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  • Author: Gianluca Vernillo x
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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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Gianluca Vernillo, Aldo Savoldelli, Barbara Pellegrini and Federico Schena

Background:

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

Purpose:

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

Methods:

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.

Results:

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.

Conclusions:

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.

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Gianluca Vernillo, Alfredo Brighenti, Eloisa Limonta, Pietro Trabucchi, Davide Malatesta, Grégoire P. Millet and Federico Schena

Purpose:

To quantify changes in skeletal-muscle oxygenation and pulmonary O2 uptake (V̇O2) after an extreme ultratrail running bout.

Methods:

Before (PRE) and after (POST) the race (330-km, 24000 D±), profiles of vastus lateralis muscle oxygenation (ie, oxyhemoglobin [O2Hb], deoxyhemoglobin [HHb], and tissue oxygenation index [TOI]) and V̇O2 were determined in 14 athletes (EXP) and 12 control adults (CON) during two 4-min constant-load cycling bouts at power outputs of 1 (p1) and 1.5 (p1.5) W/kg performed in randomized order.

Results:

At POST, normalized [HHb] values increased (p1, +38.0%; p1.5, +27.9%; P < .05), while normalized [O2Hb] (p1, –20.4%; p1.5, –14.4%; P < .05) and TOI (p1, –17.0%; p1.5, –17.7%; P < .05) decreased in EXP. V̇O2 values were similar (P > 0.05). An “overshoot“ in normalized [HHb]:V̇O2 was observed, although the increase was significant only during p1.5 (+58.7%, P = .003). No difference in the aforementioned variables was noted in CON (P > .05).

Conclusions:

The concentric and, particularly, the eccentric loads characterizing this extreme ultratrail-running bout may have led to variations in muscle structure and function, increasing the local muscle deoxygenation profile and the imbalance between O2 delivery to working muscles and muscle O2 consumption. This highlights the importance of incorporating graded training, particularly downhill bouts, to reduce the negative influence of concentric and severe eccentric loads to the microcirculatory function and to enhance the ability of runners to sustain such loading.

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Martina A. Maggioni, Matteo Bonato, Alexander Stahn, Antonio La Torre, Luca Agnello, Gianluca Vernillo, Carlo Castagna and Giampiero Merati

Purpose: To investigate the effects of ball drills and repeated-sprint-ability training during the regular season in basketball players. Methods: A total of 30 players were randomized into 3 groups: ball-drills training (BDT, n = 12, 4 × 4 min, 3 vs 3 with 3-min passive recovery), repeated-sprint-ability training (RSAT, n = 9, 3 × 6 × 20-m shuttle running with 20-s and 4-min recovery), and general basketball training (n = 9, basketball technical/tactical exercises), as control group. Players were tested before and after 8 wk of training using the following tests: V˙O2max, squat jump, countermovement jump, Yo-Yo Intermittent Recovery Test Level 1 (YIRT1), agility T test, line-drill test, 5-/10-/20-m sprints, and blood lactate concentration. A custom-developed survey was used to analyze players’ technical skills. Results: After training, significant improvements were seen in YIRT1 (BDT P = .014, effect size [ES] ± 90% CI = 0.8 ± 0.3; RSAT P = .022, ES ± 90% CI = 0.7 ± 0.3), the agility T test (BDT P = .018, ES ± 90% CI = 0.7 ± 0.5; RSAT P = .037, ES ± 90% CI = 0.7 ± 0.5), and the line-drill test (BDT P = .010, ES ± 90% CI = 0.3 ± 0.1; RSAT P < .0001, ES ± 90% CI = 0.4 ± 0.1). In the RSAT group, only 10-m sprint speeds (P = .039, ES ± 90% CI = 0.3 ± 0.2) and blood lactate concentration (P = .004, ES ± 90% CI = 0.8 ± 1.1) were improved. Finally, technical skills were increased in BDT regarding dribbling (P = .038, ES ± 90% CI = 0.8 ± 0.6), shooting (P = .036, ES ± 90% CI = 0.8 ± 0.8), passing (P = .034, ES ± 90% CI = 0.9 ± 0.3), rebounding (P = .023, ES ± 90% CI = 1.1 ± 0.3), defense (P = .042, ES ± 90% CI = 0.5 ± 0.5), and offense (P = .044, ES ± 90% CI = 0.4 ± 0.4) skills. Conclusions: BDT and RSAT are both effective in improving the physical performance of basketball players. BDT had also a positive impact on technical skills. Basketball strength and conditioning professionals should include BDT as a routine tool to improve technical skills and physical performance simultaneously throughout the regular training season.