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1.
This study examined the accuracy of a new device (Caltrac) in estimating energy expenditure via acceleration measurements. Energy expenditure of 20 high school students during basketball class activity (average length = 37 min) was estimated using the Caltrac, heart rate recording, and video analysis. Heart rate recording and video analysis estimates of energy expenditure were determined from heart rate, caloric expenditure curves, and an activity rating scale, respectively. The following estimates of caloric expenditure (M +/- SD) were found: heart rate recording = 196 +/- 73 greater than Caltrac = 163 +/- 49 greater than film analysis = 123 +/- 30 kcal (p less than .05). Laboratory simulations of the basketball activity revealed that the Caltrac energy expenditure was not significantly different from the actual energy expenditure (p greater than .05). The heart rate recording and video analysis estimates of energy expenditure were significantly (p less than .05) higher and lower, respectively, than the actual energy expenditure. The Caltrac is a lightweight, low-cost device that provides a relatively accurate estimate of energy expenditure in free-ranging activities, such as basketball.  相似文献   

2.
ABSTRACT

Purpose: The purpose of this study was to evaluate the agreement of five commercially available accelerometers in estimating energy expenditure while performing an acute bout of high-intensity functional training (HIFT). Methods: Participants (n = 47; average age: 28.5 ± 11.6 years) consisted of recreationally active, healthy adults. Each participant completed a session of HIFT: a 15-minute workout consisting of 12 repetitions each of air-squats, sit-ups, push-ups, lunges, pull-ups, steps-ups, and high-knees; performed circuit-style by completing as many rounds as possible. During this session, each participant wore the Cosmed K4b2 portable metabolic analyzer (PMA) and five different accelerometers (ActiGraph GT3X, Nike Fuelband, Fitbit One, Fitbit Charge HR, and Jawbone UP Move). Results: Four of the five activity trackers reported lower (p < .05) total EE values compared to the PMA during the acute bout of HIFT. The waist-mounted device (ActiGraph, 182.55 ± 37.93 kcal) was not significantly different from, and most closely estimated caloric expenditure compared to the PMA (144.99 ± 37.13 kcal) (p = .056). A repeated-measures ANOVA showed that all activity trackers were significantly different from the reference measure (PMA) (p < .05). Systematic relative agreement between the activity trackers was calculated, exhibiting a significant ICC = 0.426 (F [46,230] = 5.446 [p < .05]). Conclusion: The wrist- and hip-mounted activity trackers did not accurately assess energy expenditure during HIFT exercise. With the exception of the ActiGraph GT3X, the remaining four activity trackers showed inaccurate estimates of the amount of kilocalories expended during the HIFT exercise bout compared to the PMA.  相似文献   

3.
Abstract

Energy turnover was assessed in two conditions of mixed ultra-endurance exercise. In Study 1, energy expenditure and intake were measured in nine males in a laboratory over 24 h. In Study 2, energy expenditure was assessed in six males during an 800-km Adventure race (mean race time 152.5 h). Individual correlations between heart rate and oxygen uptake ([Vdot]O2) were established during pre-tests when kayaking, cycling, and running. During exercise, energy expenditure was estimated from continuous heart rate recordings. Heart rate and [Vdot]O2 were measured regularly during fixed cycling work rates to correct energy expenditure for drift in oxygen pulse. Mean energy expenditure was 18,050 ± 2,390 kcal (750 ± 100 kcal · h?1) and 80,000 ± 18,000 kcal (500 ± 100 kcal · h?1) in Study 1 and Study 2 respectively, which is higher than previously reported. Energy intake in Study 1 was 8,450 ± 1,160 kcal, resulting in an energy deficit of 9,590 ± 770 kcal. Body mass decreased in Study 1 (?2.3 ± 0.8 kg) but was unchanged in Study 2. Fat mass decreased in Study 2 (?2.3 ± 1.5 kg). In Study 1, muscle glycogen content decreased by only 60%. Adventure racing requires a high energy expenditure, with large inter-individual variation. A large energy deficit is caused by inadequate energy intake, possibly due to suppressed appetite and gastrointestinal problems. The oxygen pulse, comparing start to 12 h of exercise and beyond, increased by 10% and 5% in Study 1 and Study 2 respectively. Hence, estimations of energy expenditure from heart rate recordings should be corrected according to this drift.  相似文献   

