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Bolton, Samantha, Nick Cave, Naomi Cogger, and G. R. Colborne. "Use of a Collar-Mounted Triaxial Accelerometer to Predict Speed and Gait in Dogs." Animals 11, no. 5 (April 27, 2021): 1262. http://dx.doi.org/10.3390/ani11051262.
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Accelerometry has been used to measure treatment efficacy in dogs with osteoarthritis, although interpretation is difficult. Simplification of the output into speed or gait categories could simplify interpretation. We aimed to determine whether collar-mounted accelerometry could estimate the speed and categorise dogs’ gait on a treadmill. Eight Huntaway dogs were fitted with a triaxial accelerometer and then recorded using high-speed video on a treadmill at a slow and fast walk, trot, and canter. The accelerometer data (delta-G) was aligned with the video data and records of the treadmill speed and gait. Mixed linear and logistic regression models that included delta-G and a term accounting for the dogs’ skeletal sizes were used to predict speed and gait, respectively, from the accelerometer signal. Gait could be categorised (pseudo-R2 = 0.87) into binary categories of walking and faster (trot or canter), but not into the separate faster gaits. The estimation of speed above 3 m/s was inaccurate, though it is not clear whether that inaccuracy was due to the sampling frequency of the particular device, or whether that is an inherent limitation of collar-mounted accelerometers in dogs. Thus, collar-mounted accelerometry can reliably categorise dogs’ gaits into two categories, but finer gait descriptions or speed estimates require individual dog modelling and validation. Nonetheless, this accelerometry method could improve the use of accelerometry to detect treatment effects in osteoarthritis by allowing the selection of periods of activity that are most affected by treatment.
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Sjöros, Tanja, Henri Vähä-Ypyä, Saara Laine, Taru Garthwaite, Eliisa Löyttyniemi, Harri Sievänen, Kari K. Kalliokoski, Juhani Knuuti, Tommi Vasankari, and Ilkka H. A. Heinonen. "Influence of the Duration and Timing of Data Collection on Accelerometer-Measured Physical Activity, Sedentary Time and Associated Insulin Resistance." International Journal of Environmental Research and Public Health 18, no. 9 (May 6, 2021): 4950. http://dx.doi.org/10.3390/ijerph18094950.
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Accelerometry is a commonly used method to determine physical activity in clinical studies, but the duration and timing of measurement have seldom been addressed. We aimed to evaluate possible changes in the measured outcomes and associations with insulin resistance during four weeks of accelerometry data collection. This study included 143 participants (median age of 59 (IQR9) years; mean BMI of 30.7 (SD4) kg/m2; 41 men). Sedentary and standing time, breaks in sedentary time, and different intensities of physical activity were measured with hip-worn accelerometers. Differences in the accelerometer-based results between weeks 1, 2, 3 and 4 were analyzed by mixed models, differences during winter and summer by two-way ANOVA, and the associations between insulin resistance and cumulative means of accelerometer results during weeks 1 to 4 by linear models. Mean accelerometry duration was 24 (SD3) days. Sedentary time decreased after three weeks of measurement. More physical activity was measured during summer compared to winter. The associations between insulin resistance and sedentary behavior and light physical activity were non-significant after the first week of measurement, but the associations turned significant in two to three weeks. If the purpose of data collection is to reveal associations between accelerometer-measured outcomes and tenuous health outcomes, such as insulin sensitivity, data collection for at least three weeks may be needed.
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Ortolá, Rosario, Esther García-Esquinas, Verónica Cabanas-Sánchez, Jairo H. Migueles, David Martínez-Gómez, and Fernando Rodríguez-Artalejo. "Association of Physical Activity, Sedentary Behavior, and Sleep With Unhealthy Aging: Consistent Results for Device-Measured and Self-reported Behaviors Using Isotemporal Substitution Models." Journals of Gerontology: Series A 76, no. 1 (July 23, 2020): 85–94. http://dx.doi.org/10.1093/gerona/glaa177.
