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Gabriel Felipe Arantes Bertochi; Jeffer Eidi Sasaki – Measurement in Physical Education and Exercise Science, 2025
This study compared the weekly training load (TL) variation across different measures. Fifty-two runners reported their heart rate and distance ran for each training session during four weeks of training. Heart rate measures were used to calculate the weekly TRaining IMPulse (W-TRIMP), whereas the distance ran was used to calculate the weekly…
Descriptors: Physical Education, Physical Activities, Athletics, Athletes
Hirsch, Katie R.; Blue, Malia N. M.; Smith-Ryan, Abbie E. – Measurement in Physical Education and Exercise Science, 2023
Impedance (Z), resistance (R), reactance (Xc), and phase angle (PhA) are sensitive to shifts in fluid between intra- and extracellular compartments, as would occur with nutrient uptake into skeletal muscle, but remains largely unexplored. To explore the sensitivity of whole-body and segmental (arms, legs, trunk) bioimpedance to acute feeding, 27…
Descriptors: Nutrition, Biochemistry, Metabolism, Young Adults
da Cruz, Carlos Janssen Gomes; Porto, Luiz Guilherme Grossi; Molina, Guilherme Eckhardt – Measurement in Physical Education and Exercise Science, 2022
The heart rate variability threshold (HRVT) is a useful and inexpensive alternative to estimate the ventilatory threshold (VT). However, its validity in women remains underexplored. We investigated the agreement between HRVT and VT in young women and the influence of cardiac parasympathetic status and cardiorespiratory fitness (CRF). Sixty-one…
Descriptors: Physical Fitness, Females, Young Adults, Measurement
Merrigan, Justin J.; Stovall, J. Hannah; Stone, Jason D.; Stephenson, Mark; Finomore, Victor S.; Hagen, Joshua A. – Measurement in Physical Education and Exercise Science, 2023
Heart rate samples (n = 4500-8000) from wearables were compared to electrocardiography during a steady-state ruck (Ruck-S), maximal effort ruck (Ruck-M), submaximal cycle (Cycle), and Tabata Circuit. One device was worn at each location (wrist: Polar Grit-X, Garmin Fenix 6; chest-straps: Polar H10, Garmin HRM-Pro; armband: Polar Verity).…
Descriptors: Measurement Equipment, Exercise Physiology, Training, Metabolism
Markwell, Logan T.; Nolan, Russel; Brown, Blake; Makaruk, Hubert; Porter, Jared M. – Measurement in Physical Education and Exercise Science, 2022
Subtle instructional changes that direct attentional focus can lead to changes in performance, potentially hindering a fitness assessment. An external attentional focus has been found to improve motor performance, however less is known about instructional effects on performance and the physiological response during an isometric endurance test. To…
Descriptors: Attention, Physical Fitness, Testing, Exercise Physiology
Crotty, Nora May; Boland, Marie; Mahony, Nick; Donne, Bernard; Fleming, Neil – Measurement in Physical Education and Exercise Science, 2021
This study evaluated the reliability of the portable Lactate Pro 2 analyzer (LP2), and its validity compared to a laboratory-based analyzer, YSI 1500 Sport (YSI). Blood samples (n = 258) were collected during 44 graded incremental rowing tests, with data from 17 tests used to quantify load, heart rate, and oxygen consumption at lactate threshold.…
Descriptors: Reliability, Validity, Measurement Equipment, Exercise
Krkeljas, Zarko; Engelbrecht, Louise; Terblanche, Elmarie – Measurement in Physical Education and Exercise Science, 2019
Accurate assessment of resting metabolic rate (RMR) is necessary for calorie-based recommendations in diet and exercise training interventions. BodyMetrix™ is an ultrasound-based device that provides an estimate of RMR based on body composition, but has not been proven valid or reliable. Therefore, we evaluated the agreement between Katch-McArdle…
Descriptors: Foreign Countries, Adults, Measurement Techniques, Metabolism
Matthews, Evan L.; Horvat, Fiona M.; Phillips, David A. – Measurement in Physical Education and Exercise Science, 2022
The YMCA step test uses a prescribed step height which is difficult in a telehealth setting. Examine a modification of the YMCA step test allowing for the use of preexisting in-home objects of variable height as the "step" in a virtual environment. Young healthy participants (n = 40) performed step tests with a small and large object of…