4.
In this study, the intensities of activity and movement patterns during men's basketball were investigated by videoing the movements and monitoring the heart rate and blood lactate responses of eight elite players during competition. The results are expressed according to ‘live time’, which is actual playing time, and ‘total time’, which includes live time as well as all stoppages in play. The mean (± s.d.) frequency of all activities was 997 ± 183, with a change in movement category every 2.0 s. A mean total of 105 ± 52 high‐intensity runs (mean duration 1.7 s) was recorded for each game, resulting in one high‐intensity run every 21 s during live time. Sixty percent of live time was spent engaged in low‐intensity activity, while 15% was spent in high‐intensity activity. The mean heart rate (HR) during live time was 169 ± 9 beats min‐l (89 ± 2% peak HR attained during laboratory testing); 75% of live time was spent with a HR response of greater than 85% peak HR. The mean blood lactate concentration was 6.8 ± 2.8 mM, indicating the involvement of glycolysis in the energy demands of basketball. It is concluded that the physiological requirements of men's basketball are high, placing considerable demands on the cardiovascular and metabolic capacities of players.  相似文献   

5.
Abstract

The purpose of this study was to examine the accuracy of the ePulse Personal Fitness Assistant, a forearm-worn device that provides measures of heart rate and estimates energy expenditure. Forty-six participants engaged in 4-minute periods of standing, 2.0 mph walking, 3.5 mph walking, 4.5 mph jogging, and 6.0 mph running. Heart rate and energy expenditure were simultaneously recorded at 60-second intervals using the ePulse, an electrocardiogram (EKG), and indirect calorimetry. The heart rates obtained from the ePulse were highly correlated (intraclass correlation coefficients [ICCs] ≥0.85) with those from the EKG during all conditions. The typical errors progressively increased with increasing exercise intensity but were <5 bpm only during rest and 2.0 mph. Energy expenditure from the ePulse was poorly correlated with indirect calorimetry (ICCs: 0.01–0.36) and the typical errors for energy expenditure ranged from 0.69–2.97 kcal · min?1, progressively increasing with exercise intensity. These data suggest that the ePulse Personal Fitness Assistant is a valid device for monitoring heart rate at rest and low-intensity exercise, but becomes less accurate as exercise intensity increases. However, it does not appear to be a valid device to estimate energy expenditure during exercise.  相似文献   

6.
Purpose: This study aimed to compare the energy expenditure and intensity of active video games to that of treadmill walking in children and adolescents. Method: Seventy-two boys and girls (aged 8–13 years) were recruited from local public schools. Energy expenditure and heart rate were measured during rest, during 3-km/hr, 4-km/hr, and 5-km/hr walks, and during active games (Adventure, Boxing I, Boxing II, and Dance). During walking and active games, we also assessed physical activity using an accelerometer. Results: The energy expenditure of the active games Adventure, Boxing I, Boxing II, and Dance was similar to that of treadmill walking at 5 km/hr in boys and girls. Heart rate was significantly higher for the game Adventure compared with walking at 3 km/hr, 4 km/hr, and 5 km/hr and the game Dance in both genders. The heart rate of girls during the games Adventure and Dance was significantly higher compared with boys. There was a statistically significant difference (p < .05, with an effect size ranging from 0.40 to 3.54) in the counts·min?1, measured through accelerometry, between activities. Conclusion: XBOX 360 Kinect games provide energy expenditure and physical activity of moderate intensity for both genders. The use of active video games can be an interesting alternative to increase physical activity levels.  相似文献   