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Abstract Background We examined the association of time allocation among physical activity (PA), sedentary behavior (SB), and sleep with unhealthy aging (UA), using both accelerometry and self-reports. Method We used cross-sectional data from 2312 individuals aged 65 years and older. Physical activity, SB, and sleep were ascertained by both wrist accelerometers and validated questionnaires, and UA was measured with a 52-item health-deficit accumulation index. Analyses used isotemporal substitution linear regression models. Results Less deficit accumulation was observed when the distribution of activities was 30 min/d less of SB and 30 min/d more of PA for both accelerometer (fully adjusted β [95% CI]: –0.75 [–0.90, –0.61]) and self-reports (–0.55 [–0.65, –0.45]), as well as less long sleep and more PA (accelerometer: –1.44 [–1.86, –1.01]; self-reports: –2.35 [–3.35, –1.36]) or more SB (accelerometer: –0.45 [–0.86, –0.05]; self-reports: –1.28 [–2.29, –0.28]), less normal sleep and more moderate-to-vigorous PA (accelerometer: –1.70 [–2.28, –1.13]; self-reports: –0.65 [–0.99, –0.31]), and less accelerometer light PA and more moderate-to-vigorous PA (–1.62 [–2.17, –1.07]). However, more deficit accumulation was observed when less sleep was accompanied by either more SB or more light PA in short sleepers. Self-reports captured differential associations by activity: walking appeared to be as beneficial as more vigorous activities, such as cycling or sports, and reading was associated with less UA than more mentally passive SBs, such as watching TV. Conclusions More PA was associated with less UA when accompanied by less SB time or sleep in long/normal sleepers, but not in short sleepers, where the opposite was found. Accelerometry and self-reports provided consistent associations.
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FENATO JUNIOR, ALEXANDRE, LARISSA MARTINS GARCIA, GLEICI DA SILVA CASTRO PERDONÁ, and DANIEL AUGUSTO MARANHO. "MEASUREMENT OF PELVIC RETROVERSION DURING HIP FLEXION: EVALUATION WITH ACCELEROMETERS." Acta Ortopédica Brasileira 28, no. 2 (April 2020): 69–73. http://dx.doi.org/10.1590/1413-785220202801227237.
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ABSTRACT Objective: To quantify pelvic retroversion during clinical evaluation of hip flexion with accelerometers and to verify the reliability of these sensors to measure hip flexion. Methods: An accelerometer was positioned laterally in the pelvis to measure pelvic retroversion. Another accelerometer was positioned anteriorly on the thigh to evaluate hip flexion amplitude. The evaluations were performed with volunteers in supine position by three raters. For evaluation of pelvic retroversion, the mean ± SD (minimum-maximum) was calculated. Reliability of the accelerometer between raters was determined by intraclass correlation coefficients (ICC). The linear correlation coefficient between hip flexion was determined by using goniometer and accelerometer. Results: The mean pelvic retroversion was 7.3° ± 0.93° (6°-11°) in the clinical limit of the hip range of motion, which was 106.25° ± 10.46° (93°-130°). The ICC between two raters were 0.60, 0.71 and 0.74 (goniometer) and 0.46, 0.71 and 0.83 (accelerometer). The linear correlation between hip flexion measurements with goniometer and accelerometer was 0.87. Conclusion: During clinical evaluation of the final range of hip flexion, there was an associated pelvic movement of approximately 7.3º. Accelerometers have proven to be reliable for measurement of hip flexion. Level of Evidence III, Study of nonconsecutive patients with no gold reference standard applied uniformly.
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Ullrich, Antje, Sophie Baumann, Lisa Voigt, Ulrich John, and Sabina Ulbricht. "Measurement Reactivity of Accelerometer-Based Sedentary Behavior and Physical Activity in 2 Assessment Periods." Journal of Physical Activity and Health 18, no. 2 (February 1, 2021): 185–91. http://dx.doi.org/10.1123/jpah.2020-0331.
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Background: The purposes of this study were to examine accelerometer measurement reactivity (AMR) in sedentary behavior (SB), physical activity (PA), and accelerometer wear time in 2 measurement periods and to quantify AMR as a human-related source of bias for the reproducibility of SB and PA estimates. Methods: In total, 136 participants (65% women, mean age = 54.6 y) received 7-day accelerometry at the baseline and after 12 months. Latent growth models were used to identify AMR. Intraclass correlations were calculated to examine the reproducibility using 2-level mixed-effects linear regression analyses. Results: Within each 7-day accelerometry assessment, the participants increased their time spent in SB (b = 2.4 min/d; b = 3.8 min/d) and reduced their time spent in light PA (b = −2.0 min/d; b = −3.2 min/d), but did not change moderate to vigorous PA. The participants reduced their wear time (b = −5.2 min/d) only at the baseline. The intraclass correlations ranged from .42 for accelerometer wear time to .74 for SB. The AMR was not identified as a source of bias in any regression model. Conclusions: AMR may influence SB and PA estimates differentially. Although 7-day accelerometry seems to be a reproducible measure, our findings highlight accelerometer wear time as a crucial confounder in analyzing SB and PA data.
