965 resultados para arm activity monitoring


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The climatic conditions of tropical and subtropical regions within Australia present, at times, extreme risk of physical activity induced heat illness. Many administrators and teachers in school settings are aware of the general risks of heat related illness. In the absence of reliable information applied at the local level, there is a risk that inappropriate decisions may be made concerning school events that incorporate opportunities to be physically active. Such events may be prematurely cancelled resulting in the loss of necessary time for physical activity. Under high or extremely high risk conditions however, the absence of appropriate modifications or continuation could place the health of students, staff and other parties at risk. School staff and other key stakeholders should understand the mechanisms of escalating risk and be supported to undertake action to reduce the level of risk through appropriate policies, procedures, resources and action plans.

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Obesity rates are increasing in children of all ages, and reduced physical activity (PA) is a likely contributor to this trend. Little is known about the physical activity behavior of preschool-age children, or about the influence of preschool attendance on physical activity. Purpose The purpose of this study was to quantify the physical activity levels of children attending a center-based half-day preschool program. Methods Forty-two 3-to-5-year old children (Mean age = 4.0 ± 0.7, 54.8% Male, Mean BMI = 16.5 ± 5.5, Mean BMI %tile = 52.1 ± 33.5) from four class groups (two morning and two afternoon), wore an Actigraph 7164 accelerometer for the entire halfday program (including classroom learning experiences, snack and recess time) 2 times per week, for 10 weeks (20 activity monitoring records in total). Activity counts for each 5-sec interval were uploaded to a customized data reduction program to determine total counts, minutes of moderate PA (MPA) (3–5.9 METs), and minutes of vigorous PA (VPA) (> = 6 METs) per session. Counts were categorized as either MPA or VPA using the cutpoints developed by Sirard and colleagues (2001). Results Across the four 2.5 hour programs, the average MPA, VPA and total counts (× 103) were 12.4 ± 3.1 minutes, 18.3 ± 4.6 minutes, and 171.1 ± 29.7 counts, respectively. Thus, on average, children accumulated just over 12 minutes of moderateto-vigorous PA per hour of program attendance. The PA variables did not differ significantly by gender, weight status, or time of day. There were, however, significant age differences, with 3-year-olds exhibiting significantly less PA than their 4- and 5-year-old counterparts. Conclusions These results suggest that young children are relatively lowactive while attending preschool. Accordingly, interventions to increase movement opportunities during the preschool day are warranted.

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In the Public Health White Paper "Healthy Lives, Healthy People" (2010), the UK Government emphasised using incentives and "nudging" to encourage positive, healthy behaviour changes. However, there is little evidence that nudging is effective, in particular for increasing physical activity. We have created a platform to research the effectiveness of health-related behaviour change interventions and incentive schemes. The system consists of an outward-facing website, incorporating tools for incentivizing behaviour change, and a novel physical activity monitoring system. The monitoring system consists of the "Physical Activity Loyalty Card", which contains a passive RFID tag, and a contactless sensor network to detect the cards. This paper describes the application of this novel web-based system to investigate the effectiveness of non-cash incentives to "nudge" adults to undertake more physical activity. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

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Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

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  Remote human activity monitoring is critical and essential in physiotherapy with respect to the skyrocketing healthcare expenditure and the fast aging population. One of frequently used method to monitor human activity is wearing inertial sensors since it is low-cost and accurate. However, the measurements of those sensors are able only to estimate the orientation and rotation angles with respect to actual movement angles, because of differences in the body’s co-ordination system and the sensor’s co-ordination system. There were numerous studies being conducted to improve the accuracy of estimation, though there is potential for further discussions on improving accuracy by replacing heavy algorithms to less complexity. This research is an attempt to propose an adaptive complementary filter for identifying human upper arm movements. Further, this article discusses a feasibility of upper arm rehabilitation using the proposed adaptive complementary filter and inertial measurement sensors. The proposed algorithm is tested with four healthy subjects wearing an inertial sensor against gold standard, which is the VICON system. It demonstrated root mean squared error of 8.77◦ for upper body limb orientation estimation when compared to gold standard VICON optical motion capture system.

