629 resultados para Remotely Monitoring Exercise, Cardiac Rehabiliation
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We have determined the effect of two exercise-training intensities on the phospholipid profile of both glycolytic and oxidative muscle fibers of female Sprague-Dawley rats using electrospray-ionization mass spectrometry. Animals were randomly divided into three training groups: control, which performed no exercise training; low-intensity (8 m/min) treadmill running; or high-intensity (28 m/min) treadmill running. All exercise-trained rats ran 1,000 m/session for 4 days/wk for 4 wk and were killed 48 h after the last training bout. Exercise training was found to produce no novel phospholipid species but was associated with significant alterations in the relative abundance of a number of phospholipid molecular species. These changes were more prominent in glycolytic (white vastus lateralis) than in oxidative (red vastus lateralis) muscle fibers. The largest observed change was a decrease of ∼20% in the abundance of 1-stearoyl-2-docosahexaenoyl-phosphatidylethanolamine [PE(18:0/22:6); P < 0.001] ions in both the low- and high-intensity training regimes in glycolytic fibers. Increases in the abundance of 1-oleoyl-2-linoleoyl phopshatidic acid [PA(18:1/18:2); P < 0.001] and 1-alkenylpalmitoyl-2-linoleoyl phosphatidylethanolamine [plasmenyl PE (16:0/18:2); P < 0.005] ions were also observed for both training regimes in glycolytic fibers. We conclude that exercise training results in a remodeling of phospholipids in rat skeletal muscle. Even though little is known about the physiological or pathophysiological role of specific phospholipid molecular species in skeletal muscle, it is likely that this remodeling will have an impact on a range of cellular functions.
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Purpose This study aimed to objectively measure the physical activity (PA) characteristics of a racially and ethnically diverse sample of inner-city elementary schoolchildren and to examine the influence of sex, race/ethnicity, grade level, and weight status on PA. Methods A total of 470 students in grades 4-6 from six inner-city schools in Philadelphia wore an ActiGraph GT3X+ accelerometer (Actigraph, Pensacola, FL) for up to 7 d. The resultant data were uploaded to a customized Visual Basic EXCEL macro to determine the time spent in sedentary (SED), light-intensity PA (LPA), and moderate- to vigorous-intensity PA (MVPA). Results On average, students accumulated 48 min of MVPA daily. Expressed as a percentage of monitoring time, students were sedentary for 63% of the time, in LPA 31% of the time, and in MVPA 6% of the time. Across all race/ethnicity and grade level groups, boys exhibited significantly higher levels of MVPA than girls did; fifth-grade boys exhibited significantly lower MVPA levels than fourth-and sixth-grade boys did, and sixth-grade girls exhibited significantly lower MVPA levels than fourth-and fifth-grade girls did. Hispanic children exhibited lower levels of MVPA than children from other racial/ethnic groups did, and overweight and obese children exhibited significantly lower MVPA levels than children in the healthy weight range did. Across the entire sample, only 24.3% met the current public health guidelines for PA. Physical inactivity was significantly greater among females, Hispanics, and overweight and obese students. Conclusions Fewer than one in four inner-city schoolchildren accumulated the recommended 60 min of MVPA daily. These findings highlight the need for effective and sustainable programs to promote PA in inner-city youth.
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Introduction Older people recovering from cardiac events requiring an acute hospital admission may experience a decline in physical function limiting their ability to return home to their previous accommodation. Subacute inpatient rehabilitation therapies have potential to assist recovery of physical functioning. However, it is unknown whether age influences the length of stay or physical functioning at discharge from subacute inpatient rehabilitation for this population. Objectives This study examined the outcomes of a cohort of older patients recovering from a cardiac event requiring hospitalisation to investigate the association between age and physical function at discharge, as well as age and length of rehabilitation stay. Methods Participants included 145 consecutive inpatient admissions to a subacute geriatric assessment and rehabilitation unit with a cardiac condition as their primary reason for hospital admission. Participants were required to complete a multi-disciplinary physical functioning assessment within 72 hours of admission to the unit, and again within 72 hours prior to discharge from the unit. The primary outcome measure was the Functional Independence Measure motor score. Demographic and clinical information, including length of stay and discharge destination, were also recorded. Results A total n=126 (87%) participants, with a mean (standard deviation) age of 79 (10) years, had both assessments completed and were included in analyses. Participants who had passed away (n=4, 3%), or did not have both assessments completed per protocol were excluded from analyses. Discharge destinations included home (n=101, 80%), residential aged care (n=17, 13%) and another hospital (n=8, 6%). The (median, interquartile range) Functional Independence Measure motor score was higher at discharge (79, 71 to 84) than admission (61, 48 to 71); z=7.75 p<0.001. Age was not associated with Functional Independence Measure motor score at discharge (t= -0.18, p=0.86), or length of stay in the rehabilitation unit (t= -0.52, 0.60). Conclusion Any perception that age may be associated with longer lengths of stay and reduced physical function outcomes among patients with cardiac conditions admitted for subacute inpatient rehabilitation for older adults is not supported data from this investigation. Older age should not be considered a disincentive when considering the suitability of patients with cardiac diagnoses for this type of inpatient rehabilitation or their potential physical functioning outcome.