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Lawinger, Elizabeth, Tim L. Uhl, Mark Abel, and Srinath Kamineni. "Assessment of Accelerometers for Measuring Upper-Extremity Physical Activity." Journal of Sport Rehabilitation 24, no. 3 (August 2015): 236–43. http://dx.doi.org/10.1123/jsr.2013-0140.
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Objective:The overarching goal of this study was to examine the use of triaxial accelerometers in measuring upper-extremity motions to monitor upper-extremity-exercise compliance. There were multiple questions investigated, but the primary objective was to investigate the correlation between visually observed arm motions and triaxial accelerometer activity counts to establish fundamental activity counts for the upper extremity.Study Design:Cross-sectional, basic research.Setting:Clinical laboratory.Participants:Thirty healthy individuals age 26 ± 6 y, body mass 24 ± 3 kg, and height 1.68 ± 0.09 m volunteered.Intervention:Participants performed 3 series of tasks: activities of daily living (ADLs), rehabilitation exercises, and passive shoulder range of motion at 5 specific velocities on an isokinetic dynamometer while wearing an accelerometer on each wrist. Participants performed exercises with their dominant arm to examine differences between sides. A researcher visually counted all arm motions to correlate counts with physical activity counts provided by the accelerometer.Main Outcome Measure:Physical activity counts derived from the accelerometer and visually observed activity counts recorded from a single investigator.Results:There was a strong positive correlation (r = .93, P < .01) between accelerometer physical activity counts and visual activity counts for all ADLs. Accelerometers activity counts demonstrated side-to-side difference for all ADLs (P < .001) and 5 of the 7 rehabilitation activities (P < .003). All velocities tested on the isokinetic dynamometer were shown to be significantly different from each other (P < .001).Conclusion:There is a linear relationship between arm motions counted visually and the physical activity counts generated by an accelerometer, indicating that arm motions could be potentially accounted for if monitoring arm usage. The accelerometers can detect differences in relatively slow arm-movement velocities, which is critical if attempting to evaluate exercise compliance during early phases of shoulder rehabilitation. These results provide fundamental information that indicates that triaxial accelerometers have the potential to objectively monitor and measure arm activities during rehabilitation and ADLs.
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Arvidsson, Daniel, Mark Fitch, Mark L. Hudes, Catrine Tudor-Locke, and Sharon E. Fleming. "Accelerometer Response to Physical Activity Intensity in Normal-Weight Versus Overweight African American Children." Journal of Physical Activity and Health 8, no. 5 (July 2011): 682–92. http://dx.doi.org/10.1123/jpah.8.5.682.
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Background:Different movement efficiency in overweight children may affect accelerometer output data. The purpose was to investigate the ability of accelerometers to assess physical activity intensity and number of steps in normal-weight compared with overweight children.Methods:Eleven normal-weight and 14 overweight African American children walked at 2, 4, 5, and 6 km/h on a treadmill wearing Lifecorder, ActiGraph, RT3, and Biotrainer. Oxygen uptake was measured and steps manually counted. Fat free mass (FFM) was assessed from bioelectrical impedance analysis. Accelerometer counts and the individual linear regression lines of accelerometer counts versus VO2/FFM were evaluated, together with steps recorded by Lifecorder and Actigraph.Results:Correlations between accelerometer counts and VO2/FFM for all monitors were r ≥ .95 (P < .01). The accelerometer counts and their relationship to VO2/FFM did not generally differ significantly by body weight status. Lifecorder and Actigraph underestimated steps at 4, 5, and 6 km/h by less than 9%, but the error was up to −95% at 2 km/h.Conclusions:All 4 accelerometers show high ability to assess physical activity intensity, and can be used to compare physical activity between normal-weight and overweight children. The Lifecorder and the ActiGraph showed high accuracy in assessing steps, providing speed of movement exceeded 2 km/h.
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Al-Rawashdeh, Yazan M., and Moustafa Elshafei. "Filtering Techniques for Estimating the Angular Motion Using All-Accelerometers." Applied Mechanics and Materials 829 (March 2016): 103–9. http://dx.doi.org/10.4028/www.scientific.net/amm.829.103.
