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Gianluca Vernillo, Aldo Savoldelli, Barbara Pellegrini and Federico Schena

The current study aimed to show the validity of a portable motion sensor, the SenseWear Armband (SWA), for the estimation of energy expenditure during pole walking. Twenty healthy adults (mean ± SD: age 30.1 ± 7.2 year, body mass 66.1 ± 10.6 kg, height 172.4 ± 8.0 cm, BMI 22.1 ± 2.4 kg·m−2) wore the armband during randomized pole walking activities at a constant speed (1.25 m·s−1) and at seven grades (0%, ±5%, ±15% and ±25%). Estimates of total energy expenditure from the armband were compared with values derived from indirect calorimetry methodology (IC) using a 2–way mixed model ANOVA (Device × Slope), correlation analyses and Bland-Altman plots. Results revealed significant main effects for device, and slope (p < .025) as well as a significant interaction (p < .001). Significant differences between IC and SWA were observed for all conditions (p < .05). SWA generally underestimate the EE values during uphill PW by 0.04 kcal·kg−1·min−1 (p < .05). Whereas, a significant overestimation has been detected during flat and downhill PW by 0.01 and 0.03 kcal·kg−1·min−1 (p < .05), respectively. The Bland-Altman plots revealed bias of the armband compared with the indirect calorimetry at any condition examined. The present data suggest that the armband is not accurate to correctly detect and estimate the energy expenditure during pole walking activities. Therefore, the observed over- and under-estimations warrants more work to improve the ability of SWA to accurately measure EE for these activities.

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Laurent Mourot, Nicolas Fabre, Aldo Savoldelli and Federico Schena

To determine the most accurate method based on spectral analysis of heart-rate variability (SA-HRV) during an incremental and continuous maximal test involving the upper body, the authors tested 4 different methods to obtain the heart rate (HR) at the second ventilatory threshold (VT2). Sixteen ski mountaineers (mean ± SD; age 25 ± 3 y, height 177 ± 8 cm, mass 69 ± 10 kg) performed a roller-ski test on a treadmill. Respiratory variables and HR were continuously recorded, and the 4 SA-HRV methods were compared with the gas-exchange method through Bland and Altman analyses. The best method was the one based on a time-varying spectral analysis with high frequency ranging from 0.15 Hz to a cutoff point relative to the individual’s respiratory sinus arrhythmia. The HR values were significantly correlated (r 2 = .903), with a mean HR difference with the respiratory method of 0.1 ± 3.0 beats/min and low limits of agreements (around –6/+6 beats/min). The 3 other methods led to larger errors and lower agreements (up to 5 beats/min and around –23/+20 beats/min). It is possible to accurately determine VT2 with an HR monitor during an incremental test involving the upper body if the appropriate HRV method is used.

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Gianluca Vernillo, Aldo Savoldelli, Barbara Pellegrini and Federico Schena


Accurate assessments of physical activity and energy expenditure (EE) are needed to advance research on positive and negative graded walking.


To evaluate the validity of 2 SenseWear Armband monitors (Pro3 and the recently released Mini) during graded walking.


Twenty healthy adults wore both monitors during randomized walking activities on a motorized treadmill at 7 grades (0%, ±5%, ±15%, and ±25%). Estimates of total EE from the monitors were computed using different algorithms and compared with values derived from indirect calorimetry methodology using a 2-way mixed model ANOVA (Device × Condition), correlation analyses and Bland-Altman plots.


There was no significant difference in EE between the 2 armbands in any of the conditions examined. Significant main effects for device and condition, as well as a consistent bias, were observed during positive and negative graded walking with a greater over- and under-estimation at higher slope.


Both the armbands produced similar EE values and seem to be not accurate in estimation of EE during activities involving uphill and downhill walking. Additional work is needed to understand factors contributing to this discrepancy and to improve the ability of these monitors to accurately measure EE during graded walking.