DESIGN: This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.
SETTING: General Intensive Care Unit, University of Malaya Medical Centre.
PATIENTS: Mechanically ventilated critically ill patients.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.
CONCLUSIONS: Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.
OBJECTIVES:: The aim was to investigate their dynamic characteristics and create a relationship between these dynamic data and the prescription of foot.
STUDY DESIGN:: Experimental Assessment.
METHODS:: This article presents the modal analysis results of the full range of Össur Flex-Run™ running feet that are commercially available (1LO-9LO) using experimental modal analysis technique under a constant mass at 53 kg and boundary condition.
RESULTS:: It was shown that both the undamped natural frequency and stiffness increase linearly from the lowest to the highest stiffness category of foot which allows for a more informed prescription of foot when tuning to a matched natural frequency. The low damping characteristics determined experimentally that ranged between 1.5% and 2.0% indicates that the feet require less input energy to maintain the steady-state cyclic motion before take-off from the ground. An analysis of the mode shapes also showed a unique design feature of these feet that is hypothesised to enhance their performance.
CONCLUSION:: A better understanding of dynamic characteristics of the feet can help tune the feet to the user's requirements in promoting a better gait performance.
CLINICAL RELEVANCE: The dynamic data determined from this study are needed to better inform the amputees in predicting the natural frequency of the foot prescribed. The amputees can intuitively tune the cyclic body rhythm during walking or running to match with the natural frequency. This could eventually promote a better gait performance.
METHOD: Two lifting loads were considered in this study: 1 kg and 5 kg. Each subject adjusted his frequency of lifting using a psychophysical approach. The subjects were instructed to perform combined MMH task as fast as they could over a period of 45 minutes without exhausting themselves or becoming overheated. The physiological response energy expenditure was recorded during the experimental sessions. The ratings of perceived exertion (RPE) for four body parts (forearms, upper arm, lower back and entire body) were recorded after the subjects had completed the instructed task.
RESULTS: The mean frequencies of the MMH task had been 6.8 and 5.5 cycles/minute for lifting load of 1 and 5 kg, respectively, while the mean energy expenditure values were 4.16 and 5.62 kcal/min for 1 and 5 kg load, respectively. These displayed a significant difference in the Maximum Acceptable Frequency of Lift (MAFL) between the two loads, energy expenditure and RPE (p < 0.05) whereby the subjects appeared to work harder physiologically for heavier load.
CONCLUSION: It can be concluded that it is significant to assess physiological response and RPE in determining the maximum acceptable lifting frequency at varied levels of load weight. The findings retrieved in this study can aid in designing tasks that do not exceed the capacity of workers in order to minimise the risk of WRMSDs.
AIM: To compare the physiological responses and user preferences between conventional heavy-bag boxing against a novel form of video game boxing, known as exergaming boxing.
DESIGN: Cross-sectional study.
SETTING: Exercise laboratory setting in a university medical center.
POPULATION: Seventeen participants with SCI were recruited, of which sixteen were male and only one female. Their mean age was 35.6±10.2 years.
METHODS: All of them performed a 15-minute physical exercise session of exergaming and heavy-bag boxing in a sitting position. The study assessed physiological responses in terms of oxygen consumption, metabolic equivalent (MET) and energy expenditure between exergaming and heavy-bag boxing derived from open-circuit spirometry. Participants also rated their perceived exertion using Borg's category-ratio ratings of perceived exertion.
RESULTS: Both exergaming (MET: 4.3±1.0) and heavy-bag boxing (MET: 4.4±1.0) achieved moderate exercise intensities in these participants with SCI. Paired t-test revealed no significant differences (P>0.05, Cohen's d: 0.02-0.49) in the physiological or perceived exertional responses between the two modalities of boxing. Post session user survey reported all the participants found exergaming boxing more enjoyable.
CONCLUSIONS: Exergaming boxing, was able to produce equipotent physiological responses as conventional heavy-bag boxing. The intensity of both exercise modalities achieved recommended intensities for health and fitness benefits.
CLINICAL REHABILITATION IMPACT: Exergaming boxing have the potential to provide an enjoyable, self-competitive environment for moderate-vigorous exercise even at the comfort of their homes.
INTRODUCTION: The major goal of this study was to determine the effects of short-term group-based step aerobics (GBSA) exercise on the bone metabolism, bone mineral density (BMD), and functional fitness of postmenopausal women (PMW) with low bone mass.
METHODS: Forty-eight PMW (aged 58.2 ± 3.5 years) with low bone mass (lumbar spine BMD T-score of -2.00 ± 0.67) were recruited and randomly assigned to an exercise group (EG) or to a control group (CG). Participants from the EG attended a progressive 10-week GBSA exercise at an intensity of 75-85 % of heart rate reserve, 90 min per session, and three sessions per week. Serum bone metabolic markers (C-terminal telopeptide of type 1 collagen [CTX] and osteocalcin), BMD, and functional fitness components were measured before and after the training program. Mixed-models repeated measures method was used to compare differences between the groups (α = 0.05).
RESULTS: After the 10-week intervention period, there was no significant exercise program by time interaction for CTX; however, the percent change for CTX was significantly different between the groups (EG = -13.1 ± 24.4 % vs. CG = 11.0 ± 51.5 %, P