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Linear accelerometers can be used to retrieve the angular motion of the body they are attached to if their measurements are handled in an appropriate way. In this paper, an 18-accelerometer configuration is used to facilitate angular motion determination. Various measurement models are investigated where each model utilizes different accelerometers’ measurements. These models are used to build linear and nonlinear filters. The filters performances are evaluated and the associated sign ambiguity problem is solved. It is shown that a norm-constrained Kalman filters bank will give the best results. This work can be used within inertial navigation systems as a replacement of the gyroscopes.
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Jung, Sunah, Haesang Yang, Kiheum Park, Yutaek Seo, and Woojae Seong. "Monitoring Severe Slugging in Pipeline-Riser System Using Accelerometers for Application in Early Recognition." Sensors 19, no. 18 (September 12, 2019): 3930. http://dx.doi.org/10.3390/s19183930.
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The use of accelerometer signals for early recognition of severe slugging is investigated in a pipeline-riser system conveying an air–water two-phase flow, where six accelerometers are installed from the bottom to the top of the riser. Twelve different environmental conditions are produced by changing water and gas superficial velocities, of which three conditions are stable states and the other conditions are related to severe slugging. For online recognition, simple parameters using statistics and linear prediction coefficients are employed to extract useful features. Binary classification to recognize stable flow and severe slugging is performed using a support vector machine and a neural network. In multiclass classification, the neural network is adopted to identify four flow patterns of stable state, two types of severe slugging, and an irregular transition state between severe slugging and dual-frequency severe slugging. The performance is compared and analyzed according to the signal length for three cases of sensor location: six accelerometers, one accelerometer at the riser base, and one accelerometer at the top of the riser.
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Tomczyk, Krzysztof. "Monte Carlo-Based Procedure for Determining the Maximum Energy at the Output of Accelerometers." Energies 13, no. 7 (March 27, 2020): 1552. http://dx.doi.org/10.3390/en13071552.
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The solutions presented in this paper can be the basis for mutual comparison of different types of accelerometers produced by competing companies. An application of a procedure based on the Monte Carlo method to determine the maximum energy at the output of accelerometers is discussed here. The fixed-point algorithm controlled by the Monte Carlo method is used to determine this energy. This algorithm can only be used for the time-invariant and linear measurement systems. Hence, the accelerometer nonlinearities are not considered here. The mathematical models of the accelerometer and the special filter, represented by the relevant transfer functions, are the basis for the above procedure. Testing results of the voltage-mode accelerometer of type DJB A/1800/V are presented here as an example of an implementation of the solutions proposed. Calculation of the energy was executed in Mathcad 14 program with the built-in Programming Toolbar. The value of the maximum output energy determined for a specified time interval corresponds to the maximum integral-square error of the accelerometer. Such maximum energy can be a comparative ratio just like the accuracy class in the case of instruments used for the static measurements. Hence, the main analytical and technical contributions of this paper concern the development of theoretical procedures and the presentation of their application on the example of a real type of accelerometer.
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Ghasemzadeh, Vahid, and Mohammad M. Arefi. "Design, modeling, and simulation of an INS system using an asymmetric structure of six accelerometers and its error analysis in the ECEF frame." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 13 (August 11, 2016): 2345–61. http://dx.doi.org/10.1177/0954410016662059.
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The inertial navigation system is one of the most important and common methods of navigation. In this system, accelerometers and gyroscopes are used to measure linear accelerations and angular velocities, respectively. Accelerometers have simpler manufacture techniques, lower cost, and smaller volume and weight in comparison with gyroscopes. Therefore, in some application of navigation systems, non-gyro inertial navigation systems based on accelerometers are used. In this paper, an asymmetric structure of six accelerometers is proposed. Then dynamic relations of this structure are extracted. This structure and its relations can determine linear accelerations and angular velocities, completely. Moreover, the algorithm of inertial navigation in earth centered earth fixed (ECEF) frame is suggested. Error analysis as of the most important issues in inertial navigation is discussed. Thus, bias, misalignment, sensitivity, and noise of accelerometers are modeled appropriately. In addition, a symmetric structure of accelerometers is proposed and its equations are derived. Finally, the designed system, error model of accelerometers, and algorithm of inertial navigation in ECEF frame are simulated. The results of simulation show that the designed system has suitable accuracy and applications for short time navigation. Furthermore, results confirm that the proposed asymmetric structure requires less accelerometer in comparison with symmetric structure.
