Dataset Information

Assessment of energy expenditure during high intensity cycling and running using a heart rate and activity monitor in young active adults.

ABSTRACT: OBJECTIVE:Although high intensity physical activities may represent a great proportion of the total energy expenditure in active people, only sparse studies have investigated the accuracy of wearable monitors to assess activity related energy expenditure (AEE) during high intensity exercises. Therefore, the purpose of the present study was to investigate the accuracy of the Actiheart, a light portable monitor estimating AEE based on heart rate (HR) and activity counts (ACT), during two popular activities (running and cycling) performed at high intensities. The benefit of an individual calibration of the HR-AEE relationship established during a preliminary maximal test was also evaluated. METHODS:AEE was estimated in eighteen active adults (4 women and 14 men; 25 ± 4 yr) with indirect calorimetry using a respiratory gas analysis system (reference method) and the Actiheart during 5-min running and cycling at 60, 75 and 85% of maximal oxygen uptake (VO2max) previously determined during a maximal test performed on a treadmill or cycle ergometer. For the Actiheart, AEE was estimated either using the group or individual calibrated equations available in the dedicated software, and their respective HR, ACT or combined HR/ACT algorithms. RESULTS:When the HR algorithm was used for cycling and the HR or HR/ACT algorithms for running, AEE measured by the Actiheart increased proportionally to exercise intensity from 60 to 85% VO2max (P<0.001). Compared to indirect calorimetry, the Actiheart group calibrated equations slightly to moderately underestimated (3 to 20%) AEE for the three exercise intensities (P<0.001). Accuracy of AEE estimation was greatly improved by individual calibration of the HR-AEE relationship (underestimation below 5% and intraclass correlation coefficient [ICC]: 0.79-0.93) compared to group calibration (ICC: 0.64-0.79). CONCLUSION:The Actiheart enables to assess AEE during high intensity running and cycling when the appropriate algorithm is applied. Since an underestimation was present for group calibration, an individual and sport-specific calibration should be performed when a high accuracy is required.

SUBMITTER: Klass M

PROVIDER: S-EPMC6837421 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Assessment of energy expenditure during high intensity cycling and running using a heart rate and activity monitor in young active adults.

Klass Malgorzata M Faoro Vitalie V Carpentier Alain A

PloS one 20191107 11

<h4>Objective</h4>Although high intensity physical activities may represent a great proportion of the total energy expenditure in active people, only sparse studies have investigated the accuracy of wearable monitors to assess activity related energy expenditure (AEE) during high intensity exercises. Therefore, the purpose of the present study was to investigate the accuracy of the Actiheart, a light portable monitor estimating AEE based on heart rate (HR) and activity counts (ACT), during two p ...[more]

PMID: 31697742

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Project description:IntroductionWrist-mounted motion sensors can quantify the volume and intensity of physical activities, but little is known about their long-term validity. Our aim was to validate a wrist motion sensor in estimating daily energy expenditure, including any change induced by long-term participation in endurance and strength training. Supplemental heart rate monitoring during weekly exercise was also investigated.MethodsA 13-day doubly labeled water (DLW) measurement of total energy expenditure (TEE) was performed twice in healthy male subjects: during two last weeks of a 12-week Control period (n = 15) and during two last weeks of a 12-week combined strength and aerobic Training period (n = 13). Resting energy expenditure was estimated using two equations: one with body weight and age, and another one with fat-free mass. TEE and activity induced energy expenditure (AEE) were determined from motion sensor alone, and from motions sensor combined with heart rate monitor, the latter being worn during exercise only.ResultsWhen body weight and age were used in the calculation of resting energy expenditure, the motion sensor data alone explained 78% and 62% of the variation in TEE assessed by DLW at the end of Control and Training periods, respectively, with a bias of +1.75 (p <.001) and +1.19 MJ/day (p = .002). When exercise heart rate data was added to the model, the combined wearable device approach explained 85% and 70% of the variation in TEE assessed by DLW with a bias of +1.89 and +1.75 MJ/day (p <.001 for both). While significant increases in TEE and AEE were detected by all methods as a result of participation in regular training, motion sensor approach underestimated the change measured by DLW: +1.13±0.66 by DLW, +0.59±0.69 (p = .004) by motion sensor, and +0.98±0.70 MJ/day by combination of motion sensor and heart rate. Use of fat-free mass in the estimation of resting energy expenditure removed the biases between the wearable device estimations and the golden standard reference method of TEE and demonstrated a training-induced increase in resting energy expenditure by +0.18±0.13 MJ/day (p <.001).ConclusionsWrist motion sensor combined with a heart rate monitor during exercise sessions, showed high agreement with the golden standard measurement of daily TEE and its change induced by participation in a long-term training protocol. The positive findings concerning the validity, especially the ability to follow-up the change associated with a lifestyle modification, can be considered significant because they partially determine the feasibility of wearable devices as quantifiers of health-related behavior.

Project description:BackgroundStandardized training prescriptions often result in large variation in training response with a substantial number of individuals that show little or no response at all. The present study examined whether the response in markers of cardiorespiratory fitness (CRF) to moderate intensity endurance training can be elevated by an increase in training intensity.MethodsThirty-one healthy, untrained participants (46 ± 8 years, BMI 25.4 ± 3.3 kg m-2 and [Formula: see text]O2max 34 ± 4 mL min-1 kg-1) trained for 10 weeks with moderate intensity (3 day week-1 for 50 min per session at 55% HRreserve). Hereafter, the allocation into two groups was performed by stratified randomization for age, gender and VO2max response. CON (continuous moderate intensity) trained for another 16 weeks at moderate intensity, INC (increased intensity) trained energy-equivalent for 8 weeks at 70% HRreserve and then performed high-intensity interval training (4 × 4) for another 8 weeks. Responders were identified as participants with VO2max increase above the technical measurement error.ResultsThere was a significant difference in [Formula: see text]O2max response between INC (3.4 ± 2.7 mL kg-1 min-1) and CON (0.4 ± 2.9 mL kg-1 min-1) after 26 weeks of training (P = 0.020). After 10 weeks of moderate training, in total 16 of 31 participants were classified as VO2max responders (52%). After another 16 weeks continuous moderate intensity training, no further increase of responders was observed in CON. In contrast, the energy equivalent training with increasing training intensity in INC significantly (P = 0.031) increased the number of responders to 13 of 15 (87%). The energy equivalent higher training intensities increased the rate of responders more effectively than continued moderate training intensities (P = 0.012).ConclusionHigh-intensity interval training increases the rate of response in VO2max to endurance training even when the total energy expenditure is held constant. Maintaining moderate endurance training intensities might not be the best choice to optimize training gains. Trial Registration German Clinical Trials Register, DRKS00031445, Registered 08 March 2023-Retrospectively registered, https://www.drks.de/DRKS00031445.

Dataset Information

Assessment of energy expenditure during high intensity cycling and running using a heart rate and activity monitor in young active adults.

Publications

Assessment of energy expenditure during high intensity cycling and running using a heart rate and activity monitor in young active adults.

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