Brage S, Ekelund U, Brage N, Hennings MA, Froberg K, Franks PW, Wareham NJ. Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity. J Appl Physiol 103: [682][683][684][685][686][687][688][689][690][691][692] 2007. First published April 26, 2007; doi:10.1152/japplphysiol.00092.2006.-Combining accelerometry with heart rate (HR) monitoring may improve precision of physical activity measurement. Considerable variation exists in the relationships between physical activity intensity (PAI) and HR and accelerometry, which may be reduced by individual calibration. However, individual calibration limits feasibility of these techniques in population studies, and less burdensome, yet valid, methods of calibration are required. We aimed to evaluate the precision of different individual calibration procedures against a reference calibration procedure: a ramped treadmill walking-running test with continuous measurement of PAI by indirect calorimetry in 26 women and 25 men [mean (SD): 35 (9) yr, 1.69 (0.10) m, 70 (14) kg]. Acceleration (along the longitudinal axis of the trunk) and HR were measured simultaneously. Alternative calibration procedures included treadmill testing without calorimetry, submaximal step and walk tests with and without calorimetry, and nonexercise calibration using sleeping HR and gender. Reference accelerometry and HR models explained Ͼ95% of the betweenindividual variance in PAI (P Ͻ 0.001). This fraction dropped to 73 and 81%, respectively, for accelerometry and HR models calibrated with treadmill tests without calorimetry.Step-test calibration captured 62-64% (accelerometry) and 68% (HR) of the variance between individuals. Corresponding values were 63-76% and 59 -61% for walk-test calibration. There was only little benefit of including calorimetry during step and walk calibration for HR models. Nonexercise calibration procedures explained 54% (accelerometry) and 30% (HR) of the between-individual variance. In conclusion, a substantial proportion of the between-individual variance in relationships between PAI, accelerometry, and HR is captured with simple calibration procedures, feasible for use in epidemiological studies. energy expenditure; monitoring; heart rate variability; accelerometry; movement sensor ACCURATE QUANTIFICATION OF habitual physical activity is important to characterize the relationships between physical activity and health outcomes, to determine the interaction between physical activity and genetic factors, to monitor temporal trends at the population level, and to assess compliance to lifestyle interventions (24,38,60).1 Of the available objective methods, heart rate (HR) monitoring has the advantage that, within an individual, HR displays a strong and relatively universal relationship with physical activity intensity (PAI) across different types of activity, at least at moderate to high intensities (55). However, because the accurate estimation of PAI via HR monitoring may require relatively resourcedemanding procedures for ind...