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Douma, Joeri A. J., Maaike B. de Beaufort, Caroline S. Kampshoff, Saskia Persoon, Jorine A. Vermaire, Mai J. Chinapaw, Willem van Mechelen, et al. "Physical activity in patients with cancer: self-report versus accelerometer assessments." Supportive Care in Cancer 28, no. 8 (December 9, 2019): 3701–9. http://dx.doi.org/10.1007/s00520-019-05203-3.
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Abstract Purpose The level of daily physical activity in patients with cancer is frequently assessed by questionnaires, such as the Physical Activity Scale for the Elderly (PASE). Objective assessments, with for example accelerometers, may be a good alternative. The aim of this study was to investigate the agreement between the PASE questionnaire and accelerometer-assessed physical activity in a large group of patients with different types of cancer. Methods Baseline accelerometer and PASE questionnaire data of 403 participants from the REACT (Resistance and Endurance Exercise After Chemotherapy, n = 227), the EXIST (Exercise Intervention After Stem-Cell Transplantation, n = 74), and NET-QUBIC (NEtherlands QUality of Life And Biomedical Cohort Studies In Cancer, n = 102) studies were available for the current analyses. Physical activity was assessed by the PASE questionnaire (total score) and accelerometers (total minutes per day > 100 counts). Linear mixed models regression analysis was used to assess the agreement between the PASE questionnaire and accelerometer-assessed physical activity. Results The mean (SD) PASE score was 95.9 (75.1) points and mean (SD) time in physical activity measured with the accelerometer was 256.6 (78.8) min per day. The agreement between the PASE score and the accelerometer data was significant, but poor (standardized regression coefficient (B) = 0.36, 95%CI = 0.27; 0.44, p < 0.01). Conclusion Agreement between the PASE questionnaire and accelerometer-assessed physical activity was poor. The poor agreement indicates that they measure different physical activity constructs and cannot be used interchangeably to assess the level of daily physical activity in patients with cancer.
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Adolph, Anne L., Maurice R. Puyau, Firoz A. Vohra, Theresa A. Nicklas, Issa F. Zakeri, and Nancy F. Butte. "Validation of Uniaxial and Triaxial Accelerometers for the Assessment of Physical Activity in Preschool Children." Journal of Physical Activity and Health 9, no. 7 (September 2012): 944–53. http://dx.doi.org/10.1123/jpah.9.7.944.
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Purpose:Given the unique physical activity (PA) patterns of preschoolers, wearable electronic devices for quantitative assessment of physical activity require validation in this population. Study objective was to validate uniaxial and triaxial accelerometers in preschoolers.Methods:Room calorimetry was performed over 3 hours in 64 preschoolers, wearing Actical, Actiheart, and RT3 accelerometers during play, slow, moderate, and fast translocation. Based on activity energy expenditure (AEE) and accelerometer counts, optimal thresholds for PA levels were determined by piecewise linear regression and discrimination boundary analysis.Results:Established HR cutoffs in preschoolers for sedentary/light, light/moderate and moderate/vigorous levels were used to define AEE (0.015, 0.054, 0.076 kcal·kg−1·min−1) and PA ratio (PAR; 1.6, 2.9, 3.6) thresholds, and accelerometer thresholds. True positive predictive rates were 77%, 75%, and 76% for sedentary; 63%, 61%, and 65% for light; 34%, 52%, and 49% for moderate; 46%, 46%, and 49% for vigorous levels. Due to low positive predictive rates, we combined moderate and vigorous PA. Classification accuracy was improved overall and for the combined moderate-to-vigorous PA level (69%, 82%, 79%) for Actical, Actiheart, and RT3, respectively.Conclusion:Uniaxial and triaxial accelerometers are acceptable devices with similar classification accuracy for sedentary, light, and moderate-to-vigorous levels of PA in preschoolers.
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Williams, Lauren R., Greg J. Bishop-Hurley, Angela E. Anderson, and Dave L. Swain. "Application of accelerometers to record drinking behaviour of beef cattle." Animal Production Science 59, no. 1 (2019): 122. http://dx.doi.org/10.1071/an17052.