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This paper firstly presents the benefits and critical challenges on the use of Bluetooth and Wi-Fi for crowd data collection and monitoring. The major challenges include antenna characteristics, environment’s complexity and scanning features. Wi-Fi and Bluetooth are compared in this paper in terms of architecture, discovery time, popularity of use and signal strength. Type of antennas used and the environment’s complexity such as trees for outdoor and partitions for indoor spaces highly affect the scanning range. The aforementioned challenges are empirically evaluated by “real” experiments using Bluetooth and Wi-Fi Scanners. The issues related to the antenna characteristics are also highlighted by experimenting with different antenna types. Novel scanning approaches including Overlapped Zones and Single Point Multi-Range detection methods will be then presented and verified by real-world tests. These novel techniques will be applied for location identification of the MAC IDs captured that can extract more information about people movement dynamics.
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Background Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Best Practices Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e.g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). Future Directions New methods of calibration now use "pattern recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.
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Purpose Most studies that use either a single exercise session, exercise training, or a cross-sectional design have failed to find a relationship between exercise and plasma lipoprotein(a) [Lp(a)] concentrations. However, a few studies investigating the effects of longer and/or more strenuous exercise have shown elevated Lp(a) concentrations, possibly as an acute-phase reactant to muscle damage. Based on the assumption that greater muscle damage would occur with exercise of longer duration, the purpose of the present study was to determine whether exercise of longer duration would increase Lp(a) concentration and creatine kinase. (CK) activity more than exercise of shorter duration. Methods Ten endurance-trained men (mean +/- SD: age, 27 +/- 6 yr; maximal oxygen consumption [(V)over dotO(2max)], 57 +/- 7 mL(.)kg(-1) min(-1)) completed two separate exercise sessions at 70% (V)over dotO(2max). One session required 900 kcal of energy expenditure (60 +/- 6 min), and the other required 1500 kcal (112 +/- 12 min). Fasted blood samples were taken immediately before (0-pre), immediately after (0-post), 1 d after (1-post), and 2 d after (2-post) each exercise session. Results CK activity increased after both exercise sessions (mean +/- SE; 800 kcal: 0-pre 55 +/- 11, 1-post 168 +/- 64 U(.)L(-1.)min(-1); 1500 kcal: 0-pre 51 +/- 5, 1-post 187 +/- 30, 2-post 123 +/- 19 U(.)L(-1.)min(-1); P < 0.05). However, median Lp(a) concentrations were not altered by either exercise session (800 kcal: 0-pre 5.0 mg(.)dL(-1), 0-post 3.2 mg(.)dL(-1), 1-post 4.0 mg(.)dL(-1), 2-post 3.4 mg(.)dL(-1); 1500 kcal: 0-pre 5.8 mg(.)dL(-1), 0-post 4.3 mg(.)dL(-1), 1-post 3.2 mg(.)dL(-1), 2-post 5.3 mg(.)dL(-1)). In addition, no relationship existed between exercise-induced changes in CK activity and Lp(a) concentration (800 kcal: r = -0.26; 1500 kcal: r = -0.02). Conclusion These results suggest that plasma Lp(a) concentration will not increase in response to minor exercise-induced muscle damage in endurance-trained runners.
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Lipoprotein(a) (Lp(a)) is bound to apolipoprotein B-100 by disulfide linkage and is associated in the upper density range of low density lipoprotein cholesterol. Persons with elevated concentrations of Lp(a) are regarded as having an increased risk for premature coronary artery disease. Although many studies exist evaluating the effects of a single session of exercise on lipids and lipoproteins, little information is available concerning the effects of exercise on Lp(a). Therefore, the purpose of this study was to determine the effects of a single exercise session on plasma Lp(a). Twelve physically active men completed two 30-min submaximal treadmill exercise sessions: low intensity (LI, 50% VO2max) and high intensity (HI, 80% VO2max). Blood samples were obtained immediately before and after exercise. Total cholesterol (LI: before 4.22 +/- 0.26, after 4.24 +/- 0.28; HI: before 4.24 +/- 0.31, after 4.11 +/- 0.28 mmol . l(-1), mean +/- SE) and triglyceride (LI: before 1.14 +/- 0.16, after 1.06 +/- 0.16; HI: before 1.12 +/- 0.19, after 1.21 +/- 0.19 mmol . l(-1)) concentrations did not differ immediately after either exercise session, nor did Lp(a) concentrations differ immediately after either exercise session (LI: before 4.1 +/- 2.2, after 4.0 +/- 2.1; HI: before 3.9 +/- 2.2, after 3.7 +/- 2.0 mg . dl(-1)). These results suggest that neither a low nor a high intensity exercise session lasting 30 min in duration has an immediate effect on plasma Lp(a).
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The purpose of this study was to determine whether physical activity behavior tracks during early childhood. Forty-seven children (22 males, 25 females) aged 3-4 yr at the beginning of the study were followed over a 3-yr period. Heart rates were measured at least 2 and up to 4 d . yr(-1) with a Quantum XL Telemetry heart rate monitor. Physical activity was quantified as the percentage of observed minutes between 3:00 and 6:00 p.m. during which heart rate was 50% or more above individual resting heart rate (PAHR-50 Index). Tracking of physical activity was analyzed using Pearson and Spearman correlations. Yearly PAHR-50 index tertiles were created and examined for percent agreement and Cohen's kappa. Repeated measures ANOVA was used to calculate the intraclass correlation coefficient across the 3 yr of the study. Spearman rank order correlations ranged from 0.57 to 0.66 (P < 0.0001). Percent agreement ranged from 49% to 62%. The intraclass R for the 3 yr was 0.81. It was concluded that physical activity behavior tends to track during early childhood.
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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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In order to effectively measure the physical activity of children, objective monitoring devices must be able to quantify the intermittent and nonlinear movement of free play. The purpose of this study was to investigate the validity of the Computer Science and Applications (CSA) uniaxial accelerometer and the TriTrac-R3D triaxial accelerometer with respect to their ability to measure 8 "free-play" activities of different intensity. The activities ranged from light to very vigorous in intensity and included activities such as throwing and catching, hopscotch, and basketball. Twenty-eight children, ages 9 to 11, wore a CSA and a heart rate monitor while performing the activities. Sixteen children also wore a Tritrac. Counts from the CSA, Tritrac, and heart rates corresponding to the last 3 min of the 5 min spent at each activity were averaged and used in correlation analyses. Across all 8 activities, Tritrac counts were significantly correlated with predicted MET level (r= 0.69) and heart rate (r= 0.73). Correlations between CSA output, predicted MET level (0.43), and heart rate (0.64) were also significant but were lower than those observed for the Tritrac. These data indicate that accelerometers are an appropriate methodology for measuring children's free-play physical activities.
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The purpose of this study was to examine the validity of the 3-Day Physical Activity Recall (3DPAR) self-report instrument in a sample of eighth and ninth grade girls (n = 70, 54.3% white, 37.1% African American). Criterion measures of physical activity were derived using the CSA 7164 accelerometer. Participants wore a CSA monitor for 7 consecutive days and completed the self-report physical activity recall for the last 3 of those days. Self-reported total METs, 30-min blocks of MVPA, and 30-min blocks of VPA were all significantly correlated with analogous CSA variables for 7 days (r = 0.35-0.51; P < 0.01) and 3 days (r = 0.27-0.46; P < 0.05) of monitoring. The results indicate that the 3DPAR is a valid instrument for assessing overall, vigorous, and moderate to vigorous physical activity in adolescent girls.
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Objective To evaluate a conceptual model linking parent physical activity (PA) orientations, parental support for PA, and PA behavior in preschool children. Methods Participants were 156 parent-child dyads from 13 child care centers in Queensland, Australia. Parents completed a questionnaire measuring parental PA, parental enjoyment of PA, perceived importance of PA, parental support for PA, parents' perceptions of competence, and child PA at home. MVPA while attending child care was measured via accelerometry. Data were collected between May and August of 2003. The relationships between the study variables and child PA were tested using observed variable path analysis. Results Parental PA and parents' perceptions of competence were positively associated with parental support for PA (β= 0.23 and 0.18, respectively, p<0.05). Parental support, in turn, was positively associated with child PA at home (β= 0.16, p<0.05), but not at child care (β= 0.01, p= 0.94). Parents' perceptions of competence was positively associated with both home-based and child care PA (β= 0.20 and 0.28, respectively, p<0.05). Conclusions Family-based interventions targeting preschoolers should include strategies to increase parental support for PA. Parents who perceive their child to have low physical competence should be encouraged to provide adequate support for PA. © 2009 Elsevier Inc.
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Many countries conduct regular national time use surveys, some of which date back as far as the 1960s. Time use surveys potentially provide more detailed and accurate national estimates of the prevalence of sedentary and physical activity behavior than more traditional self-report surveillance systems. In this study, the authors determined the reliability and validity of time use surveys for assessing sedentary and physical activity behavior. In 2006 and 2007, participants (n = 134) were recruited from work sites in the Australian state of New South Wales. Participants completed a 2-day time use diary twice, 7 days apart, and wore an accelerometer. The 2 diaries were compared for test-retest reliability, and comparison with the accelerometer determined concurrent validity. Participants with similar activity patterns during the 2 diary periods showed reliability intraclass correlations of 0.74 and 0.73 for nonoccupational sedentary behavior and moderate/vigorous physical activity, respectively. Comparison of the diary with the accelerometer showed Spearman correlations of 0.57-0.59 and 0.45-0.69 for nonoccupational sedentary behavior and moderate/vigorous physical activity, respectively. Time use surveys appear to be more valid for population surveillance of nonoccupational sedentary behavior and health-enhancing physical activity than more traditional surveillance systems. National time use surveys could be used to retrospectively study nonoccupational sedentary and physical activity behavior over the past 5 decades.
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Purpose To test the effects of a community-based physical activity intervention designed to increase physical activity and to conduct an extensive process evaluation of the intervention. Design Quasi-experimental. Setting Two rural communities in South Carolina. One community received the intervention, and the other served as the comparison. Subjects Public school students who were in fifth grade at the start of the study (558 at baseline) were eligible to participate. A total of 436 students participated over the course of the study. Intervention The intervention included after-school and summer physical activity programs and home, school, and community components designed to increase physical activity in youth. The intervention took place over an 18-month period. Measures. Students reported after-school physical activity at three data collection points (prior to, during, and following the intervention) using the Previous Day Physical Activity Recall (PDPAR). They also completed a questionnaire designed to measure hypothesized psychosocial and environmental determinants of physical activity behavior The process evaluation used meeting records, documentation of program activities, interviews, focus groups, and heart rate monitoring to evaluate the planning and implementation of the intervention. Results There were no significant differences in the physical activity variables and few significant differences in the psychosocial variables between the intervention and comparison groups. The process evaluation indicated that the after-school and summer physical activity component of the intervention was implemented as planned, but because of resource and time limitations, the home, school, and community components were not implemented as planned. Conclusions The intervention did not have a significant effect on physical activity in the target population of children in the intervention community. This outcome is similar to that reported in other studies of community-based physical activity intervention.
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To date, a wide range of methods has been used to measure physical activity in children and adolescents. These include self-report methods such as questionnaires, activity logs, and diaries as well as objective measures of physical activity such as direct observation, doubly labeled water, heart rate monitoring, accelerometers, and pedometers. The purpose of this review is to overview the methods currently being used to measure physical activity in children and adolescents. For each measurement approach, new developments and/or innovations are identified and discussed. Particular attention is given to the use of accelerometers and the calibration of accelerometer output to units of energy expenditure to developing children.