7.
Familial aggregation in physical activity.   总被引：1，自引：0，他引：1  
The purposes of this study were to (a) examine the stability and consistency of the Caltrac accelerometer (Hemokinetics, Madison, WI) and an activity record to assess physical activity in children and adults (Experiment 1), and (b) to determine if there is a relationship between parents and their children in physical activity level (Experiment 2). Thirty 5-9-year-old children and their biological parents wore Caltrac accelerometers for three consecutive days (including one weekend day). At the same time, parents completed a Caltrac Activity Record (CAL REC) for themselves and their child. Dependent variables were counts per day for the Caltrac and minutes of light activity and activity for the CAL REC. Between-day correlations for the Caltrac ranged from r = .73 to .87 for the parents (p less than .001) and from r = .38 (p less than .04) to .79 (p less than .001) for the children. An analysis of variance with repeated measures indicated no significant differences for the Caltrac between days for parents and children. Between-day correlations for CAL REC ranged from r = .67 to .91 (p less than .05) for parents and r = .36 to .72 (p less than .05) for children, and there were no significant differences between days. In Experiment 2, chi 2 analyses were used to examine familial resemblance in physical activity. Using the Caltrac, familial resemblance occurred in 67% (father and child) and 73% (mother and child) of the families. Using the CAL REC, familial aggregation was present in 70% (father and child) and 66% (mother and child) of the families.(ABSTRACT TRUNCATED AT 250 WORDS)  相似文献   

8.
Abstract

The purposes of this study were to (a) examine the stability and consistency of the Caltrac accelerometer (Hemokinetics, Madison, WI) and an activity record to assess physical activity in children and adults (Experiment 1), and (b) to determine if there is a relationship between parents and their children in physical activity level (Experiment 2). Thirty 5–9-year-old children and their biological parents wore Caltrac accelerometers for three consecutive days (including one weekend day). At the same time, parents completed a Caltrac Activity Record (CAL REC) for themselves and their child. Dependent variables were counts per day for the Caltrac and minutes of light activity and activity for the CAL REC. Between-day correlations for the Caltrac ranged from r = .73 to .87 for the parents (p < .001) and from r = .38 (p < .04) to .79 (p < .001) for the children. An analysis of variance with repeated measures indicated no significant differences for the Caltrac between days for parents and children. Between-day correlations for CAL REC ranged from r = .67 to .91 (p < .05) for parents and r = .36 to .72 (p < .05) for children, and there were no significant differences between days. In Experiment 2, χ2 analyses were used to examine familial resemblance in physical activity. Using the Caltrac, familial resemblance occurred in 67% (father and child) and 73% (mother and child) of the families. Using the CAL REC, familial aggregation was present in 70% (father and child) and 66% (mother and child) of the families. Thus, children of active and less active parents exhibited physical activity patterns similar to their parents.  相似文献   

9.
Abstract

Women participants in archery, badminton, basketball, bowling, golf, hockey, Softball, tennis, and volleyball were tested to determine the relative strenuousness of these sports. The subjects' heart beats were telemetered during participation in each sport, and estimates of their ventilation and oxygen uptake for each activity were determined from data collected in the laboratory.

Mean heart rates, oxygen uptake and VO2 per kilogram of body weight were calculated for each subject in each sport. Comparisons were made to determine which activities demanded the greatest energy expenditure.

Heart rates ranging from a mean of 85 beats/min. in bowling to a mean of 185 beats/min. for the roving player in basketball were recorded. The energy expenditure of the roving player in basketball was similar to that of the center halfback in hockey; these two positions required a significantly greater O2 uptake than the positions tested in all other sports. Play in these positions was classified as heavy activity.

The non-roving positions of forward and guard in basketball, badminton, tennis, Softball (pitcher), and volleyball were rated as moderate activity. Golf, archery, and bowling were categorized as light activity in terms of energy expenditure.  相似文献   

10.
This study aimed to apply a validated bioenergetics model of sprint running to recordings obtained from commercial basic high-sensitivity global positioning system receivers to estimate energy expenditure and physical activity variables during soccer refereeing. We studied five Italian fifth division referees during 20 official matches while carrying the receivers. By applying the model to the recorded speed and acceleration data, we calculated energy consumption during activity, mass-normalised total energy consumption, total distance, metabolically equivalent distance and their ratio over the entire match and the two halves. Main results were as follows: (match) energy consumption = 4729 ± 608 kJ, mass normalised total energy consumption = 74 ± 8 kJ · kg?1, total distance = 13,112 ± 1225 m, metabolically equivalent distance = 13,788 ± 1151 m and metabolically equivalent/total distance = 1.05 ± 0.05. By using a very low-cost device, it is possible to estimate the energy expenditure of soccer refereeing. The provided predicting mass-normalised total energy consumption versus total distance equation can supply information about soccer refereeing energy demand.  相似文献   

