title: Simultaneous heart rate-motion sensor technique to estimate energy expenditure.
abstract: OBJECTIVE
  Heart rate (HR) and motion sensors represent promising tools for physical activity (PA) assessment, as each provides an estimate of energy expenditure (EE). Although each has inherent limitations, the simultaneous use of HR and motion sensors may increase the accuracy of EE estimates. The primary purpose of this study was to establish the accuracy of predicting EE from the simultaneous HR-motion sensor technique. In addition, the accuracy of EE estimated by the simultaneous HR-motion sensor technique was compared to that of HR and motion sensors used independently.
  
  
  METHODS
  Thirty participants (16 men: age, 33.1 +/- 12.2 yr; BMI, 26.1 +/- 0.7 kg.m(-2); and 14 women: age, 31.9 +/- 13.1 yr; BMI, 27.2 +/- 1.1 kg.m(-2) (mean +/- SD)) performed arm and leg work in the laboratory for the purpose of developing individualized HR-VO2 regression equations. Participants then performed physical tasks in a field setting for 15 min each. CSA accelerometers placed on the arm and leg were to discriminate between upper and lower body movement, and HR was then used to predict EE (METs) from the corresponding arm or leg laboratory regression equation. A hip-mounted CSA accelerometer and Yamax pedometer were also used to predict EE. Predicted values (METs) were compared to measured values (METs), obtained via a portable metabolic measurement system (Cosmed K4b(2)).
  
  
  RESULTS
  The Yamax pedometer and the CSA accelerometer on the hip significantly underestimated the energy cost of selected physical activities, whereas HR alone significantly overestimated the energy cost of selected physical activities. The simultaneous HR-motion sensor technique showed the strongest relationship with VO(2) (R(2) = 0.81) and did not significantly over- or underpredict the energy cost (P = 0.341).
  
  
  CONCLUSIONS
  The simultaneous HR-motion sensor technique is a good predictor of EE during selected lifestyle activities, and allows researchers to more accurately quantify free-living PA.
authors.affiliation: Department of Exercise Science and Sport Management, University of Tennessee, Knoxville, TN 37996-2700, USA. sjstra3@uky.edu
authors.forename: S J
authors.initials: SJ
authors.lastname: Strath
authors.forename: D R
authors.initials: DR
authors.lastname: Bassett
authors.forename: A M
authors.initials: AM
authors.lastname: Swartz
authors.forename: D L
authors.initials: DL
authors.lastname: Thompson
mesh_terms: D000203:Activities of Daily Living; D000328:Adult; D004734:Energy Metabolism / Q000502:physiology*; D005080:Exercise Test; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008019:Life Style; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation / Q000379:methods*; D009068:Movement / Q000502:physiology*; D005082:Physical Exertion / Q000502:physiology*; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity