14 resultados para Accelerometer
Resumo:
Background: Accurate assessment tools are required for the surveillance of physical activity (PA) levels and the assessment of the effect of interventions. In addition, increasing awareness of PA is often used as the first step in pragmatic behavioural interventions, as discrepancies between the amount of activity an individual perceives they do and the amount actually undertaken may act as a barrier to change. Previous research has demonstrated differences in the amount of activity individuals report doing, compared to their level of physical activity when measured with an accelerometer. Understanding the characteristics of those whose PA level is ranked differently when measured with either self-report or accelerometry is important as it may inform the choice of instrument for future research. The aim of this project was to determine which individual characteristics are associated with differences between self-reported and accelerometer measured physical activity.
Methods: Participant data from the 2009 wave of the Commuting and Health in Cambridge study were used. Quartiles of self-reported and accelerometer measured PA were derived by ranking each measure from lowest to highest. These quartiles were compared to determine whether individuals’ physical activity was ranked higher by either method. Multinomial logistic regression models were used to investigate the individual characteristics associated with different categories of mismatch.
Results: Data from 486 participants (70% female) were included in the analysis. In adjusted analyses, the physical activity of overweight or obese individuals was significantly more likely to be ranked higher by self-report than by accelerometer than that of normal-weight individuals (OR = 2.07, 95%CI = 1.28–3.34), particularly among women (OR = 3.97, 95%CI = 2.11–7.47).
Conclusions: There was a greater likelihood of mismatch between self-reported and accelerometer measured physical activity levels in overweight or obese adults. Future studies in overweight or obese adults should consider employing both methods of measurement.
Resumo:
Pavement surface profiles induce dynamic ride responses in vehicles which can potentially be used to classify road surface roughness. A novel method is proposed for the characterisation of pavement roughness through an analysis of vehicle accelerations. A combinatorial optimisation technique is applied to the determination of pavement profile heights based on measured accelerations at and above the vehicle axle. Such an approach, using low-cost inertial sensors, would provide an inexpensive alternative to the costly laser-based profile measurement vehicles. The concept is numerically validated using a half-car roll dynamic model to infer measurements of road profiles in both the left and right wheel paths.
Resumo:
This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.
Resumo:
BACKGROUND: Acute ankle sprains are usually managed functionally, with advice to undertake progressive weight-bearing and walking. Mechanical loading is an important modular of tissue repair; therefore, the clinical effectiveness of walking after ankle sprain may be dose dependent. The intensity, magnitude and duration of load associated with current functional treatments for ankle sprain are unclear.
AIM: To describe physical activity (PA) in the first week after ankle sprain and to compare results with a healthy control group.
METHODS: Participants (16-65 years) with an acute ankle sprain were randomised into two groups (standard or exercise). Both groups were advised to apply ice and compression, and walk within the limits of pain. The exercise group undertook additional therapeutic exercises. PA was measured using an activPAL accelerometer, worn for 7 days after injury. Comparisons were made with a non-injured control group.
RESULTS: The standard group were significantly less active (1.2 ± 0.4 h activity/day; 5621 ± 2294 steps/day) than the exercise (1.7 ± 0 .7 h/day, p=0.04; 7886 ± 3075 steps/day, p=0.03) and non-injured control groups (1.7 ± 0.4 h/day, p=0.02; 8844 ± 2185 steps/day, p=0.002). Also, compared with the non-injured control group, the standard and exercise groups spent less time in moderate (38.3 ± 12.7 min/day vs 14.5 ± 11.4 min/day, p=0.001 and 22.5 ± 15.9 min/day, p=0.003) and high-intensity activity (4.1 ± 6.9 min/day vs 0.1 ± 0.1 min/day, p=0.001 and 0.62 ± 1.0 min/day p=0.005).
CONCLUSION: PA patterns are reduced in the first week after ankle sprain, which is partly ameliorated with addition of therapeutic exercises. This study represents the first step towards developing evidence-based walking prescription after acute ankle sprain.