11.
Abstract

Due to the unique energetic demands of professional young collision sport athletes, accurate assessment of energy balance is required. Consequently, this is the first study to simultaneously investigate the energy intake, expenditure and balance of professional young rugby league players across a pre-season period. The total energy expenditure of six professional young male rugby league players was measured via doubly labelled water over a fourteen-day assessment period. Resting metabolic rate was measured and physical activity level calculated. Dietary intake was reported via Snap-N-Send over a non-consecutive ten-day assessment period, alongside changes in fasted body mass and hydration status. Accordingly, energy balance was inferred. The mean (standard deviation) difference between total energy intake (16.73 (1.32) MJ.day?1) and total energy expenditure (18.36 (3.05) MJ.day?1) measured over the non-consecutive ten-day period was unclear (?1.63 (1.73) MJ.day?1; ES?=?0.91?±?1.28; p?=?0.221). This corresponded in a most likely trivial decrease in body mass (?0.65 (0.78) kg; ES?=?0.04?±?0.03; p?=?0.097). Resting metabolic rate and physical activity level across the fourteen-day pre-season period was 11.20 (2.16) MJ.day?1 and 1.7 (0.2), respectively. For the first time, this study utilises gold standard assessment techniques to elucidate the distinctly large energy expenditures of professional young rugby league players across a pre-season period, emphasising a requirement for equally large energy intakes to achieve targeted body mass and composition adaptations. Accordingly, it is imperative that practitioners regularly assess the energy balance of professional young collision-sport athletes to ensure their unique energetic requirements are achieved.  相似文献   

12.
This study aimed to assess the reliability, usefulness and construct validity of the newly developed Combined Basketball Skill Test (CBST). Fifteen recreational (age = 22.8 ± 4.2 y, stature = 184.8 ± 6.5 cm, body mass = 81.6 ± 9.6 kg, training experience = 9.8 ± 5.3 y) and fifteen semiprofessional (age = 18.9 ± 3.3 y, stature = 190.5 ± 8.1 cm, body mass = 84.2 ± 11.2 kg, training experience = 11.1 ± 3.5 y) players volunteered to participate in this study. Test–retest reliability and usefulness were examined for recreational players, while construct validity was evaluated comparing the two player groups. The CBST is composed of 12 trials and its outcome measures include: completion time (sum of the 12 trial times); penalty time (sum of the times from the 12 trials); performance time (completion time + penalty time) and total number of errors. Relative reliability analysis showed acceptable ICC values (i.e. ≥0.70) in all the studied variables. Absolute reliability analysis showed a CV < 5% for completion (1.6%) and performance (2.0%) time, while a CV >5% is reported for the remaining variables. The usefulness of the test was considered “Marginal” and “Good” when comparing TE values with SWC02 and SWC05, respectively for all the studied variables. Likely and very likely differences were shown between recreational and semiprofessional players in all investigated variables. Results showed that the CBST is reliable, useful to detect moderate changes and valid to assess basketball skills.  相似文献   

13.
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14.
This study developed and validated a vector magnitude (VM) two-regression model (2RM) for use with an ankle-worn ActiGraph accelerometer. For model development, 181 youth (mean ± SD; age, 12.0 ± 1.5 yr) completed 30 min of supine rest and 2–7 structured activities. For cross-validation, 42 youth (age, 12.6 ± 0.8 yr) completed approximately 2 hr of unstructured physical activity (PA). PA data were collected using an ActiGraph accelerometer, (non-dominant ankle) and the VM was expressed as counts/5-s. Measured energy expenditure (Cosmed K4b2) was converted to youth METs (METy; activity VO2 divided by resting VO2). A coefficient of variation (CV) was calculated for each activity to distinguish continuous walking/running from intermittent activity. The ankle VM sedentary behavior threshold was ≤10 counts/5-s, and a CV≤15 counts/5-s was used to identify walking/running. The ankle VM2RM was within 0.42 METy of measured METy during the unstructured PA (P > 0.05). The ankle VM2RM was within 5.7 min of measured time spent in sedentary, LPA, MPA, and VPA (P > 0.05). Compared to the K4b2, the ankle VM2RM provided similar estimates to measured values during unstructured play and provides a feasible wear location for future studies.  相似文献   