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Stroke is a common neurological condition which is becoming increasingly common as the population ages. This entails healthcare monitoring systems suitable for home use, with remote access for medical professionals and emergency responders. The mobile phone is becoming the easy access tool for self-evaluation of health, but it is hindered by inherent problems including computational power and storage capacity. This research proposes a novel cloud based architecture of a biomedical system for a wearable motion kinematic analysis system which mitigates the above mentioned deficiencies of mobile devices. The system contains three subsystems: 1. Bio Kin WMS for measuring the acceleration and rotation of movement 2. Bio Kin Mobi for Mobile phone based data gathering and visualization 3. Bio Kin Cloud for data intensive computations and storage. The system is implemented as a web system and an android based mobile application. The web system communicates with the mobile application using an encrypted data structure containing sensor data and identifiable headings. The raw data, according to identifiable headings, is stored in the Amazon Relational Database Service which is automatically backed up daily. The system was deployed and tested in Amazon Web Services.

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BACKGROUND: Online, self-guided programs exist for a wide range of mental health conditions, including bipolar disorder, and discussion boards are often part of these interventions. The impact engagement with these discussion boards has on the psychosocial well-being of users is largely unknown. More specifically we need to clarify the influence of the type and level of engagement on outcomes. The primary aim of this exploratory study is to determine if there is a relationship between different types (active, passive or none) and levels (high, mid and low) of discussion board engagement and improvement in outcome measures from baseline to follow up, with a focus on self-reported social support, stigma, quality of life and levels of depression and mania. The secondary aim of this study is to identify any differences in demographic variables among discussion users.

METHODS/DESIGN: The present study is a sub-study of the MoodSwings 2.0 3-arm randomised controlled trial (discussion board only (arm 1), discussion board plus psychoeducation (arm 2), discussion board, psychoeducation plus cognitive behavioural therapy-based tools (arm 3)). Discussion engagement will be measured via online participant activity monitoring. Assessments include online self-report as well as blinded phone interviews at baseline, 3, 6, 9 and 12 months follow up.

DISCUSSION: The results of this study will help to inform future programs about whether or not discussion boards are a beneficial inclusion in online self-help interventions. It will also help to determine if motivating users to actively engage in online discussion is necessary, and if so, what level of engagement is optimal to produce the most benefit. Future programs may benefit through being able to identify those most likely to poorly engage, based on demographic variables, so motivational strategies can be targeted accordingly.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Objetivo: Evaluar las propiedades psicométricas de los instrumentos para la medición de la actividad física en adultos de 18-65 años con discapacidad física por lesión de médula espinal. Materiales y métodos: Revisión sistemática. Las bases de datos de Medline, Scopus, Web of Science y 19 revistas especializadas fueron consultadas durante once días entre abril de 2015 y febrero de 2016 para identificar estudios originales de validación, sin límite de tiempo y que estuvieran publicados en español, francés y/o inglés. La calidad metodológica de los instrumentos de medición se evaluó usando las diferentes cajas de propiedades de la lista COSMIN. Resultados: Se identificaron 9229 referencias, de las cuales sólo 12 cumplieron los criterios de inclusión, dando como resultado 13 instrumentos de medición. Se evaluaron seis propiedades psicométricas. La propiedad más común fue la confiabilidad, además se observó que la calidad metodológica de los estudios incluidos no representa los resultados de las propiedades psicométricas de los instrumentos de medición. La calidad metodológica de los instrumentos para la evaluación de la actividad física en población con lesión medular espinal es “baja” para propiedades como consistencia interna, error de medición, sensibilidad, validez de criterio (con excepción del WISCI II que tiene buena validez) y excelente para validez de contenido y fiabilidad. Conclusión: Se ha encontrado que instrumentos empleados hasta el presente en la medición de la actividad física en población con discapacidad física relacionada con lesión de médula espinal han sido creados para otros tipos de discapacidad y otros instrumentos deben ser validados en futuros estudios.

