Comparing the validity and output of the GT1M and GT3X accelerometer in 5- to 9-year-old children

The purpose of this study was to compare the validity and output of the biaxial ActiGraph GT1M and the triaxial GT3X (ActiGraph, LLC, Pensacola, FL, USA)accelerometer in 5- to 9-year-old children. Thirty-two children wore the two monitors while their energy expenditure was measured with indirect calorimetry. They performed four locomotor and four play activities in an exercise laboratory and were further measured during 12 minutes of a sports lesson. Validity evidence in relation to indirect calorimetry was examined with linear regression equations applied to the laboratory data. During the sports lessons predicted energy expenditure according to the regression equations was compared to measured energy expenditure with the Wilcoxon-signed rank test and the Spearman correlation. To compare the output, agreement between counts of the two monitors during the laboratory activities was assessed with Bland-Altman plots. The evidence of validity was similar for both monitors. Agreement between the output of the two monitors was good for vertical counts (mean bias = −14 ± 22 counts) but not for horizontal counts (−17 ± 32 counts). The current results indicate that the two accelerometer models are able to estimate energy expenditure of a range of physical activities equally well in young children. However, they show output differences for movement in the horizontal direction.

Development and validation of energy expenditure prediction models based on GT3X accelerometer data in 5- to 9-year-old children

Background: Accelerometry has been established as an objective method that can be used to assess physical activity behavior in large groups. The purpose of the current study was to provide a validated equation to translate accelerometer counts of the triaxial GT3X into energy expenditure in young children. Methods: Thirty-two children aged 5–9 years performed locomotor and play activities that are typical for their age group. Children wore a GT3X accelerometer and their energy expenditure was measured with indirect calorimetry. Twenty-one children were randomly selected to serve as development group. A cubic 2-regression model involving separate equations for locomotor and play activities was developed on the basis of model fit. It was then validated using data of the remaining children and compared with a linear 2-regression model and a linear 1-regression model. Results: All 3 regression models produced strong correlations between predicted and measured MET values. Agreement was acceptable for the cubic model and good for both linear regression approaches. Conclusions: The current linear 1-regression model provides valid estimates of energy expenditure for ActiGraph GT3X data for 5- to 9-year-old children and shows equal or better predictive validity than a cubic or a linear 2-regression model.

Development and validation of GT3X accelerometer cut-off points in 5- to 9-year-old children based on indirect calorimetry measurements

The ActiGraph accelerometer is commonly used to measure physical activity in children. Count cut-off points are needed when using accelerometer data to determine the time a person spent in moderate or vigorous physical activity. For the GT3X accelerometer no cut-off points for young children have been published yet. The aim of the current study was thus to develop and validate count cut-off points for young children. Thirty-two children aged 5 to 9 years performed four locomotor and four play activities. Activity classification into the light-, moderate- or vigorous-intensity category was based on energy expenditure measurements with indirect calorimetry. Vertical axis as well as vector magnitude cut-off points were determined through receiver operating characteristic curve analyses with the data of two thirds of the study group and validated with the data of the remaining third. The vertical axis cut-off points were 133 counts per 5 sec for moderate to vigorous physical activity (MVPA), 193 counts for vigorous activity (VPA) corresponding to a metabolic threshold of 5 MET and 233 for VPA corresponding to 6 MET. The vector magnitude cut-off points were 246 counts per 5 sec for MVPA, 316 counts for VPA - 5 MET and 381 counts for VPA - 6 MET. When validated, the current cut-off points generally showed high recognition rates for each category, high sensitivity and specificity values and moderate agreement in terms of the Kappa statistic. These results were similar for vertical axis and vector magnitude cut-off points. The current cut-off points adequately reflect MVPA and VPA in young children. Cut-off points based on vector magnitude counts did not appear to reflect the intensity categories better than cut-off points based on vertical axis counts alone.

