Estimating energy expenditure from raw accelerometry in three types of locomotion
| Autor: | Mirko Brandes, Viviane Hannöver, Soren Brage, Vincent T. van Hees |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Adult
Male Adolescent Physical Therapy Sports Therapy and Rehabilitation Accelerometer Young Adult Oxygen Consumption Germany Statistics Linear regression Accelerometry Humans Orthopedics and Sports Medicine Resting energy expenditure Child Mathematics Aged Aged 80 and over Oxygen analyzer Triaxial accelerometer Overground walking Middle Aged Energy expenditure Female Cycling Energy Metabolism Algorithms Locomotion |
| Zdroj: | Medicine and science in sports and exercise. 44(11) |
| ISSN: | 1530-0315 |
| Popis: | AB Purpose: Accuracy of estimating activity-related energy expenditure (AEE) from raw body acceleration may improve by using prediction equations that are specific for the type of activity. The current study aims to improve published equations by deriving an equation for overground walking and to evaluate whether overground cycling and stair walking require specific prediction equations. Methods: Participants (91 male/95 female, 8-81 yr old) were equipped with a triaxial accelerometer (DynaPort MiniMod; McRoberts BV, The Hague, The Netherlands) on their lower back. Total energy expenditure (TEE) was measured using a mobile oxygen analyzer (MetaMax 3b; Cortex Biophysik, Leipzig, Germany). Resting energy expenditure (REE) was measured for 30 min, following which a physical activity course was completed involving walking on level ground at slow (8 min), normal (8 min), and fast speed (3 min), stair walking (3 min), and cycling (8 min). AEE was calculated as TEE - REE, expressed in both absolute (kJ[middle dot]min-1) and relative (J[middle dot]min-1[middle dot]kg-1) units. Mixed linear regression analysis was used for developing regression equations for walking, stair walking, and cycling. Results: Acceleration contributed 76% and 93% (P < 0.001) to explained variance in walking AEE for absolute and relative AEE models, respectively. Age and gender improved estimation accuracy by |
| Databáze: | OpenAIRE |
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