7 resultados para Accelerometer
em University of Queensland eSpace - Australia
Resumo:
Background: Physical activity (PA) is relevant to the prevention and management of many health conditions in family practice. There is a need for an efficient, reliable, and valid assessment tool to identify patients in need of PA interventions. Methods: Twenty-eight family physicians in three Australian cities assessed the PA of their adult patients during 2004 using either a two- (2Q) or three-question (3Q) assessment. This was administered again approximately 3 days later to evaluate test-retest reliability. Concurrent validity was evaluated by measuring agreement with the Active Australia Questionnaire, and criterion validity by comparison with 7-day Computer Science Applications, Inc. (CSA) accelerometer counts. Results: A total of 509 patients participated, with 428 (84%) completing a repeat assessment, and 415 (82%) accelerometer monitoring. The brief assessments had moderate test-retest reliability (2Q k = 58.0%, 95% confidence interval [CI] = 47.2-68.8%; 3Q k = 55.6%, 95% CI = 43.8-67.4%); fair to moderate concurrent validity (2Q k = 46.7%, 95% CI = 35.657.9%; 3Q k = 38.7%, 95% CI = 26.4-51.1%); and poor to fair criterion validity (2Q k = 18.2%, 95% CI = 3.9-32.6%; 3Q k = 24.3%, 95% CI = 11.6-36.9%) for identifying patients as sufficiently active. A four-level scale of PA derived from the PA assessments was significantly correlated with accelerometer minutes (2Q rho = 0.39, 95% CI = 0.28-0.49; 3Q rho = 0.31, 95% CI = 0.18-0.43). Physicians reported that the assessments took I to 2 minutes to complete. Conclusions: Both PA assessments were feasible to use in family practice, and were suitable for identifying the least active patients. The 2Q assessment was preferred by clinicians and may be most appropriate for dissemination.
Resumo:
Purpose: To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods: Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results: Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions: Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.
Resumo:
Two force balance techniques for use in hypersonic impulse facilities are compared by measuring the drag force on a 30&DEG; semi-apex-angle blunt cone model in a hypersonic shock tunnel at a free stream Mach number of 5.75. An accelerometer-based balance and a stress-wave force balance were tested simultaneously on the same model to measure the drag force. It was found that drag force measurements could be made using both techniques in a flow with a 450-μ s test period. The measured drag forces compared well with the theoretical values estimated using Newtonian theory.
Resumo:
Objective: To evaluate the reliability and validity of a brief physical activity assessment tool suitable for doctors to use to identify inactive patients in the primary care setting. Methods: Volunteer family doctors (n = 8) screened consenting patients (n = 75) for physical activity participation using a brief physical activity assessment tool. Inter-rater reliability was assessed within one week (n = 71). Validity was assessed against an objective physical activity monitor (computer science and applications accelerometer; n = 42). Results: The brief physical activity assessment tool produced repeatable estimates of sufficient total physical activity, correctly classifying over 76% of cases (kappa 0.53, 95% confidence interval (CI) 0.33 to 0.72). The validity coefficient was reasonable (kappa 0.40, 95% CI 0.12 to 0.69), with good percentage agreement (71%). Conclusions: The brief physical activity assessment tool is a reliable instrument, with validity similar to that of more detailed self report measures of physical activity. It is a tool that can be used efficiently in routine primary healthcare services to identify insufficiently active patients who may need physical activity advice.
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.
Resumo:
Purpose: This Study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents. Methods: A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking. brisk walking, easy running, and fast running) in ail indoor exercise facility. During each trial, participants were all ActiGraph accelerometer oil the right hip. EE was monitored breath by breath using the Cosmed K4b(2) portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve, Results: None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity. with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest. Conclusions: These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe, however, for estimating participation in moderate and vigorous activity.