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Purpose - This paper seeks to examine the complex relationships between urban planning, infrastructure management, sustainable urban development, and to illustrate why there is an urgent need for local governments to develop a robust planning support system which integrates with advance urban computer modelling tools to facilitate better infrastructure management and improve knowledge sharing between the community, urban planners, engineers and decision makers. Design/methodology/approach - The methods used in this paper includes literature review and practical project case observations. Originality/value - This paper provides an insight of how the Brisbane's planning support system established by Brisbane City Council has significantly improved the effectiveness of urban planning, infrastructure management and community engagement through better knowledge management processes. Practical implications - This paper presents a practical framework for setting up a functional planning support system within local government. The integration of the Brisbane Urban Growth model, Virtual Brisbane and the Brisbane Economic Activity Monitoring (BEAM) database have proven initially successful to provide a dynamic platform to assist elected officials, planners and engineers to understand the limitations of the local environment, its urban systems and the planning implications on a city. With the Brisbane's planning support system, planners and decision makers are able to provide better planning outcomes, policy and infrastructure that adequately address the local needs and achieve sustainable spatial forms.

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Regular physical activity is an important component of a healthy lifestyle in children and adolescents. However, despite the noted short- and long-term health benefits associated with physical activity, monitoring and surveillance studies show that a significant percentage of children and adolescents fail to meet the recommended guideline of 60 minutes or more of moderate-to-vigorous physical activity daily. This review examines key evidence from the public health and health promotion literature on promotion of health-enhancing physical activity in children and adolescents. We describe best practice in three key behavior settings—schools, homes, and health care settings. In school-based settings, it has been shown that physical education programs can be modified to increase the percentage of class time engaged in moderate-to-vigorous physical activity. In the home setting, there is evidence that teaching parents to establish and monitor physical activity goals and provide appropriate rewards for meeting these goals results in gains in physical activity and/or physical fitness. In health care settings, evidence from two studies suggests that physician-based counseling coupled with stage appropriate written materials can be effective among adolescent youth.

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This work brings a perspective from an employer-sponsored health and wellness program called Global Corporate Challenge (GCC) to the 'quantified self' research. We present preliminary findings from a study with 17 university employees who participated in the GCC. We aimed to explore how participants derived meaningfulness from their self-tracking experiences. Our findings echo the growing body of work that advocates for conceptualizing activity tracking beyond the rationalistic, data-oriented perspectives and supporting more social and lived experiences.

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Phosphine resistance alleles might be expected to negatively affect energy demanding activities such as walking and flying, because of the inverse relationship between phosphine resistance and respiration. We used an activity monitoring system to quantify walking of Rhyzopertha dominica (F.) and a flight chamber to estimate their propensity for flight initiation. No significant difference in the duration of walking was observed between the strongly resistant, weakly resistant, and susceptible strains of R. dominica we tested, and females walked significantly more than males regardless of genotype. The walking activity monitor revealed no pattern of movement across the day and no particular time of peak activity despite reports of peak activity of R. dominica and Tribolium castaneum (Herbst) under field conditions during dawn and dusk. Flight initiation was significantly higher for all strains at 28 degrees C and 55% relative humidity than at 25, 30, 32, and 35 degrees C in the first 24 h of placing beetles in the flight chamber. Food deprivation and genotype had no significant effect on flight initiation. Our results suggest that known resistance alleles in R. dominica do not affect insect mobility and should therefore not inhibit the dispersal of resistant insects in the field.

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In this paper we explore ways to address the issue of dataset bias in person re-identification by using data augmentation to increase the variability of the available datasets, and we introduce a novel data augmentation method for re-identification based on changing the image background. We show that use of data augmentation can improve the cross-dataset generalisation of convolutional network based re-identification systems, and that changing the image background yields further improvements.