15.
Abstract

This study was designed to examine the magnitude and duration of excess postexercise oxygen consumption (EPOC) following upper body exercise, using lower body exercise for comparison. On separate days and in a counterbalanced order, eight subjects (four male and four female) performed a 20-min exercise at 60% of mode-specific peak oxygen uptake (VO2) using an arm crank and cycle ergometer. Prior to each exercise, baseline VO2 and heart rate (HR) were measured during the final 15 min of a 45-min seated rest. VO2 and HR were measured continuously during the postexercise period until baseline VO2 was reestablished. No significant difference between the two experimental conditions was found for magnitude of EPOC (t [7] = 0.69, p > .05). Mean (± SD) values were 9.2 ± 3.3 and 10.4 ± 5.8 kcal for the arm crank and cycle ergometer exercises, respectively. Duration of EPOC was relatively short and not significantly different (t [7] = 0.24, p > .05) between the upper body (22.9 ± 13.7 min) and lower body (24.2 ± 19.4 min) exercises. Within the framework of the chosen exercise conditions, these results suggest EPOC may be related primarily to the relative metabolic rate of the active musculature, as opposed to the absolute exercise VO2 or quantity of active muscle mass associated with these two types of exercise.  相似文献   

16.
The aims of this study were to quantify the effects of factors such as mode of exercise, body composition and training on the relationship between heart rate and physical activity energy expenditure (measured in kJ?·?min?1) and to develop prediction equations for energy expenditure from heart rate. Regularly exercising individuals (n = 115; age 18?–?45 years, body mass 47?–?120?kg) underwent a test for maximal oxygen uptake ([Vdot]O2max test), using incremental protocols on either a cycle ergometer or treadmill; [Vdot]O2max ranged from 27 to 81?ml?·?kg?1?·?min?1. The participants then completed three steady-state exercise stages on either the treadmill (10?min) or the cycle ergometer (15?min) at 35%, 62% and 80% of [Vdot]O2max, corresponding to 57%, 77% and 90% of maximal heart rate. Heart rate and respiratory exchange ratio data were collected during each stage. A mixed-model analysis identified gender, heart rate, weight, [Vdot]2max and age as factors that best predicted the relationship between heart rate and energy expenditure. The model (with the highest likelihood ratio) was used to estimate energy expenditure. The correlation coefficient (r) between the measured and estimated energy expenditure was 0.913. The model therefore accounted for 83.3% (R 2) of the variance in energy expenditure in this sample. Because a measure of fitness, such as [Vdot]O2max, is not always available, a model without [Vdot]O2max included was also fitted. The correlation coefficient between the measured energy expenditure and estimates from the mixed model without [Vdot]O2max was 0.857. It follows that the model without a fitness measure accounted for 73.4% of the variance in energy expenditure in this sample. Based on these results, we conclude that it is possible to estimate physical activity energy expenditure from heart rate in a group of individuals with a great deal of accuracy, after adjusting for age, gender, body mass and fitness.  相似文献   

17.
The purpose of this investigation was to examine the validity of energy expenditure (EE), steps, and heart rate measured with the Apple Watch 1 and Fitbit Charge HR. Thirty-nine healthy adults wore the two monitors while completing a semi-structured activity protocol consisting of 20 minutes of sedentary activity, 25 minutes of aerobic exercise, and 25 minutes of light intensity physical activity. Criterion measures were obtained from an Oxycon Mobile for EE, a pedometer for steps, and a Polar heart rate strap worn on the chest for heart rate. For estimating whole-trial EE, the mean absolute percent error (MAPE) from Fitbit Charge HR (32.9%) was more than twice that of Apple Watch 1 (15.2%). This trend was consistent for the individual conditions. Both monitors accurately assessed steps during aerobic activity (MAPEApple: 6.2%; MAPEFitbit: 9.4%) but overestimated steps in light physical activity. For heart rate, Fitbit Charge HR produced its smallest MAPE in sedentary behaviors (7.2%), followed by aerobic exercise (8.4%), and light activity (10.1%). The Apple Watch 1 had stronger validity than the Fitbit Charge HR for assessing overall EE and steps during aerobic exercise. The Fitbit Charge HR provided heart rate estimates that were statistically equivalent to Polar monitor.  相似文献   

