Academic journal article Research Quarterly for Exercise and Sport

Predicting Activity Energy Expenditure Using the Actical[R] Activity Monitor

Academic journal article Research Quarterly for Exercise and Sport

Predicting Activity Energy Expenditure Using the Actical[R] Activity Monitor

Article excerpt

This study developed algorithms for predicting activity energy expenditure (AEE) in children (n = 24) and adults (n = 24) from the Actical[R] activity monitor. Each participant performed 10 activities (supine resting, three sitting, three house cleaning, and three locomotion) while wearing monitors on the ankle, hip, and wrist; AEE was computed from oxygen consumption. Regression analysis, used to create AEE prediction equations based on Actical[R] output, varied considerably for both children ([R.sup.2] =. 45-. 75; p <. 001) and adults ([R.sup.2] =. 14-. 85; p <. 008). Most of the resulting algorithms accurately predicted accumulated AEE and time within light, moderate, and vigorous intensity categories (p >. 05). The Actical[R] monitor may be useful for predicting AEE and time variables at the ankle, hip, or wrist locations.

Key words: exercise, locomotion, physical activity


Accurately estimating free-living energy expenditure (EE) using electronic monitoring devices is of interest to researchers and clinicians. Research validating the use of electronic monitoring devices has primarily focused on accelerometers, pedometers, and heart rate monitors. Using accelerometers (hereafter referred to as activity monitors), however, appears to be the most promising because of their small size, long-term data storage capabilities, and potential to assess the intensity, frequency, and duration domains of physical activities. For assessing whole-body EE, activity monitors placed at the hip along the belt line have provided valid estimates of EE in adults (Freedson, Melanson, & Sirard, 1998; Hendelman, Miller, Baggett, Debold, & Freedson, 2000; Swartz et al., 2000) and children (Janz 1994; Janz, Cassady, Barr, & Kelly, 1995; Puyau, Adolph, Vohra, & Butte, 2002; Trost et al., 1998). It has been suggested, however, that activity monitors placed at the hip cannot accurately detect the EE associated with upper body movements (Swartz et al., 2000). This capacity may be especially important for populations whose primary physical activity results from household and garden activities, occupational tasks (e.g., laborer versus office worker), or those with limited mobility (e.g., activity limited to wheelchairs). Despite the potential advantage for predicting EE from wrist-based monitors, few have attempted to validate alternatives to hip-placed monitors (Heil 2002; Leenders, Nelson, Sherman, 2003; Melanson & Freedson, 1995; Puyau et al., 2002; Swartz et al., 2000). Despite the lack of research, it seems reasonable to suggest that wrist and ankle accelerometer locations can provide some valuable information about time-based (e.g., time accumulated in moderate-to-vigorous intensity activity) or EE-based (e.g., daily activity energy expenditure) variables.

Complicating the issue of monitor placement is the technology underlying the use of activity monitors to measure and process acceleration. The motion-sensing mechanism for the most common commercially available monitors can be described as uniaxial (sensing motion in a single plane) or triaxial (sensing motion in all three planes), while a single company describes their monitor as omnidirectional (sensing motion primarily in a single plane and less sensitively in the other planes). The ability to sense motion in more than one plane should be an advantage for measuring complex human movements; thus, the triaxial or omnidirectional measurement mechanisms may be more appropriate for evaluating alternatives to hip-placed activity monitors.

Last, many of the published equations for predicting EE from activity monitor output in adults have been reported exclusively in units of metabolic equivalents (METs). The MET unit can be useful for direct comparisons with published compilations of MET intensities for physical activities (Ainsworth et al., 2000). These MET equations, however, have the practical limitation of forcing those interested in EE to convert METs into units of caloric expenditure (e. …

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