Resumo:
In this paper we present an Orientation Free Adaptive Step Detection (OFASD) algorithm for deployment in a smart phone for the purposes of physical activity monitoring. The OFASD algorithm detects individual steps and measures a user’s step counts using the smart phone’s in-built accelerometer. The algorithm considers both the variance of an individual’s walking pattern and the orientation of the smart phone. Experimental validation of the algorithm involved the collection of data from 10 participants using five phones (worn at five different body positions) whilst walking on a treadmill at a controlled speed for periods of 5 min. Results indicated that, for steps detected by the OFASD algorithm, there were no significant differences between where the phones were placed on the body (p > 0.05). The mean step detection accuracies ranged from 93.4 % to 96.4 %. Compared to measurements acquired using existing dedicated commercial devices, the results demonstrated that using a smart phone for monitoring physical activity is promising, as it adds value to an accepted everyday accessory, whilst imposing minimum interaction from the user. The algorithm can be used as the underlying component within an application deployed within a smart phone designed to promote self-management of chronic disease where activity measurement is a significant factor, as it provides a practical solution, with minimal requirements for user intervention and less constraints than current solutions.
Resumo:
Background
Feasible, cost-effective instruments are required for the surveillance of moderate-to-vigorous physical activity (MVPA) and sedentary behaviour (SB) and to assess the effects of interventions. However, the evidence base for the validity and reliability of the World Health Organisation-endorsed Global Physical Activity Questionnaire (GPAQ) is limited. We aimed to assess the validity of the GPAQ, compared to accelerometer data in measuring and assessing change in MVPA and SB.
Participants (n = 101) were selected randomly from an on-going research study, stratified by level of physical activity (low, moderate or highly active, based on the GPAQ) and sex. Participants wore an accelerometer (Actigraph GT3X) for seven days and completed a GPAQ on Day 7. This protocol was repeated for a random sub-sample at a second time point, 3–6 months later. Analysis involved Wilcoxon-signed rank tests for differences in measures, Bland-Altman analysis for the agreement between measures for median MVPA and SB mins/day, and Spearman’s rho coefficient for criterion validity and extent of change.
Results95 participants completed baseline measurements (44 females, 51 males; mean age 44 years, (SD 14); measurements of change were calculated for 41 (21 females, 20 males; mean age 46 years, (SD 14). There was moderate agreement between GPAQ and accelerometer for MVPA mins/day (r = 0.48) and poor agreement for SB (r = 0.19). The absolute mean difference (self-report minus accelerometer) for MVPA was −0.8 mins/day and 348.7 mins/day for SB; and negative bias was found to exist, with those people who were more physically active over-reporting their level of MVPA: those who were more sedentary were less likely to under-report their level of SB. Results for agreement in change over time showed moderate correlation (r = 0.52, p = 0.12) for MVPA and poor correlation for SB (r = −0.024, p = 0.916).
Levels of agreement with objective measurements indicate the GPAQ is a valid measure of MVPA and change in MVPA but is a less valid measure of current levels and change in SB. Thus, GPAQ appears to be an appropriate measure for assessing the effectiveness of interventions to promote MVPA.
Resumo:
BACKGROUND: The new generation of activity monitors allow users to upload their data to the internet and review progress. The aim of this study is to validate the Fitbit Zip as a measure of free-living physical activity.
FINDINGS: Participants wore a Fitbit Zip, ActiGraph GT3X accelerometer and a Yamax CW700 pedometer for seven days. Participants were asked their opinion on the utility of the Fitbit Zip. Validity was assessed by comparing the output using Spearman's rank correlation coefficients, Wilcoxon signed rank tests and Bland-Altman plots. 59.5% (25/47) of the cohort were female. There was a high correlation in steps/day between the Fitbit Zip and the two reference devices (r = 0.91, p < 0.001). No statistically significant difference between the Fitbit and Yamax steps/day was observed (Median (IQR) 7477 (3597) vs 6774 (3851); p = 0.11). The Fitbit measured significantly more steps/day than the Actigraph (7477 (3597) vs 6774 (3851); p < 0.001). Bland-Altman plots revealed no systematic differences between the devices.
