Search results for "accelerometer data"
showing 10 items of 11 documents
Training Volume and Intensity of Physical Activity among Young Athletes: The Health Promoting Sports Club (HPSC) Study
2019
Both training volume and overall physical activity (PA) play a role in young athletes’ sports performance and athletic development. The purpose of this study was to describe the training volume and PA of young athletes in endurance, aesthetics, ball games, and power sports. Questionnaire data (n = 671) were obtained from 15-year-old Finnish athletes on sports participation, along with accelerometer data (n = 350) assessing the amount and intensity of their PA. The athletes’ mean weekly training volume was 11 h 41 min. Objectively assessed PA amounted to 4 h 31 min daily, out of which 1 h 31 min was at a level of moderate-to-vigorous intensity (MVPA). Among 24% of the athletes, the weekly tr…
Physical Activity Level Following Resistance Training in Community-Dwelling Older Adults Receiving Home Care: Results from a Cluster-Randomized Contr…
2021
Older adults’ physical activity (PA) is low. We examined whether eight months of resistance training increased PA level in community-dwelling older adults receiving home care. A two-armed cluster-randomized trial using parallel groups was conducted. The included participants were >
Patterns of objectively measured sedentary time in 10- to 12-year-old Belgian children: an observational study within the ENERGY-project
2017
Background This study examined the frequency of and differences in sedentary bouts of different durations and the total time spent in sedentary bouts on a weekday, a weekend day, during school hours, during after-school hours and in the evening period in a sample of 10- to 12-year-old Belgian children. Methods Accelerometer data were collected as part of the ENERGY-project in Belgium (n = 577, 10.9 ± 0.7 years, 53% girls) in 2011. Differences in total sedentary time, sedentary bouts of 2–5, 5–10, 10–20, 20–30 and ≥30 min and total time accumulated in those bouts were examined on a weekday, a weekend day, during school hours, during after-school hours and in the evening period, using multile…
Deep Learning for Classifying Physical Activities from Accelerometer Data
2021
Physical inactivity increases the risk of many adverse health conditions, including the world’s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are minimal medical care and personal trainers’ methods to monitor a patient’s actual physical activity types. To improve activity monitoring, we propose an artificial-intelligence-based approach to classify the physical movement activity patterns. In more detail, we employ two deep learning (DL) methods, namely a deep feed-forward neural network (DNN) and a deep recurrent neural network (RNN) for this purpose. We evaluate the proposed models on two phy…
Experiences from a wearable-mobile acquisition system for ambulatory assessment of diet and activity
2017
Public health trends are currently monitored and diagnosed based on large studies that often rely on pen-and-paper data methods that tend to require a large collection campaign. With the pervasiveness of smart-phones and -watches throughout the general population, we argue in this paper that such devices and their built-in sensors can be used to capture such data more accurately with less of an effort. We present a system that targets a pan-European and harmonised architecture, using smartphones and wrist-worn activity loggers to enable the collection of data to estimate sedentary behavior and physical activity, plus the consumption of sugar-sweetened beverages. We report on a unified pilot…
Adaptive Vehicle Mode Monitoring Using Embedded Devices with Accelerometers
2012
Monitoring of specific attributes such as vehicle speed and fuel consumption as well as cargo safety is an important problem for transport domain. This task is performed using specific multiagent monitoring systems. To ensure secure operation of such systems they should have autonomous and adaptive behaviour.
The UP4FUN intervention effect on overall sedentary time and breaking up sedentary time in Belgian children (10–12 years): The ENERGY-project
2014
Introduction Within the ENERGY-project [1] , a school-based intervention to reduce and to break up sedentary time (UP4FUN) was developed for children aged 10 to 12 years. This study examined the UP4FUN intervention effect on objectively measured overall sedentary time and sedentary pattern variables among Belgian children. Sedentary pattern variables included number of breaks in sedentary time, number of sedentary bouts (≥ 10 minutes) and total and average amount of time spent in those sedentary bouts. Methods The six weeks intervention was tested in a randomized controlled trial with pre-test post-test design with five intervention and five control schools in Belgium. The total sample incl…
Weekday and weekend sedentary time and physical activity in differentially active children
2015
To investigate whether weekday-weekend differences in sedentary time and specific intensities of physical activity exist among children categorised by physical activity levels.Cross-sectional observational study.Seven-day accelerometer data were obtained from 810 English children (n=420 girls) aged 10-11 years. Daily average minday(-1) spent in moderate to vigorous physical activity were calculated for each child. Sex-specific moderate to vigorous physical activity quartile cut-off values categorised boys and girls separately into four graded groups representing the least (Q1) through to the most active (Q4) children. Sex- and activity quartile-specific multilevel linear regression analyses…
A new algorithm for the identification of dives reveals the foraging ecology of a shallow-diving seabird using accelerometer data
2017
International audience; The identification of feeding events is crucial to our understanding of the foraging ecology of seabirds. Technology has made small devices, such as time-depth recorders (TDRs) and accelerometers available. However, TDRs might not be sensitive enough to identify shallow dives, whereas accelerometers might reveal more subtle behaviours at a smaller temporal scale. Due to the limitations of TDRs, the foraging ecology of many shallow-diving seabirds has been poorly investigated to date. We thus developed an algorithm to identify dive events in a shallow-diving seabird species, the Scopoli’s shearwater, using only accelerometer data. The accuracy in the identification of…
Definitions, measurement and prevalence of sedentary behaviour in adults with intellectual disabilities – a systematic review
2017
Supporting positive change in lifestyle behaviours is a priority in tackling the health inequalities experienced by adults with intellectual disabilities. In this systematic review, we examine the evidence on the definition, measurement and epidemiology of sedentary behaviour of adults with intellectual disabilities. A systematic literature search of PUBMED, EMBASE, MEDLINE and Google Scholar was performed to identify studies published from 1990 up to October 2015. Nineteen papers met the criteria for inclusion in the systematic review. Many researchers do not distinguish between insufficient physical activity and sedentary behaviour. None of the studies reported the reliability and validit…