Upright Bicycle and Treadmill Stress Echocardiography Techniques and Technical Hints for the Sonographer

Davis, Cris

doi:10.1016/s0894-7317(14)80129-6

Cited by 6 publications

(2 citation statements)

References 2 publications

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“…During the VO 2 max testing, the individual pedaled the bicycle at 60 revolutions per minute (rpm) against 25 W of resistance. At the start of each 2 min stage, the resistance was raised by 25 W [ 23 ]. The test was terminated when two of three requirements were met: a respiratory exchange ratio (RER) of ≥ 1.1 occurred, a heart rate (HR) within 10 beats or over their theoretical aged-predicted maximal HR (220—age) was reached, or an expression of Borg rate of perceived exertion (RPE) of ≥16/20 was achieved [ 24 ].…”

Section: Methodsmentioning

confidence: 99%

Oxygen Consumption (VO2) and Surface Electromyography (sEMG) during Moderate-Strength Training Exercises

Adeel

Chen

Lin

et al. 2022

IJERPH

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Oxygen consumption (VO2) during strength training can be predicted through surface electromyography (sEMG) of local muscles. This research aimed to determine relations between VO2 and sEMG of upper and lower body muscles to predict VO2 from sEMG during moderate-intensity strength training exercises. Of the 12 participants recruited, 11 were divided into two groups: untrained (n = 5; with no training experience) and trained (n = 6; with 2 months of training experience). On different days, each individual completed six training sessions. Each participant performed training sessions consisting of three types of dumbbell exercises: shoulder press, deadlift, and squat, while wearing a mask for indirect calorimetric measurements of VO2 using the Cortex Metalyzer 3B. sEMG measurements of the bilateral middle deltoid, lumbar erector spinae, quadriceps (rectus femoris), and hamstring (biceps femoris) muscles were recorded. The VO2 was predicted from sEMG root mean square (RMS) values of the investigated muscles during the exercise period using generalized estimating equation (GEE) modeling. The predicted models for the three types of exercises for the untrained vs. trained groups were shoulder press [QIC = 102, * p = 0.000 vs. QIC = 82, * p = 0.000], deadlift [QIC = 172, * p = 0.000 vs. QIC = 320, * p = 0.026], and squat [QIC = 76, * p = 0.000 vs. QIC = 348, * p = 0.001], respectively. It was observed that untrained vs. trained groups predicted GEE models [quasi-likelihood under an independence model criterion (QIC) = 368, p = 0.330 vs. QIC = 837, p = 0.058], respectively. The study obtained significant VO2 prediction models during shoulder press, deadlift, and squat exercises using the right and left middle deltoid, right and left lumbar erector spinae, left rectus femoris, and right and left biceps femoris sEMG RMS for the untrained and trained groups during moderate-intensity strength training exercises.

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Section: Methodsmentioning

confidence: 99%

Oxygen Consumption (VO2) and Surface Electromyography (sEMG) during Moderate-Strength Training Exercises

Adeel

Chen

Lin

et al. 2022

IJERPH

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show abstract

“…The incremental bicycle testing protocol was conducted when the participant pedaled the bicycle at approximately 60 revolutions per minute (rpm) against 25 watts of resistance. The resistance was increased by 25 watts at the beginning of each two-minute stage [13]. The test was stopped when two of three occurred; a respiratory exchange ratio (RER) ≥ 1.1, an HR within 10 beats or over their theoretical aged-predicted maximal HR (220-age), and an expression of RPE ≥ 16/20 [14].…”

Section: Methodsmentioning

confidence: 99%

Modeling of Metabolic Equivalents (METs) during Moderate Resistance Training Exercises

Adeel

Lai

et al. 2021

Applied Sciences

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Energy expenditure through metabolic equivalent (MET) prediction during resistance exercises in humans can be modeled by using cardiorespiratory parameters. In this study, we aimed to predict MET during six moderate-intensity resistance training sessions consisting of three different exercises. Eleven participants were recruited into two groups; an untrained (n = 5; with no resistance training experience) and a trained group (n = 6; with 2 months resistance training experience). Each participant completed six training sessions separated with a rest interval of 1–2 days. While wearing a mask for indirect calorimetric measurements using Cortex Metalyzer 3B, each participant performed training sessions consisting of three types of dumbbell exercises: shoulder press, deadlift, and squat. The metabolic equivalents (METs), respiratory exchange ratio (RER), heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), blood lactate (BL), and Borg rate of perceived exertion (RPE) were measured. The MET was predicted using generalized estimating equations (GEE) for repeated measure data collected during exercise and rest periods. It was observed that during exercise period, RER, HR, SBP, and BL for the training group (QIC = 187, 95% CI = −0.012~0.915, p = 0.000*~0.033*) while RER, HR, SBP, DBP, and RPE (QIC = 48, 95% CI = −0.024~0.422, p = 0.000*~0.002*) during resting period for untrained group significantly predicted MET for moderate-intensity interval resistance training. It is concluded that the cardiorespiratory variables are significantly related to MET. During exercise, RER and HR significantly predicted MET for both groups along with additional parameters of SBP and BL for the training group. While during the resting period, RER, HR, SBP, DBP, and RPE related significantly for untrained and BL for training group respectively.

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Performance of stress echocardiography

Marwick

2003

Stress Echocardiography

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Upright Bicycle and Treadmill Stress Echocardiography Techniques and Technical Hints for the Sonographer

Cited by 6 publications

References 2 publications

Oxygen Consumption (VO2) and Surface Electromyography (sEMG) during Moderate-Strength Training Exercises

Oxygen Consumption (VO2) and Surface Electromyography (sEMG) during Moderate-Strength Training Exercises

Modeling of Metabolic Equivalents (METs) during Moderate Resistance Training Exercises

Performance of stress echocardiography

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