CONCLUSIONS: Given the high level of correlation and no apparent systematic biases in the Bland Altman plots, the use of Fitbit Zip as a measure of physical activity. However the Fitbit Zip recorded a significantly higher number of steps per day than the Actigraph.
Resumo:
BACKGROUND: The impact of bronchiectasis on sedentary behaviour and physical activity is unknown. It is important to explore this to identify the need for physical activity interventions and how to tailor interventions to this patient population. We aimed to explore the patterns and correlates of sedentary behaviour and physical activity in bronchiectasis.
METHODS: Physical activity was assessed in 63 patients with bronchiectasis using an ActiGraph GT3X+ accelerometer over seven days. Patients completed: questionnaires on health-related quality-of-life and attitudes to physical activity (questions based on an adaption of the transtheoretical model (TTM) of behaviour change); spirometry; and the modified shuttle test (MST). Multiple linear regression analysis using forward selection based on likelihood ratio statistics explored the correlates of sedentary behaviour and physical activity dimensions. Between-group analysis using independent sample t-tests were used to explore differences for selected variables.
RESULTS: Fifty-five patients had complete datasets. Average daily time, mean(standard deviation) spent in sedentary behaviour was 634(77)mins, light-lifestyle physical activity was 207(63)mins and moderate-vigorous physical activity (MVPA) was 25(20)mins. Only 11% of patients met recommended guidelines. Forced expiratory volume in one-second percentage predicted (FEV1% predicted) and disease severity were not correlates of sedentary behaviour or physical activity. For sedentary behaviour, decisional balance 'pros' score was the only correlate. Performance on the MST was the strongest correlate of physical activity. In addition to the MST, there were other important correlate variables for MVPA accumulated in ≥10-minute bouts (QOL-B Social Functioning) and for activity energy expenditure (Body Mass Index and QOL-B Respiratory Symptoms).
CONCLUSIONS: Patients with bronchiectasis demonstrated a largely inactive lifestyle and few met the recommended physical activity guidelines. Exercise capacity was the strongest correlate of physical activity, and dimensions of the QOL-B were also important. FEV1% predicted and disease severity were not correlates of sedentary behaviour or physical activity. The inclusion of a range of physical activity dimensions could facilitate in-depth exploration of patterns of physical activity. This study demonstrates the need for interventions targeted at reducing sedentary behaviour and increasing physical activity, and provides information to tailor interventions to the bronchiectasis population.
Resumo:
Background: Workplace sedentary behaviour is a priority target for health promotion. However, little is known about how to effect change. We aimed to explore desk-based office workers’ perceptions of factors that influenced sedentary behaviour at work and to explore the feasibility of using a novel mobile phone application to track their behaviours.
Methods: We invited office employees (n = 12) and managers (n = 2) in a software engineering company to participate in semi-structured interviews to explore perceived barriers and facilitators affecting workplace sedentary behaviour. We assessed participants’ sedentary behaviours using an accelerometer before and after they used a mobile phone application to record their activities at self-selected time intervals daily for 2 weeks. Interviews were analysed using a thematic framework.
Results: Software engineers (5 employees; 2 managers) were interviewed; 13 tested the mobile phone application; 8 returned feedback. Major barriers to reducing workplace sedentary behaviour included the pressure of ‘getting the job done’, the nature of their work requiring sitting at a computer, personal preferences for the use of time at and after work, and a lack of facilities, such as a canteen, to encourage moving from their desks. Facilitators for reduced sedentariness included having a definite reason to leave their desks, social interaction and relief of physical and mental symptoms of prolonged sitting. The findings were similar for participants with different levels of overall physical activity. Valid accelerometer data were tracked for four participants: all reduced their sedentary behaviour. Participants stated that recording data using the phone application added to their day’s work but the extent to which individuals perceived this as a burden varied and was counter-balanced by its perceived value in increasing awareness of sedentary behaviour. Individuals expressed a wish for flexibility in its configuration.
