928 resultados para Portable.


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The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. PURPOSE This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. METHODS A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and VO 2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). RESULTS Across all four intensity levels, the EV (κ = 0.68) and FT (κ = 0.66) cut points exhibited significantly better agreement than TR (κ = 0.62), MT (κ = 0.54), and PU (κ = 0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate-to vigorous-intensity physical activity (ROC-AUC = 0.90) than TR, PU, or MT cut points (ROC-AUC = 0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC = 0.90). CONCLUSIONS On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents. Copyright © 2011 by the American College of Sports Medicine.

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Child care centers differ systematically with respect to the quality and quantity of physical activity they provide, suggesting that center-level policies and practices, as well as the center's physical environment, are important influences on children's physical activity behavior. Purpose To summarize and critically evaluate the extant peer-reviewed literature on the influence of child care policy and environment on physical activity in preschool-aged children. Methods A computer database search identified seven relevant studies that were categorized into three broad areas: cross-sectional studies investigating the impact of selected center-level policies and practices on moderate-to-vigorous physical activity (MVPA), studies correlating specific attributes of the outdoor play environment with the level and intensity of MVPA, and studies in which a specific center-level policy or environmental attribute was experimentally manipulated and evaluated for changes in MVPA. Results Staff education and training, as well as staff behavior on the playground, seem to be salient influences on MVPA in preschoolers. Lower playground density (less children per square meter) and the presence of vegetation and open play areas also seem to be positive influences on MVPA. However, not all studies found these attributes to be significant. The availability and quality of portable play equipment, not the amount or type of fixed play equipment, significantly influenced MVPA levels. Conclusions Emerging evidence suggests that several policy and environmental factors contribute to the marked between-center variability in physical activity and sedentary behavior. Intervention studies targeting these factors are thus warranted.

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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.

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Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

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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.

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Objective To determine the relationship between family child care home (FCCH) practices and characteristics, and objectively measured physical activity (PA) among children attending FCCHs. Methods FCCH practices and characteristics were assessed in 45 FCCHs in Oregon (USA) in 2010-2011 using the Nutrition and Physical Activity Self-Assessment for Child Care Instrument. Within the 45 FCCHs, 136 children between ages 2 and 5. years wore an accelerometer during child care attendance over a one-week period. Time spent in light, moderate, and vigorous PA per hour was calculated using intensity-related cut-points (Pate et al., 2006). Results FCCH characteristics and practices associated with higher levels of PA (min/h; p < 0.05) included provision of sufficient outdoor active play [32.2 (1.0) vs. 28.6 (1.3)], active play using portable play equipment [31.7 (1.0) vs. 29.3 (1.4)], the presence of a variety of fixed play equipment [32.2 (1.0) vs. 28.9 (1.3)], and suitable indoor play space [32.2 (1.0) vs. 28.6 (1.3)], engaging in active play with children [32.1 (1.1) vs. 29.6 (1.2)], and receiving activity-related training [33.1 (1.2) vs. 30.3 (1.1)]. Conclusions This is the first study to identify practices and characteristics of FCCHs that influence children's PA. These data should be considered when developing programs and policies to promote PA in FCCHs.

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To evaluate the validity of the ActiGraph accelerometer for the measurement of physical activity intensity in children and adolescents with cerebral palsy (CP) using oxygen uptake (VO 2) as the criterion measure. Thirty children and adolescents with CP (mean age 12.6 ± 2.0 years) wore an ActiGraph 7164 and a Cosmed K4b 2 portable indirect calorimeter during four activities; quiet sitting, comfortable paced walking, brisk paced walking and fast paced walking. VO 2 was converted to METs and activity energy expenditure and classiWed as sedentary, light or moderate-to-vigorous intensity according to the conventions for children. Mean ActiGraph counts min -1 were classiWed as sedentary, light or moderate-to-vigorous (MVPA) intensity using four diVerent sets of cut-points. VO 2 and counts min¡1 increased signiWcantly with increases in walking speed (P < 0.001). Receiver operating characteristic (ROC) curve analysis indicated that, of the four sets of cut-points evaluated, the Evenson et al. (J Sports Sci 26(14):1557-1565, 2008) cut-points had the highest classiWcation accuracy for sedentary (92%) and MVPA (91%), as well as the second highest classiWcation accuracy for light intensity physical activity (67%). A ROC curve analysis of data from our participants yielded a CP-speciWc cut-point for MVPA that was lower than the Evenson cut-point (2,012 vs. 2,296 counts min¡1), however, the diVerence in classiWcation accuracy was not statistically signiWcant 94% (95% CI = 88.2-97.7%) vs. 91% (95% CI = 83.5-96.5%). In conclusion, among children and adolescents with CP, the ActiGraph is able to diVerentiate between diVerent intensities of walking. The use of the Evenson cut-points will permit the estimation of time spent in MVPA and allows comparisons to be made between activity measured in typically developing adolescents and adolescents with CP. © 2011 Springer-Verlag.