Reactivity to Accelerometer Measurement of Children and Adolescents

PURPOSE: Awareness of being monitored can influence participants' habitual physical activity (PA) behavior. This reactivity effect may threaten the validity of PA assessment. Reports on reactivity when measuring the PA of children and adolescents have been inconsistent. The aim of this study was to investigate whether PA outcomes measured by accelerometer devices differ from measurement day to measurement day and whether the day of the week and the day on which measurement started influence these differences. METHODS: Accelerometer data (counts per minute [cpm]) of children and adolescents (n = 2081) pooled from eight studies in Switzerland with at least 10 h of daily valid recording were investigated for effects of measurement day, day of the week, and start day using mixed linear regression. RESULTS: The first measurement day was the most active day. Counts per minute were significantly higher than on the second to the sixth day, but not on the seventh day. Differences in the age-adjusted means between the first and consecutive days ranged from 23 to 45 cpm (3.6%-7.1%). In preschoolchildren, the differences almost reached 10%. The start day significantly influenced PA outcome measures. CONCLUSIONS: Reactivity to accelerometer measurement of PA is likely to be present to an extent of approximately 5% on the first day and may introduce a relevant bias to accelerometer-based studies. In preschoolchildren, the effects are larger than those in elementary and secondary schoolchildren. As the day of the week and the start day significantly influence PA estimates, researchers should plan for at least one familiarization day in school-age children and randomly assign start days.

Accelerometry and Energy Expenditure in Obese Adults and Normal Weight Controls

Objective: To evaluate a new triaxial accelerometer device for prediction of energy expenditure, measured as VO2/kg, in obese adults and normal-weight controls during activities of daily life. Subjects and methods: Thirty-seven obese adults (Body Mass Index (BMI) 37±5.4) and seventeen controls (BMI 23±1.8) performed eight activities for 5 to 8 minutes while wearing a triaxial accelerometer on the right thigh. Simultaneously, VO2 and VCO2 were measured using a portable metabolic system. The relationship between accelerometer counts (AC) and VO2/kg was analysed using spline regression and linear mixed-effects models. Results: For all activities, VO2/kg was significantly lower in obese participants than in normalweight controls. A linear relationship between AC and VO2/kg existed only within accelerometer values from 0 to 300 counts/min, with an increase of 3.7 (95%-confidence interval (CI) 3.4 - 4.1) and 3.9 ml/min (95%-CI 3.4 - 4.3) per increase of 100 counts/min in obese and normal-weight adults, respectively. Linear modelling of the whole range yields wide prediction intervals for VO2/kg of ± 6.3 and ±7.3 ml/min in both groups. Conclusion: In obese and normal-weight adults, the use of AC for predicting energy expenditure, defined as VO2/kg, from a broad range of physical activities, characterized by varying intensities and types of muscle work, is limited.

Neuromechanical gait adaptations in women with joint hypermobility - an exploratory study

BACKGROUND Joint hypermobility is known to be associated with joint and muscle pain, joint instability and osteoarthritis. Previous work suggested that those individuals present an altered neuromuscular behavior during activities such as level walking. Therefore, the aim of this study was to explore the differences in ground reaction forces, temporal parameters and muscle activation patterns during gait between normomobile and hypermobile women, including symptomatic and asymptomatic hypermobile individuals. METHODS A total of 195 women were included in this cross-sectional study, including 67 normomobile (mean 24.8 [SD 5.4] years) and 128 hypermobile (mean 25.8 [SD 5.4] years), of which 56 were further classified as symptomatic and 47 as asymptomatic. The remaining 25 subjects could not be further classified. Ground reaction forces and muscle activation from six leg muscles were measured while the subjects walked at a self-selected speed on an instrumented walkway. Temporal parameters were derived from ground reaction forces and a foot accelerometer. The normomobile and hypermobile groups were compared using independent samples t-tests, whereas the normomobile, symptomatic and asymptomatic hypermobile groups were compared using one-way ANOVAs with Tukey post-hoc tests (significance level=0.05). FINDINGS Swing phase duration was higher among hypermobile (P=0.005) and symptomatic hypermobile (P=0.018) compared to normomobile women. The vastus medialis (P=0.049) and lateralis (P=0.030) and medial gastrocnemius (P=0.011) muscles showed higher mean activation levels during stance in the hypermobile compared to the normomobile group. INTERPRETATION Hypermobile women might alter their gait pattern in order to stabilize their knee joint.