Conclusions: These findings indicate that employers’ and employees’ perceptions of the cultural context and physical environment of their work, as well as personal factors, must be considered in attempting to effect changes that reduce workplace sedentary behaviour. Further research should investigate appropriate individually tailored approaches to this challenge, using a framework of behaviour change theory which takes account of specific work practices, preferences and settings.
Resumo:
BACKGROUND: The transtheoretical model has been successful in promoting health behavior change in general and clinical populations. However, there is little knowledge about the application of the transtheoretical model to explain physical activity behavior in individuals with non-cystic fibrosis bronchiectasis. The aim was to examine patterns of (1) physical activity and (2) mediators of behavior change (self-efficacy, decisional balance, and processes of change) across stages of change in individuals with non-cystic fibrosis bronchiectasis.
METHODS: Fifty-five subjects with non-cystic fibrosis bronchiectasis (mean age ± SD = 63 ± 10 y) had physical activity assessed over 7 d using an accelerometer. Each component of the transtheoretical model was assessed using validated questionnaires. Subjects were divided into groups depending on stage of change: Group 1 (pre-contemplation and contemplation; n = 10), Group 2 (preparation; n = 20), and Group 3 (action and maintenance; n = 25). Statistical analyses included one-way analysis of variance and Tukey-Kramer post hoc tests.
RESULTS: Physical activity variables were significantly (P < .05) higher in Group 3 (action and maintenance) compared with Group 2 (preparation) and Group 1 (pre-contemplation and contemplation). For self-efficacy, there were no significant differences between groups for mean scores (P = .14). Decisional balance cons (barriers to being physically active) were significantly lower in Group 3 versus Group 2 (P = .032). For processes of change, substituting alternatives (substituting inactive options for active options) was significantly higher in Group 3 versus Group 1 (P = .01), and enlisting social support (seeking out social support to increase and maintain physical activity) was significantly lower in Group 3 versus Group 2 (P = .038).
CONCLUSIONS: The pattern of physical activity across stages of change is consistent with the theoretical predictions of the transtheoretical model. Constructs of the transtheoretical model that appear to be important at different stages of change include decisional balance cons, substituting alternatives, and enlisting social support. This study provides support to explore transtheoretical model-based physical activity interventions in individuals with non-cystic fibrosis bronchiectasis.
Resumo:
BACKGROUND: Research on wild animal ecology is increasingly employing GPS telemetry in order to determine animal movement. However, GPS systems record position intermittently, providing no information on latent position or track tortuosity. High frequency GPS have high power requirements, which necessitates large batteries (often effectively precluding their use on small animals) or reduced deployment duration. Dead-reckoning is an alternative approach which has the potential to 'fill in the gaps' between less resolute forms of telemetry without incurring the power costs. However, although this method has been used in aquatic environments, no explicit demonstration of terrestrial dead-reckoning has been presented.
RESULTS: We perform a simple validation experiment to assess the rate of error accumulation in terrestrial dead-reckoning. In addition, examples of successful implementation of dead-reckoning are given using data from the domestic dog Canus lupus, horse Equus ferus, cow Bos taurus and wild badger Meles meles.
CONCLUSIONS: This study documents how terrestrial dead-reckoning can be undertaken, describing derivation of heading from tri-axial accelerometer and tri-axial magnetometer data, correction for hard and soft iron distortions on the magnetometer output, and presenting a novel correction procedure to marry dead-reckoned paths to ground-truthed positions. This study is the first explicit demonstration of terrestrial dead-reckoning, which provides a workable method of deriving the paths of animals on a step-by-step scale. The wider implications of this method for the understanding of animal movement ecology are discussed.
