The effect of leg length and stride frequency on the reliability and validity of accelerometer data
| dc.contributor.advisor | Tremblay, Mark | en_US |
| dc.contributor.committeeMember | Hall, Peter A. | en_US |
| dc.contributor.committeeMember | Drinkwater, Donald T. | en_US |
| dc.contributor.committeeMember | Binsted, Gordon | en_US |
| dc.creator | Stone, Michelle Rolande | en_US |
| dc.date.accessioned | 2005-07-22T15:39:45Z | en_US |
| dc.date.accessioned | 2013-01-04T04:46:31Z | |
| dc.date.available | 2005-07-25T08:00:00Z | en_US |
| dc.date.available | 2013-01-04T04:46:31Z | |
| dc.date.created | 2005-07 | en_US |
| dc.date.issued | 2005-07-21 | en_US |
| dc.date.submitted | July 2005 | en_US |
| dc.description.abstract | Technological advances in physical activity measurement have increased the development and utilization of accelerometers and pedometers for assessing physical activity in controlled and free-living conditions. Individual differences in leg length, stride length and stride frequency may affect the reliability and validity of accelerometers in estimating energy expenditure. To address this theory, this thesis investigated the influence of leg length, stride length and stride frequency on accelerometer counts and energy expenditure using four accelerometers (AMP, Actical, MTI, and RT3) and one pedometer (Yamax). Eighty-six participants, age 8 to 40 (17.6 ± 8.0) years performed three ten-minute bouts of treadmill activity at self-selected speeds (4 to 12 km/h). Energy expenditure (kcal/min) was measured through expired gas analysis and used as the criterion standard to compare physical activity data from activity monitors. A 3 (models) x 2 (duplicates of each model) x 3 (speeds) x 7 (minutes) repeated measures ANOVA was used to assess intra-device, inter-device, and inter-model reliability. Coefficients of variation were calculated to compare within-device variation and between-device variation in accelerometer counts. Differences between measured and predicted energy expenditure were assessed across five height categories to determine the influence of leg length on the validity of accelerometer/pedometer data. Regression equations for each model were developed using mean activity counts/steps generated for each speed, adjusting for various predictor variables (i.e., age, weight, leg length). These were compared to model-specific equations to determine whether the addition of certain variables might explain more variance in energy expenditure. Leg length and stride frequency directly influenced variability in accelerometer data and thus predicted energy expenditure. At high speeds and stride frequencies counts began to level off in the Actical, however this did not occur in the other devices. Intra-device and inter-device variation in accelerometer counts was less than 10% and was lowest at very high speeds for the Actical, MTI, and RT3 (p | en_US |
| dc.identifier.uri | http://hdl.handle.net/10388/etd-07222005-153945 | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | leg length | en_US |
| dc.subject | pedometers | en_US |
| dc.subject | accelerometers | en_US |
| dc.subject | physical activity measurement | en_US |
| dc.subject | energy expenditure | en_US |
| dc.subject | stride frequency | en_US |
| dc.title | The effect of leg length and stride frequency on the reliability and validity of accelerometer data | en_US |
| dc.type.genre | Thesis | en_US |
| dc.type.material | text | en_US |
| thesis.degree.department | College of Kinesiology | en_US |
| thesis.degree.discipline | College of Kinesiology | en_US |
| thesis.degree.grantor | University of Saskatchewan | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Science (M.Sc.) | en_US |