18.
The purpose of this study was to examine the accuracy of the ePulse Personal Fitness Assistant, a forearm-worn device that provides measures of heart rate and estimates energy expenditure. Forty-six participants engaged in 4-minute periods of standing, 2.0 mph walking, 3.5 mph walking, 4.5 mph jogging, and 6.0 mph running. Heart rate and energy expenditure were simultaneously recorded at 60-second intervals using the ePulse, an electrocardiogram (EKG), and indirect calorimetry. The heart rates obtained from the ePulse were highly correlated (intraclass correlation coefficients [ICCs] ≥0.85) with those from the EKG during all conditions. The typical errors progressively increased with increasing exercise intensity but were <5 bpm only during rest and 2.0 mph. Energy expenditure from the ePulse was poorly correlated with indirect calorimetry (ICCs: 0.01-0.36) and the typical errors for energy expenditure ranged from 0.69-2.97 kcal · min(-1), progressively increasing with exercise intensity. These data suggest that the ePulse Personal Fitness Assistant is a valid device for monitoring heart rate at rest and low-intensity exercise, but becomes less accurate as exercise intensity increases. However, it does not appear to be a valid device to estimate energy expenditure during exercise.  相似文献   

19.
We compared SenseWear Armband versions (v) 2.2 and 5.2 for estimating energy expenditure in healthy adults. Thirty-four adults (26 women), 30.1 ± 8.7 years old, performed two trials that included light-, moderate- and vigorous-intensity activities: (1) structured routine: seven activities performed for 8-min each, with 4-min of rest between activities; (2) semi-structured routine: 12 activities performed for 5-min each, with no rest between activities. Energy expenditure was measured by indirect calorimetry and predicted using SenseWear v2.2 and v5.2. Compared to indirect calorimetry (297.8 ± 54.2 kcal), the total energy expenditure was overestimated (P < 0.05) by both SenseWear v2.2 (355.6 ± 64.3 kcal) and v5.2 (342.6 ± 63.8 kcal) during the structured routine. During the semi-structured routine, the total energy expenditure for SenseWear v5.2 (275.2 ± 63.0 kcal) was not different than indirect calorimetry (262.8 ± 52.9 kcal), and both were lower (P < 0.05) than v2.2 (312.2 ± 74.5 kcal). The average mean absolute per cent error was lower for the SenseWear v5.2 than for v2.2 (P < 0.001). SenseWear v5.2 improved energy expenditure estimation for some activities (sweeping, loading/unloading boxes, walking), but produced larger errors for others (cycling, rowing). Although both algorithms overestimated energy expenditure as well as time spent in moderate-intensity physical activity (P < 0.05), v5.2 offered better estimates than v2.2.  相似文献   

20.
The aims of this study were to quantify the effects of factors such as mode of exercise, body composition and training on the relationship between heart rate and physical activity energy expenditure (measured in kJ x min(-1)) and to develop prediction equations for energy expenditure from heart rate. Regularly exercising individuals (n = 115; age 18-45 years, body mass 47-120 kg) underwent a test for maximal oxygen uptake (VO2max test), using incremental protocols on either a cycle ergometer or treadmill; VO2max ranged from 27 to 81 ml x kg(-1) x min(-1). The participants then completed three steady-state exercise stages on either the treadmill (10 min) or the cycle ergometer (15 min) at 35%, 62% and 80% of VO2max, corresponding to 57%, 77% and 90% of maximal heart rate. Heart rate and respiratory exchange ratio data were collected during each stage. A mixed-model analysis identified gender, heart rate, weight, V2max and age as factors that best predicted the relationship between heart rate and energy expenditure. The model (with the highest likelihood ratio) was used to estimate energy expenditure. The correlation coefficient (r) between the measured and estimated energy expenditure was 0.913. The model therefore accounted for 83.3% (R2) of the variance in energy expenditure in this sample. Because a measure of fitness, such as VO2max, is not always available, a model without VO2max included was also fitted. The correlation coefficient between the measured energy expenditure and estimates from the mixed model without VO2max was 0.857. It follows that the model without a fitness measure accounted for 73.4% of the variance in energy expenditure in this sample. Based on these results, we conclude that it is possible to estimate physical activity energy expenditure from heart rate in a group of individuals with a great deal of accuracy, after adjusting for age, gender, body mass and fitness.  相似文献   

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