3 resultados para walking path prediction
em University of Queensland eSpace - Australia
Resumo:
Participation in at least 30 min of moderate intensity activity on most days is assumed to confer health benefits. This study accordingly determined whether the more vigorous household and garden tasks (sweeping, window cleaning, vacuuming and lawn mowing) are performed by middle-aged men at a moderate intensity of 3-6 metabolic equivalents (METs) in the laboratory and at home. Measured energy expenditure during self-perceived moderate-paced walking was used as a marker of exercise intensity. Energy expenditure was also predicted via indirect methods. Thirty-six males [Xmacr (SD): 40.0 (3.3) years; 179.5 (6.9) cm; 83.4 (14.0) kg] were measured for resting metabolic rate (RMR) and oxygen consumption (V.O-2) during the five activities using the Douglas bag method. Heart rate , respiratory frequency, CSA (Computer Science Applications) movement counts, Borg scale ratings of perceived exertion and Quetelet's index were also recorded as potential predictors of exercise intensity. Except for vacuuming in the laboratory, which was not significantly different from 3.0 METs (P=0.98), the MET means in the laboratory and home were all significantly greater than 3.0 (Pless than or equal to0.006). The sweeping and vacuuming MET means were significantly higher (P
Resumo:
Gray's Reinforcement Sensitivity Theory (RST) consists of the Behavioural Activation System (BAS) which is the basis of Impulsivity, and Behavioural Inhibition System (BIS) which is the basis of Anxiety. In this study, Impulsivity and Anxiety were used as distal predictors of attitudes to religion in the prediction of three religious dependent variables (Church attendance, Amount of prayer, and Importance of church). We hypothesised that Impulsivity would independently predict a Rewarding attitude to the Church and that Anxiety would independently predict an Anxious attitude to the church, and that these attitudes would be proximal predictors of our dependent variables. Moreover, we predicted that interactions between predictors would be proximal. Using structural equation modelling, data from 400 participants supported the hypotheses. We also tested Eysenck's personality scales of Extraversion and Neuroticism and found a key path of the structural equation model to be non-significant. (C) 2003 Elsevier Ltd. All rights reserved.
Resumo:
Purpose: This study was conducted to devise a new individual calibration method to enhance MTI accelerometer estimation of free-living level walking speed. Method: Five female and five male middle-aged adults walked 400 m at 3.5, 4.5, and 5.5 km(.)h(-1), and 800 in at 6.5 km(.)h(-1) on an outdoor track, following a continuous protocol. Lap speed was controlled by a global positioning system (GPS) monitor. MTI counts-to-speed calibration equations were derived for each trial, for each subject for four such trials with each of four MTI, for each subject for the average MTI. and for the pooled data. Standard errors of the estimate (SEE) with and without individual calibration were compared. To assess accuracy of prediction of free-living walking speed, subjects also completed a self-paced, brisk 3-km walk wearing one of the four MTI, and differences between actual and predicted walking speed with and without individual calibration were examined. Results: Correlations between MTI counts and walking speed were 0.90 without individual calibration, 0.98 with individual calibration for the average MTI. and 0.99 with individual calibration for a specific MTI. The SEE (mean +/- SD) was 0.58 +/- 0.30 km(.)h(-1) without individual calibration, 0.19 +/- 0.09 km h(-1) with individual calibration for the average MTI monitor, and 0.16 +/- 0.08 km(.)h(-1) with individual calibration for a specific MTI monitor. The difference between actual and predicted walking speed on the brisk 3-km walk was 0.06 +/- 0.25 km(.)h(-1) using individual calibration and 0.28 +/- 0.63 km(.)h(-1) without individual calibration (for specific accelerometers). Conclusion: MTI accuracy in predicting walking speed without individual calibration might be sufficient for population-based studies but not for intervention trials. This individual calibration method will substantially increase precision of walking speed predicted from MTI counts.