movement best captured by waist-worn accelerometers (4). Other studies included more activities with varying degrees of static or variable movement energy expenditure (eg, lifting, vacuuming, racquet sports) that more completely encompass activities of daily life (4). After the simultaneous counts and oxygen consumption are obtained, regression methods are applied to determine the relationship between the two measures, and an equation to predict energy expenditure from accelerometer counts and/or a count threshold for a particular intensity of activity is determined. In most studies, a single linear regression is the analytic approach.