Estimation of Oxygen Uptake during Fast Running Using Accelerometry and Heart Rate

Fudge, Barry W.; Wilson, John; Easton, Chris; Irwin, Laura; Clark, Jonathan E.; Haddow, Olivia; Kayser, Bengt; Pitsiladis, Yannis

doi:10.1249/01.mss.0000235884.71487.21

Cited by 80 publications

(95 citation statements)

References 28 publications

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“…While our results were consistent with the linear increase during walking speeds, we did not observe an improved plateau response in the GT1M monitors. The study by Fudge et al (8) did not include the study of sedentary and light physical activity, so differences in the lowest activity count regions could not be analyzed and remain an important area for future investigation.…”

Section: Discussionmentioning

confidence: 99%

“…To our knowledge, however, no researchers to date have performed sensor characterization on newer models of the ActiGraph, such as the 71256 (marketed 1999 -2005) and the GT1M (marketed 2005-present), although differences between these device generations have been reported in a human study (8), and these differences have been suggested as a potential source of monitor variability that should be explored in a mechanical setting (5). Cross-generational analyses could provide insight into variations in the device hardware across monitor generations, which could impact the predictions of physical activity intensity or energy expenditure (EE) using devices other than the 7164 monitors.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Comparing the performance of three generations of ActiGraph accelerometers

Rothney¹,

Apker²,

Song³

et al. 2008

Journal of Applied Physiology

155

141

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Comparing the performance of three generations of ActiGraph accelerometers

Rothney¹,

Apker²,

Song³

et al. 2008

Journal of Applied Physiology

155

141

View full text Add to dashboard Cite

show abstract

“…VO 2 ) by the 3DNX model version 2 during treadmill exercise. 15,16 The capability of 3DNX to predict energy expenditure in free-living adult and adolescent cohorts has also been examined using the doubly labelled water method as a criterion measure. Carter et al 17 reported that 35% of the variance in total energy expenditure was explained by the 3DNX output; this increased to 78% when combined with anthropometric variables.…”

Section: Introductionmentioning

confidence: 99%

Reliability and validity of the 3DNX accelerometer during mechanical and human treadmill exercise testing

Horner

Rayson²,

Bilzon

2011

Int J Obes

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Objective: This study aimed to assess the validity and reliability of the 3DNX triaxial accelerometer in a laboratory and mechanical setting. Methods: Experiment 1: A total of 10 units were fixed to a Multi-axis shaker table. A schedule comprising a range of accelerations was repeated on two occasions along each of the three measurement axes. Experiment 2: A total of 11 recreationally active individuals completed a treadmill protocol (4-20 km hr À1 ) on two occasions. Two 3DNX accelerometers were secured to the lower back, logging data every 5 s. Oxygen uptake was measured using the Douglas Bag technique. Reliability inter-and intra-units were assessed using a combination of limits of agreement (LoA), coefficient of variation (CV) and intra-class correlation coefficient (ICC). Validity was assessed using simple linear regression. All data are expressed in counts per 5 s (counts 5 s À1 ). Results: Experiment 1: CV intra ranged from 0.0 to 8.9% in all axes. The absolute bias ± 95% LoA values were all below four counts 5 s À1 . CV inter did not rise above 4.5%. ICCs were 1.0 for all stages in all axes. The relationship between 3DNX counts and acceleration yielded an R 2 value of 0.99 and a standard error of the estimate (SEE) of six counts 5 s À1 . Experiment 2: CV inter ranged from 7.7 to 16.0% for trial 1 and from 7.7 to 16.2% for trial 2. ICCs between units ranged from 0.95 to 1.00 for trial 1 and from 0.90 to 0.99 for trial 2. Mean ratio bias ± 95% LoA values for intra-unit and inter-unit reliability were À0.7% (P40.05)±12.4% and 0.4% (P40.05)±5.6%, respectively. The relationship between . VO 2 and 3DNX counts for walking and running was linear (R 2 ¼ 0.65, SEE ¼ 1.42 ml kg À1 min À1 ; R 2 ¼ 0.62, SEE ¼ 3.63 ml kg À1 min À1 ). Conclusion:The 3DNX accelerometer is a reliable and valid device for measuring acceleration in a mechanical setting and during human treadmill exercise.

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“…All of them by Cobos include a recording of heart rates by telemetry, a valid system of measurement [15][16][17]. It gives us information about heart response when performing exercises that express a huge variability of intensity [18] and, at the same time, it gives us an energetice information about the performed exercise [19].…”

mentioning

confidence: 99%

Beach Handball and Beach Volleyball as Means Leading to Increasing Physical Activity of Recreational Sportspeople—Pilot Study

Šafář

Weisser²,

Chadimova³

2015

JSS

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Abstract:The sample consisted of sixteen man of aged average 24.5 year, average height 181.9 cm and weight 80.4 kg. The average of static pulse rate was 56.4 beats min -1 . The average heart rate max was 189.7 ± 7.8 beats min -1 . For the calculation of HR max (maximal heart rate), a mathematical figure HR max = 207 -(0.7 × age) was used. Probands have participated on the same day on a tournament in beach and handball tournament. HR (heart rate) was monitored via Sport Tester Polar. The results were evaluated by Polar software. The data was statistically compiled with the use of arithmetic average and standard deviation. The players played three matches in beach volleyball on one set to 21 points (necessary difference of 2 points). One set lasted approximate 13.5 min. After a break, they went to play three matches in beach handball. The average HR during beach volleyball was 149.5 ± 14.1 beats min -1 and 164.3 ± 14.5 beats min -1 in beach handball. In beach volleyball, we also focused on players' intensity load differences 172 ± 14.1 beats min -1 and goalkeepers 156.5 ± 16.6 beats min -1. In the beach volleyball, players spend most of their playing time on the playing area in the zone intensity load 80%-90% HR max (36% playing time). In the beach handball, players spend most of their playing time on the playing area in the zone intensity load 90%-100% HR max (39% playing time).

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Estimation of Oxygen Uptake during Fast Running Using Accelerometry and Heart Rate

Cited by 80 publications

References 28 publications

Comparing the performance of three generations of ActiGraph accelerometers

Comparing the performance of three generations of ActiGraph accelerometers

Reliability and validity of the 3DNX accelerometer during mechanical and human treadmill exercise testing

Beach Handball and Beach Volleyball as Means Leading to Increasing Physical Activity of Recreational Sportspeople—Pilot Study

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