No abstract

Since the 1980s, accelerometer-based activity monitors have been used by researchers to quantify physical activity. The technology of these monitors has continuously evolved. For example, changes have been made to monitor hardware (type of sensor [e.g., piezoelectric, piezoresistive, capacitive]) and output format (counts vs. raw signal). Commonly used activity monitors belong to the ActiGraph and the Actical families This article presents information on several electro-mechanical aspects of these commonly used activity monitors. The majority of the article focuses on the evolution of the ActiGraph activity monitor by describing the differences among the 7164, the GT1M, and the GT3X models. This is followed by brief descriptions of the influences of device firmware and monitor calibration status. We also describe the Actical, but the discussion is short because this device has not undergone any major changes since it was first introduced. This paper may help researchers gain a better understanding of the functioning of activity monitors. For example, a common misconception among physical activity researchers is that the ActiGraph GT1M and GT3X are piezoelectric sensor-based monitors. Thus, this information may also help researchers to describe these monitors more accurately in scientific publications.

Currently, researchers can use the Actigraph 7164 or one of three different versions of the Actigraph GT1M to objectively measure physical activity. Purpose To determine if differences exist between activity counts from the Actigraph 7164 and the three versions of the GT1M at given walking and running speeds. Methods Ten male participants (23.6 ± 2.7 yrs) completed treadmill walking and running at ten different speeds (3-minute stages) while wearing either the Actigraph 7164 and the latest GT1M (GT1M-V3) or GT1M version one (GT1M-V1) and GT1M version two (GT1M-V2). Participants walked at 3, 5, and at 7 km˙hr−1 followed by running at 8, 10, 12, 14, 16, 18, and 20 km˙hr−1. The accelerometers were worn on an elastic belt around the waist over the left and right hips. Testing was performed on different days using a counterbalanced within-subjects design to account for potential differences attributable to accelerometer placement. At each speed, a one-way repeated measures ANOVA was used to examine differences between activity counts in counts˙min−1(cpm). Post-hoc pairwise comparisons with Bonferroni adjustments were used where appropriate. Results There were no significant differences between activity counts at any given walking or running speed (p<0.05). At all running speeds, activity counts from the Actigraph 7164 and GT1M-V2 displayed the lowest and highest values, respectively. Output from all accelerometers peaked at 14 km˙hr−1 (mean range: 8974 ± 677 to 9412 ± 982 cpm) and then gradually declined at higher speeds. The mean difference score at peak output between the Actigraph 7164 and GT1M-V2 was 439 ± 565 cpm. Conclusions There were no statistically significant differences between outputs from all the accelerometers indicating that researchers can select any of the four Actigraph accelerometers to do research.

The additional PA energy expenditure from using the TMWS favorably influenced waist and hip circumferences and lipid and metabolic profiles in overweight and obese office-workers.

Technological and societal changes have impacted the types of physical activities performed by U.S. youth. These data are helpful in understanding the factors associated with the rise in obesity, and in proposing potential solutions.