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Background Promoting participation physical activity (PA) is an important means of promoting healthy growth and development in children with cerebral palsy (CP). The ActiGraph is a uniaxial accelerometer that provides a realtime measure of PA intensity, duration and frequency. Its small, light weight design makes it a promising measure of activity in children with CP. To date no study has validated the use of accelerometry as a measure of PA in ambulant adolescents with CP. Objectives To evaluate the validity of the ActiGraph accelerometer for measuring PA intensity in adolescents with CP, using oxygen consumption (VO2), measured using portable indirect calorimetry (Cosmed K4b2), as the criterion measure. Design Validation Study Participants/Setting: Ambulant adolescents with CP aged 10–16 years, GMFCS rating of I-III. The recruitment target is 30 (10 in each GMFCS level). Materials/Methods Participants wore the ActiGraph (counts/min) and a Cosmed K4b2 indirect calorimeter (mL/kg/min) during six activity trials: quiet sitting (QS), comfortable paced walking (CPW), brisk paced walking (BPW), fast paced walking (FPW), a ball-kicking protocol (KP) and a ball-throwing protocol (TP). MET levels (multiples of resting metabolism) for each activity were predicted from ActiGraph counts using the Freedson age-specific equation (Freedson et al. 2005) and compared with actual MET levels measured by the Cosmed. Predicted and measured METs for each activity trial were classified as light (> 1.5 METs and <4.6 METs) or moderate to vigorous intensity (≥ 4.6 METs). Results To date 36 bouts of activity have been completed (6 participants x 6 activities). Mean VO2 increased linearly as the intensity of the walking activity increased (CPW=9.47±2.16, BPW=14.06±4.38, FPW=19.21±5.68 ml/kg/min) and ActiGraph counts reflected this pattern (CPW=1099±574, BPW=2233±797 FPW=4707±1013 counts/min). The throwing protocol recording the lowest VO2 (TP=7.50±3.86 ml/kg/min) and lowest overall counts/min (TP=31±27 counts/min). When each of the 36 bouts were classified as either light or moderate to vigorous intensity using measured VO2 as the criterion measure, the Freedson equation correctly classified 28 from 36 bouts (78%). Conclusion/Clinical Implications These preliminary findings suggest that there is a relationship between the intensity of PA and direct measure of oxygen consumption and that therefore the ActiGraph may be a promising tool for accurately measuring free living PA in the community. Further data collection of the complete sample will enable secondary analysis of the relationship between PA and severity of CP (GMFCS level).

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Purpose The aim of this study was to assess the predictive validity of three accelerometer prediction equations (Freedson et aL, 1997; Trost et aL, 1998; Puyau et al., 2002) for energy expenditure (EE) during overland walking and running in children and adolescents. Methods 45 healthy children and adolescents aged 10-18 completed the following protocol, each task 5-mins in duration, with a 5-min rest period in between; walking normally; walking briskly; running easily and running fast. During each task participants wore MTI (WAM 7164) Actigraphs on the left and right hips. VO2 was monitored breath by breath using the Cosmed K4b2 portable indirect calorimetry system. For each prediction equation, difference scores were calculated as EE measured minus EE predicted. The percentage of 1-min epochs correctly categorized as light (<3 METs), moderate (3-5.9 METs), and vigorous (≥6 METS) was also calculated. Results The Freedson and Trost equations consistently overestimated MET level. The level of overestimation was statistically significant across all tasks for the Freedson equation, and was significant for only the walking tasks for the Trost equation. The Puyau equation consistently underestimated AEE with the exception of the walking normally task. In terms of categorisation, the Freedson equation (72.8% agreement) demonstrated better agreement than the Puyau (60.6%). 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 overland walking and running. However, the cut points generated by these equations maybe useful for classifying activity as either, light, moderate, or vigorous.