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Accelerometers have been used to record many cattle postures and behaviours including standing, lying, walking, grazing and ruminating but not cattle drinking behaviour. This study explores whether neck-mounted triaxial accelerometers can identify drinking and whether head-neck position and activity can be used to record drinking. Over three consecutive days, data were collected from 12 yearling Brahman cattle each fitted with a collar containing an accelerometer. Each day the cattle were herded into a small yard containing a water trough and allowed 5 min to drink. Drinking, standing (head up), walking and standing (head down) were recorded. Examination of the accelerometer data showed that drinking events were characterised by a unique signature compared with the other behaviours. A linear mixed-effects model identified two variables that reflected differences in head-neck position and activity between drinking and the other behaviours: mean of the z- (front-to-back) axis and variance of the x- (vertical) axis (P < 0.05). Threshold values, derived from Kernel density plots, were applied to classify drinking from the other behaviours using these two variables. The method accurately classified drinking from standing (head up) with 100% accuracy, from walking with 92% accuracy and from standing (head down) with 79% accuracy. The study shows that accelerometers have the potential to record cattle drinking behaviour. Further development of a classification method for drinking is required to allow accelerometer-derived data to be used to improve our understanding of cattle drinking behaviour and ensure that their water intake needs are met.
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F. Hraniak, Valerii, Vasyl Kukharchuk, Volodymyr Kucheruk, Samoil Katsyv, D. Zh Karabekova, and A. K. Khassenov. "Mathematical model of capacitance micromechanical accelerometer in static and dynamic operating modes." Bulletin of the Karaganda University. "Physics" Series 98, no. 2 (June 30, 2020): 60–67. http://dx.doi.org/10.31489/2020ph2/60-67.
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Monitoring and early diagnosis systems, on which the protection function of both hydroturbines and auxiliary power equipment rely, are becoming increasingly relevant. One of the most promising methods of technical control and diagnostics of hydo units is the analysis of their vibro-acoustic characteristics. But a significant technical problem that arises in the construction of such systems is the limited use of known sensors of vibration velocity and vibration displacement due to the fact that the rotary speed of hydro units is usually below the lower limit of operation of sensors of this type. One of the promising ways to solve this problem is using capacitive micromechanical accelerometers. However, the existing mathematical models describing this type of accelerometers have low accuracy, which limits their practical using. The mathematical models of the capacitive micromechanical accelerometer for static and dynamic modes of operation are developed in this article. It was established that this accelerometer has a constant sensitivity, therefore its static characteristic is linear. It is shown that in the dynamic mode of operation of a capacitive micromechanical accelerometer has a dynamic error component, the cause of which is its own displacement of the moving part of the sensor, which is due to the inertial properties of the moving part and elastic properties of stretch marks. The mathematical dependence of the absolute dynamic error of the capacitive micromechanical accelerometer is obtained, the removal of w
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Alvarez, Juan, Diego Álvarez, and Antonio López. "Accelerometry-Based Distance Estimation for Ambulatory Human Motion Analysis." Sensors 18, no. 12 (December 15, 2018): 4441. http://dx.doi.org/10.3390/s18124441.
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In human motion science, accelerometers are used as linear distance sensors by attaching them to moving body parts, with their measurement axes its measurement axis aligned in the direction of motion. When double integrating the raw sensor data, multiple error sources are also integrated integrated as well, producing inaccuracies in the final position estimation which increases fast with the integration time. In this paper, we make a systematic and experimental comparison of different methods for position estimation, with different sensors and in different motion conditions. The objective is to correlate practical factors that appear in real applications, such as motion mean velocity, path length, calibration method, or accelerometer noise level, with the quality of the estimation. The results confirm that it is possible to use accelerometers to estimate short linear displacements of the body with a typical error of around 4.5% in the general conditions tested in this study. However, they also show that the motion kinematic conditions can be a key factor in the performance of this estimation, as the dynamic response of the accelerometer can affect the final results. The study lays out the basis for a better design of distance estimations, which are useful in a wide range of ambulatory human motion monitoring applications.
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Crisco, Joseph J., Jeffrey J. Chu, and Richard M. Greenwald. "An Algorithm for Estimating Acceleration Magnitude and Impact Location Using Multiple Nonorthogonal Single-Axis Accelerometers." Journal of Biomechanical Engineering 126, no. 6 (December 1, 2004): 849–54. http://dx.doi.org/10.1115/1.1824135.