Descriptors: Physical Fitness, Metabolism, Tests, Measurement
Sacko, Ryan S.; Brazendale, Keith; Brian, Ali; McIver, Kerry; Nesbitt, Danielle; Pfeifer, Craig; Stodden, David F. – Measurement in Physical Education and Exercise Science, 2019
This study compared the energy expenditure (EE) levels during object projection skill performance (OPSP) as assessed by indirect calorimetry and accelerometry. Thirty-four adults (female n = 18) aged 18-30 (23.5 ± 2.5 years) performed three, 9-min sessions of kicking, over-arm throwing, and striking performed at 6-, 12-, and 30-sec intervals. EE…
Descriptors: Young Adults, Physical Activities, Measurement Techniques, Physical Activity Level
O'Brien, Myles W.; Johns, Jarrett A.; Fowles, Jonathon R.; Kimmerly, Derek S. – Measurement in Physical Education and Exercise Science, 2020
The activPAL is a widely-used measure of sedentary time but few studies have evaluated its ability to estimate physical activity intensity. This study determined the accuracy of the algorithm used by the activPAL to predict metabolic equivalents (METs) from cadence and a curvilinear cadence-METs equation individualized for height. Thirty-six…
Descriptors: Validity, Physical Activity Level, Accuracy, Metabolism
DeHondt, Benjamin G.; Madi, Samar A.; Drignei, Dorin; Buchan, Duncan S.; Brown, Elise C. – Measurement in Physical Education and Exercise Science, 2023
Identification of cardiometabolic risk (CMR) in U.S. younger population by assessing muscular strength via handgrip (HG) dynamometry may aid in prevention efforts. Currently, no nationally representative HG cut-points are available for identifying increased CMR in U.S. adolescents or young adults. In this study, we propose normalized grip strength…
Descriptors: Muscular Strength, Adolescents, Young Adults, Screening Tests
Mangione, Kathleen K.; Macropol, Kathy; Jia, Yanxia; Tevald, Michael; Harris, Shane; Wolff, Edward; Craik, Rebecca – Measurement in Physical Education and Exercise Science, 2018
Heart rate (HR) by time curves could be useful as a measure of treatment fidelity (TF). The purposes were to describe the frequency of common recording irregularities (e.g. errors) observed during exercise, validate a process to correct those errors, and determine whether there is a clinically meaningful benefit to data correction. In total, 1895…
Descriptors: Exercise, Older Adults, Metabolism, Injuries
Bonafiglia, Jacob T.; Sawula, Laura J.; Gurd, Brendon J. – Measurement in Physical Education and Exercise Science, 2018
The purpose of this study was to determine if the counting talk test can be used to discern whether an individual is exercising above or at/below maximal lactate steady state. Twenty-two participants completed VO[subscript 2]peak and counting talk test incremental step tests followed by an endurance test at 65% of work rate at VO[subscript 2]peak…
Descriptors: Metabolism, Exercise, Tests, Physical Fitness
Montoye, Alexander H. K.; Conger, Scott A.; Connolly, Christopher P.; Imboden, Mary T.; Nelson, M. Benjamin; Bock, Josh M.; Kaminsky, Leonard A. – Measurement in Physical Education and Exercise Science, 2017
This study compared accuracy of energy expenditure (EE) prediction models from accelerometer data collected in structured and simulated free-living settings. Twenty-four adults (mean age 45.8 years, 50% female) performed two sessions of 11 to 21 activities, wearing four ActiGraph GT9X Link activity monitors (right hip, ankle, both wrists) and a…
Descriptors: Validity, Electronic Equipment, Prediction, Physical Activity Level
Montoye, Alexander H. K.; Mitrzyk, Joe R.; Molesky, Monroe J. – Measurement in Physical Education and Exercise Science, 2017
The purpose of the current study was to determine the accuracy of the Fitbit Charge HR and Hexoskin smart shirt. Participants (n = 32, age: 23.5 ± 1.3 years) wore a Fitbit and Hexoskin while performing 14 activities in a laboratory and on a track (lying, sitting, standing, walking various speeds and inclines, jogging, and cycling). Steps, kcals,…
Descriptors: Measurement Equipment, Physical Activity Level, Measures (Individuals), Exercise Physiology