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Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

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Background: Hospital disaster resilience can be defined as a hospital’s ability to resist, absorb, and respond to the shock of disasters while maintaining critical functions, and then to recover to its original state or adapt to a new one. This study aims to explore the status of resilience among tertiary hospitals in Shandong Province, China. Methods: A stratified random sample (n = 50) was derived from tertiary A, tertiary B, and tertiary C hospitals in Shandong Province, and was surveyed by questionnaire. Data on hospital characteristics and 8 key domains of hospital resilience were collected and analysed. Variables were binary, and analysed using descriptive statistics such as frequencies. Results: A response rate of 82% (n = 41) was attained. Factor analysis identified four key factors from eight domains which appear to reflect the overall level of disaster resilience. These were hospital safety, disaster management mechanisms, disaster resources and disaster medical care capability. The survey demonstrated that in regard to hospital safety, 93% had syndromic surveillance systems for infectious diseases and 68% had evaluated their safety standards. In regard to disaster management mechanisms, all had general plans, while only 20% had specific plans for individual hazards. 49% had a public communication protocol and 43.9% attended the local coordination meetings. In regard to disaster resources, 75.6% and 87.5% stockpiled emergency drugs and materials respectively, while less than a third (30%) had a signed Memorandum of Understanding with other hospitals to share these resources. Finally in regard to medical care, 66% could dispatch an on-site medical rescue team, but only 5% had a ‘portable hospital’ function and 36.6% and 12% of the hospitals could surge their beds and staff capacity respectively. The average beds surge capacity within 1 day was 13%. Conclusions: This study validated the broad utility of a framework for understanding and measuring the level of hospital resilience. The survey demonstrated considerable variability in disaster resilience arrangements of tertiary hospitals in Shandong province, and the difference between tertiary A hospitals and tertiary B hospitals was also identified in essential areas.

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Background: In recent years, there have been investigations concerning upper-limbs kinematics by various devices. The latest generation of smartphones often includes inertial sensors with subunits which can detect inertial kinematics. The use of smartphones is presented as a convenient and portable analysis method for studying kinematics in terms of angular mobility and linear acceleration Objective: The aim of this study was to study humerus kinematics through six physical properties that correspond to angular mobility and acceleration in the three axes of space, obtained by a smartphone. Methods: This cross-sectional study recruited healthy young adult subjects. Descriptive and anthropometric independent variables related to age, gender, weight, size, and BMI were included. Six physical properties were included corresponding to two dependent variables for each of three special axes: mobility angle (degrees) and lineal acceleration (meters/seconds2), which were obtained thought the inertial measurement sensor embedded in the iPhone4 smartphone equipped with three two elements for the detection of kinematic variables: a gyroscope and an accelerometer. Apple uses an LIS302DL accelerometer in the iPhone4. The application used to obtain kinematic data was xSensor Pro, Crossbow Technology, Inc., available at the Apple AppStore. The iPhone4 has storage capacity of 20MB. The data-sampling rate was set to 32 Hz, and the data for each analytical task was transmitted as email for analysis and postprocessing The iPhone4 was placed in the right half of the body of each subject located in the middle third of the humerus slightly posterior snugly secured by a neoprene fixation belt. Tasks were explained concisely and clearly. The beginning and the end were decided by a verbal order by the researcher. Participants were placed standing, starting from neutral position, performing the following analytical tasks: 180º right shoulder abduction (eight repetitions) and, after a break of about 3 minutes, 180º right shoulder flexion (eight repetitions). Both tasks were performed with the elbow extended, wrist in neutral position and the palmar area of the hand toward the midline at the beginning and end of the movement. Results: A total of 11 subjects (8 men, 3 woman) were measured, whose mean of age was 24.7 years (SD = 4.22 years) and their average BMI was 22.64 Kg/m2 (SD = 2.29 Kg/m2). The mean of angular mobility collected by the smartphone was bigger in pitch axis for flexion (= 157.28°, SD= 12.35°) and abduction (= 151.71°, SD= 9.70°). With regard to acceleration, the highest peak mean value was shown in the Y motion axis during flexion (= 19.5°/s2, SD = 0.8°/s2) and abduction (= 19.4°/s2, SD = 0.8°/s2). Also, descriptive graphics of analytical tasks performed were obtained. Conclusions: This study shows how humerus contributes to upper-limb motion and it identified movement patterns. Therefore, it supports smartphone as a useful device to analyze upper-limb kinematics. Thanks to this study it´s possible to develop a simple application that facilitates the evaluation of the patient.