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Accelerations of the head are the likely cause of concussion injury, but identifying the specific etiology of concussion has been difficult due to the lack of a valid animal or computer model. Contact sports, in which concussions are a rising health care concern, offer a unique research laboratory environment. However, measuring head acceleration in the field has many challenges including the need for large population sampling because of the relatively low incidence of concussions. We report a novel approach for calculating linear acceleration that can be incorporated into a head-mounted system for on-field use during contact sports. The advantages of this approach include the use of single-axis linear accelerometers, which reduce costs, and a nonorthogonal arrangement of the accelerometers, which simplifies the design criteria for a head-mounted and helmet compatible system. The purpose of this study was to describe the algorithm and evaluate its accuracy for measuring linear acceleration magnitude and impact location using computer simulation and experimental tests with various accelerometer configurations. A 10% error in magnitude and a 10 deg error in impact location were achieved using as few as six single-axis accelerometers mounted on a hemispherical headform.
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Grigorie, T. L., and R. M. Botez. "A new method to reduce the noise of the miniaturised inertial sensors disposed in redundant linear configurations." Aeronautical Journal 117, no. 1188 (February 2013): 111–32. http://dx.doi.org/10.1017/s0001924000007909.
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Abstract This paper presents a new adaptive algorithm for the statistical filtering of miniaturised inertial sensor noise. The algorithm uses the minimum variance method to perform a best estimate calculation of the accelerations or angular speeds on each of the three axes of an Inertial Measurement Unit (IMU) by using the information from some accelerometers and gyros arrays placed along the IMU axes. Also, the proposed algorithm allows the reduction of both components of the sensors’ noise (long term and short term) by using redundant linear configurations for the sensors dispositions. A numerical simulation is performed to illustrate how the algorithm works, using an accelerometer sensor model and a four-sensor array (unbiased and with different noise densities). Three cases of ideal input acceleration are considered: 1) a null signal; 2) a step signal with a no-null time step; and 3) a low frequency sinusoidal signal. To experimentally validate the proposed algorithm, some bench tests are performed. In this way, two sensors configurations are used: 1) one accelerometers array with four miniaturised sensors (n = 4); and 2) one accelerometers array with nine miniaturised sensors (n = 9). Each of the two configurations are tested for three cases of input accelerations: 0ms−1, 9·80655m/s2 and 9·80655m/s2.
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Montoye, Alexander H. K., Kimberly A. Clevenger, Kelly A. Mackintosh, Melitta A. McNarry, and Karin A. Pfeiffer. "Cross-Validation and Comparison of Energy Expenditure Prediction Models Using Count-Based and Raw Accelerometer Data in Youth." Journal for the Measurement of Physical Behaviour 2, no. 4 (December 1, 2019): 237–46. http://dx.doi.org/10.1123/jmpb.2018-0011.
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Background: Machine learning may improve energy expenditure (EE) prediction from body-worn accelerometers. However, machine learning models are rarely cross-validated in an independent sample, and the use of machine learning raises additional questions including the effect of accelerometer placement and data type (count vs. raw) for optimal EE prediction. Purpose: To assess the accuracy of artificial neural network (ANN) models for EE prediction in youth using count-based or raw data from accelerometers worn on the hip, wrist, or in combination, and compare these to count-based, EE regression equations. Methods: Data were collected in two settings; one (n = 27) to calibrate the EE prediction models, and the other (n = 34) for model cross-validation. Participants wore a portable metabolic analyzer (EE criterion) and accelerometers on the left wrist and right hip while completing 30 minutes of exergames (calibration, cross-validation) and a maximal exercise test (calibration only). Six ANNs were created from the calibration data, separately by accelerometer placement (hip, wrist, combination) and data format (count-based, raw) to predict EE (15-second epochs). Three count-based linear regression equations were also developed for comparison to the ANNs. Results: The count-based, hip ANN demonstrated lower error (RMSE: 1.2 METs) than all other ANNs (RMSE: 1.7–3.6 METs) and EE regression equations (RMSE: 1.5–3.2 METs). However, all models showed bias toward the mean. Conclusion: An ANN developed for hip-worn accelerometers had higher accuracy for EE prediction during an exergame session than wrist or combination ANNs, and ANNs developed using count-based data had higher accuracy than ANNs developed using raw data.