Relationship between the objectively-assessed neighborhood area and activity behavior in Swiss youth

Background Neighborhood attributes are modifiable determinants of physical activity (PA) and sedentary behavior (SB). We tested whether the objectively-assessed built and social environment was associated with PA and SB in Swiss youth and whether sex, age and the socioeconomic position (Swiss-SEP) modified such associations. Methods We combined data of 1742 youth (ages 4 to 17) from seven studies conducted within Switzerland between 2005–2010. All youth provided accelerometer data and a home address, which was linked to objective environmental data and the Swiss-SEP-index. Associations between neighborhood attributes and PA were analyzed by multivariable multilevel regression analyses. Results The extent of green areas and building density was positively associated with PA in the total sample (p < 0.05). Factors representing centrally located areas, and more schoolchildren living nearby tended to increase PA in secondary schoolchildren, boys and those from lower-ranked socioeconomic areas. In primary schoolchildren, the extent of green areas was positively associated with PA (p = 0.05). Associations between neighborhood attributes and PA were more pronounced in youth from low socioeconomic areas. Conclusions The results indicate that some associations between neighborhood attributes and PA differ by age, sex and socioeconomic area. This should be taken into account when planning interventions to increase childhood PA.

Dyadic action control in overweight and obese couples: Effectiveness of a randomized controlled trial to promote physical activity.

BACKGROUND: Enhancing physical activity in overweight and obese individuals is an important means to promote health in this target population. The Health Action Process Approach (HAPA), which was the theoretical framework of this study, focuses on individual self-regulation variables for successful health behavior change. One key self-regulation variable of this model is action control with its three subfacets awareness of intentions, self-monitoring and regulatory effort. The social context of individuals, however, is usually neglected in common health behavior change theories. In order to integrate social influences into the HAPA, this randomized controlled trial investigated the effectiveness of a dyadic conceptualization of action control for promoting physical activity. METHODS/DESIGN: This protocol describes the design of a single-blind randomized controlled trial, which comprises four experimental groups: a dyadic action control group, an individual action control group and two control groups. Participants of this study are overweight or obese, heterosexual adult couples who intend to increase their physical activity. Blocking as means of a gender-balanced randomization is used to allocate couples to conditions and partners to either being the target person of the intervention or to the partner condition. The ecological momentary intervention takes place in the first 14 days after baseline assessment and is followed by another 14 days diary phase without intervention. Follow-ups are one month and six months later. Subsequent to the six-months follow-up another 14 days diary phase takes place.The main outcome measures are self-reported and accelerometer-assessed physical activity. Secondary outcome measures are Body Mass Index (BMI), aerobic fitness and habitual physical activity. DISCUSSION: This is the first study examining a dyadic action control intervention in comparison to an individual action control condition and two control groups applying a single-blind randomized control trial. Challenges with running couples studies as well as advantages and disadvantages of certain design-related decisions are discussed. This RCT was funded by the Swiss National Science Foundation (PP00P1_133632/1) and was registered on 27/04/2012 at http://www.isrctn.com/ISRCTN15705531.

A Dyadic Action Control Trial in Overweight and Obese Couples (DYACTIC)

BACKGROUND: Enhancing physical activity in overweight and obese individuals is an important means to promote health in this target population. The Health Action Process Approach (HAPA), which was the theoretical framework of this study, focuses on individual self-regulation variables for successful health behavior change. One key self-regulation variable of this model is action control with its three subfacets awareness of intentions, self-monitoring and regulatory effort. The social context of individuals, however, is usually neglected in common health behavior change theories. In order to integrate social influences into the HAPA, this randomized controlled trial investigated the effectiveness of a dyadic conceptualization of action control for promoting physical activity. METHODS/DESIGN: This protocol describes the design of a single-blind randomized controlled trial, which comprises four experimental groups: a dyadic action control group, an individual action control group and two control groups. Participants of this study are overweight or obese, heterosexual adult couples who intend to increase their physical activity. Blocking as means of a gender-balanced randomization is used to allocate couples to conditions and partners to either being the target person of the intervention or to the partner condition. The ecological momentary intervention takes place in the first 14 days after baseline assessment and is followed by another 14 days diary phase without intervention. Follow-ups are one month and six months later. Subsequent to the six-months follow-up another 14 days diary phase takes place.The main outcome measures are self-reported and accelerometer-assessed physical activity. Secondary outcome measures are Body Mass Index (BMI), aerobic fitness and habitual physical activity. DISCUSSION: This is the first study examining a dyadic action control intervention in comparison to an individual action control condition and two control groups applying a single-blind randomized control trial. Challenges with running couples studies as well as advantages and disadvantages of certain design-related decisions are discussed. This RCT was funded by the Swiss National Science Foundation (PP00P1_133632/1) and was registered on 27/04/2012 at http://www.isrctn.com/ISRCTN15705531.