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Background Despite the importance of an effective health system response to various disasters, relevant research is still in its infancy, especially in middle- and low-income countries. Objective This paper provides an overview of the status of disaster health management in China, with its aim to promote the effectiveness of the health response for reducing disaster-related mortality and morbidity. Design A scoping review method was used to address the recent progress of and challenges to disaster health management in China. Major health electronic databases were searched to identify English and Chinese literature that were relevant to the research aims. Results The review found that since 2003 considerable progress has been achieved in the health disaster response system in China. However, there remain challenges that hinder effective health disaster responses, including low standards of disaster-resistant infrastructure safety, the lack of specific disaster plans, poor emergency coordination between hospitals, lack of portable diagnostic equipment and underdeveloped triage skills, surge capacity, and psychological interventions. Additional challenges include the fragmentation of the emergency health service system, a lack of specific legislation for emergencies, disparities in the distribution of funding, and inadequate cost-effective considerations for disaster rescue. Conclusions One solution identified to address these challenges appears to be through corresponding policy strategies at multiple levels (e.g. community, hospital, and healthcare system level).

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Building rich and authentic learning experiences in the STEM classroom, is a challenge for many educators within Higher Education. While many Higher Education Institutions have embraced the need to transform current teaching and learning practices and include a range of online tools, this has often been met with some resistance and approaches that do not always recognise the academic who are a critical component to the success of the transformational process. Over the last decade the Internet has evolved from being a tool used by a few dedicated educators to one that is being used by the majority of educators. However, what is important is how this great resource is used in teaching and learning to allow students to build knowledge. The ability for students to construct knowledge and engage in higher order thinking skills is at the heart of educational practices, and building a community of learners has the potential to support these practices, especially within STEM education. This paper explores the relationship between students and an academic teaching in a technology rich STEM learning environment and their adoption of social community and shared tools. In particular the paper reports on the critical components that make a successful community of learners and the educational tools and approaches that were successfully used to enhance the student learning experience in a STEM classroom.

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Supported by contemporary theories of architectural aesthetics and neuro-aesthetics this paper presents a case for the use of portable fNIRS imaging in the assessment of emotional responses to spatial environments experienced by both blind and sighted. The aim of the paper is to outline the implications of fNIRS for spatial research and practice within the field of architecture, thereby suggesting a potential taxonomy of particular formations of space and affect. Empirical neurological study of affect and spatial experience from an architectural design perspective remains in many instances unchartered. Clinical research using the portable non-invasive neuro-imaging device, functional near infrared spectroscopy (fNIRS) is proving convincing in its ability to detect emotional responses to visual, spatio-auditory and task based stimuli, providing a firm basis to potentially track cortical activity in the appraisal of architectural environments. Additionally, recent neurological studies have sought to explore the manifold sensory abilities of the visually impaired to better understand spatial perception in general. Key studies reveal that early blind participants perform as well as sighted due to higher auditory and somato-sensory spatial acuity. For instance, face vision enables the visually impaired to detect environments through skin pressure, enabling at times an instantaneous impression of the layout of an unfamiliar environment. Studies also report pleasant and unpleasant emotional responses such as ‘weightedness’ or ‘claustrophobia’ within certain interior environments, revealing a deeper perceptual sensitivity then would be expected. We conclude with justification that comparative fNIRS studies between the sighted and blind concerning spatial experience have the potential to provide greater understanding of emotional responses to architectural environments.