Resumo:
Background: The European badger (Melesmeles) is involved in the maintenance of bovine tuberculosis infection and onward spread to cattle. However, little is known about how transmission occurs. One possible route could be through direct contact between infected badgers and cattle. It is also possible that indirect contact between cattle and infected badger excretory products such as faeces or urine may occur either on pasture or within and around farm buildings. A better understanding of behaviour patterns in wild badgers may help to develop biosecurity measures to minimise direct and indirect contact between badgers and cattle. However, monitoring the behaviour of free-ranging badgers can be logistically challenging and labour intensive due to their nocturnal and semi-fossorial nature.We trialled a GPS and tri-axial accelerometer-equipped collar on a free-ranging badger to assess its potential value to elucidate behaviour-time budgets and functional habitat use. Results: During the recording period between 16:00 and 08:00 on a single night, resting was the most commonly identified behaviour (67.4%) followed by walking (20.9%), snuffling (9.5%) and trotting (2.3%).When examining accelerometer data associated with each GPS fix and habitat type (occurring 2 min 30 s before and after), walking was themost common behaviour in woodland (40.3%) and arable habitats (53.8%), while snuffling was themost common behaviour in pasture (61.9%). Several nocturnal resting periods were also observed. The total distance travelled was 2.28 km. Conclusions: In the present report, we demonstrate proof of principle in the application of a combined GPS and accelerometer device to collect detailed quantitative data on wild badger behaviour. Behaviour-time budgets allow us to investigate how badgers allocate energy to different activities and how thismight change with disease status. Such information could be useful in the development of measures to reduce opportunities for onward transmission of bovine tuberculosis from badgers to cattle.
Resumo:
The popularity of tri-axial accelerometer data loggers to quantify animal activity through the analysis of signature traces is increasing. However, there is no consensus on how to process the large data sets that these devices generate when recording at the necessary high sample rates. In addition, there have been few attempts to validate accelerometer traces with specific behaviours in non-domesticated terrestrial mammals.
Resumo:
BACKGROUND:
Acute ankle sprains are usually managed functionally, with advice to undertake progressive weight-bearing and walking. Mechanical loading is an important modular of tissue repair; therefore, the clinical effectiveness of walking after ankle sprain may be dose dependent. The intensity, magnitude and duration of load associated with current functional treatments for ankle sprain are unclear.
AIM:
To describe physical activity (PA) in the first week after ankle sprain and to compare results with a healthy control group.
METHODS:
Participants (16-65 years) with an acute ankle sprain were randomised into two groups (standard or exercise). Both groups were advised to apply ice and compression, and walk within the limits of pain. The exercise group undertook additional therapeutic exercises. PA was measured using an activPAL accelerometer, worn for 7 days after injury. Comparisons were made with a non-injured control group.
RESULTS:
The standard group were significantly less active (1.2 ± 0.4 h activity/day; 5621 ± 2294 steps/day) than the exercise (1.7 ± 0 .7 h/day, p=0.04; 7886 ± 3075 steps/day, p=0.03) and non-injured control groups (1.7 ± 0.4 h/day, p=0.02; 8844 ± 2185 steps/day, p=0.002). Also, compared with the non-injured control group, the standard and exercise groups spent less time in moderate (38.3 ± 12.7 min/day vs 14.5 ± 11.4 min/day, p=0.001 and 22.5 ± 15.9 min/day, p=0.003) and high-intensity activity (4.1 ± 6.9 min/day vs 0.1 ± 0.1 min/day, p=0.001 and 0.62 ± 1.0 min/day p=0.005).
CONCLUSION:
PA patterns are reduced in the first week after ankle sprain, which is partly ameliorated with addition of therapeutic exercises. This study represents the first step towards developing evidence-based walking prescription after acute ankle sprain.