GOCE: precise orbit determination for the entire mission

The Gravity field and steady-state Ocean Circulation Explorer (GOCE) was the first Earth explorer core mission of the European Space Agency. It was launched on March 17, 2009 into a Sun-synchronous dusk-dawn orbit and re-entered into the Earth’s atmosphere on November 11, 2013. The satellite altitude was between 255 and 225 km for the measurement phases. The European GOCE Gravity consortium is responsible for the Level 1b to Level 2 data processing in the frame of the GOCE High-level processing facility (HPF). The Precise Science Orbit (PSO) is one Level 2 product, which was produced under the responsibility of the Astronomical Institute of the University of Bern within the HPF. This PSO product has been continuously delivered during the entire mission. Regular checks guaranteed a high consistency and quality of the orbits. A correlation between solar activity, GPS data availability and quality of the orbits was found. The accuracy of the kinematic orbit primarily suffers from this. Improvements in modeling the range corrections at the retro-reflector array for the SLR measurements were made and implemented in the independent SLR validation for the GOCE PSO products. The satellite laser ranging (SLR) validation finally states an orbit accuracy of 2.42 cm for the kinematic and 1.84 cm for the reduced-dynamic orbits over the entire mission. The common-mode accelerations from the GOCE gradiometer were not used for the official PSO product, but in addition to the operational HPF work a study was performed to investigate to which extent common-mode accelerations improve the reduced-dynamic orbit determination results. The accelerometer data may be used to derive realistic constraints for the empirical accelerations estimated for the reduced-dynamic orbit determination, which already improves the orbit quality. On top of that the accelerometer data may further improve the orbit quality if realistic constraints and state-of-the-art background models such as gravity field and ocean tide models are used for the reduced-dynamic orbit determination.

Improved star camera attitude data and their effect on the gravity field

Efforts are ongoing to decrease the noise of the GRACE gravity field models and hence to arrive closer to the GRACE baseline. The most significant error sources belong the untreated errors in the observation data and the imperfections in the background models. The recent study (Bandikova&Flury,2014) revealed that the current release of the star camera attitude data (SCA1B RL02) contain noise systematically higher than expected by about a factor 3-4. This is due to an incorrect implementation of the algorithms for quaternion combination in the JPL processing routines. Generating improved SCA data requires that valid data from both star camera heads are available which is not always the case because the Sun and Moon at times blind one camera. In the gravity field modeling, the attitude data are needed for the KBR antenna offset correction and to orient the non-gravitational linear accelerations sensed by the accelerometer. Hence any improvement in the SCA data is expected to be reflected in the gravity field models. In order to quantify the effect on the gravity field, we processed one month of observation data using two different approaches: the celestial mechanics approach (AIUB) and the variational equations approach (ITSG). We show that the noise in the KBR observations and the linear accelerations has effectively decreased. However, the effect on the gravity field on a global scale is hardly evident. We conclude that, at the current level of accuracy, the errors seen in the temporal gravity fields are dominated by errors coming from sources other than the attitude data.

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

Abstract: Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.

Development and validation of a novel pedometer algorithm to quantify extended characteristics of the locomotor behavior of dairy cows

Behavior is one of the most important indicators for assessing cattle health and well-being. The objective of this study was to develop and validate a novel algorithm to monitor locomotor behavior of loose-housed dairy cows based on the output of the RumiWatch pedometer (ITIN+HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Data of locomotion were acquired by simultaneous pedometer measurements at a sampling rate of 10 Hz and video recordings for manual observation later. The study consisted of 3 independent experiments. Experiment 1 was carried out to develop and validate the algorithm for lying behavior, experiment 2 for walking and standing behavior, and experiment 3 for stride duration and stride length. The final version was validated, using the raw data, collected from cows not included in the development of the algorithm. Spearman correlation coefficients were calculated between accelerometer variables and respective data derived from the video recordings (gold standard). Dichotomous data were expressed as the proportion of correctly detected events, and the overall difference for continuous data was expressed as the relative measurement error. The proportions for correctly detected events or bouts were 1 for stand ups, lie downs, standing bouts, and lying bouts and 0.99 for walking bouts. The relative measurement error and Spearman correlation coefficient for lying time were 0.09% and 1; for standing time, 4.7% and 0.96; for walking time, 17.12% and 0.96; for number of strides, 6.23% and 0.98; for stride duration, 6.65% and 0.75; and for stride length, 11.92% and 0.81, respectively. The strong to very high correlations of the variables between visual observation and converted pedometer data indicate that the novel RumiWatch algorithm may markedly improve automated livestock management systems for efficient health monitoring of dairy cows.