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Baranov, Pavel, Tamara Nesterenko, Evgenii Barbin, Aleksej Koleda, Shuji Tanaka, Takashiro Tsukamoto, Ivan Kulinich, Dmitry Zykov, and Alexander Shelupanov. "A novel multiple-axis MEMS gyroscope-accelerometer with decoupling frames." Sensor Review 39, no. 5 (September 16, 2019): 670–81. http://dx.doi.org/10.1108/sr-05-2018-0133.
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Purpose Technological capabilities of manufacturing microelectromechanical system (MEMS) gyroscopes are still insufficient if compared to manufacturing high-efficient gyroscopes and accelerometers. This creates weaknesses in their mechanical structure and restrictions in the measurement accuracy, stability and reliability of MEMS gyroscopes and accelerometers. This paper aims to develop a new architectural solutions for optimization of MEMS gyroscopes and accelerometers and propose a multi-axis MEMS inertial module combining the functions of gyroscope and accelerometer. Design/methodology/approach The finite element modeling (FEM) and the modal analysis in FEM are used for sensing, drive and control electrode capacitances of the multi-axis MEMS inertial module with the proposed new architecture. The description is given to its step-by-step process of manufacturing. Algorithms are developed to detect its angular rates and linear acceleration along three Cartesian axes. Findings Experimental results are obtained for eigenfrequencies and capacitances of sensing, drive and control electrodes for 50 manufactured prototypes of the silicon electromechanical sensor (SES). For 42 SES prototypes, a good match is observed between the calculated and simulated capacitance values of comb electrodes. Thus, the mean-square deviation is not over 20 per cent. The maximum difference between the calculated and simulated eigenfrequencies in the drive channel of 11 SES prototypes is not over 3 per cent. The same difference is detected for eigenfrequencies in the first sensing channel of 17 SES prototypes. Originality/value This study shows a way to design and optimize the structure and theoretical background for the development of the MEMS inertial module combining the functions of gyroscope and accelerometer. The obtained results will improve and expand the manufacturing technology of MEMS gyroscopes and accelerometers.
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Nishihara, Kazue. "Fundamental Study on Hand Waving Sensors." Journal of Robotics and Mechatronics 2, no. 5 (October 20, 1990): 325–34. http://dx.doi.org/10.20965/jrm.1990.p0325.
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In order to develop a dynamic man-machine interface which measures angular motions of multi-link mechanisms, a uniaxial hand wave sensor is experimented with and triaxial hand wave sensors are simulated numerically. It was confirmed that a uniaxial hand wave sensor composed of a pair of uniaxially located accelerometers directly obtains exact angular acceleration by subtracting each acceleration signal. A triaxial hand wave sensor by a six (i.e. three pairs) accelerometer method, however, contains duplex angular velocities influenced by other axes in addition to the exact angular acceleration, so it is necessary to separate those physical values by a software algorithm. Adams-Moulton's method for solving differential equations was best suited to solve this nonlinear problem. A nine accelerometer method obtains linear equations for angular accelerations readily after arithmetic calculations of the nine signals.
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Garnotel, M., T. Bastian, H. M. Romero-Ugalde, A. Maire, J. Dugas, A. Zahariev, M. Doron, et al. "Prior automatic posture and activity identification improves physical activity energy expenditure prediction from hip-worn triaxial accelerometry." Journal of Applied Physiology 124, no. 3 (March 1, 2018): 780–90. http://dx.doi.org/10.1152/japplphysiol.00556.2017.
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Accelerometry is increasingly used to quantify physical activity (PA) and related energy expenditure (EE). Linear regression models designed to derive PAEE from accelerometry-counts have shown their limits, mostly due to the lack of consideration of the nature of activities performed. Here we tested whether a model coupling an automatic activity/posture recognition (AAR) algorithm with an activity-specific count-based model, developed in 61 subjects in laboratory conditions, improved PAEE and total EE (TEE) predictions from a hip-worn triaxial-accelerometer (ActigraphGT3X+) in free-living conditions. Data from two independent subject groups of varying body mass index and age were considered: 20 subjects engaged in a 3-h urban-circuit, with activity-by-activity reference PAEE from combined heart-rate and accelerometry monitoring (Actiheart); and 56 subjects involved in a 14-day trial, with PAEE and TEE measured using the doubly-labeled water method. PAEE was estimated from accelerometry using the activity-specific model coupled to the AAR algorithm (AAR model), a simple linear model (SLM), and equations provided by the companion-software of used activity-devices (Freedson and Actiheart models). AAR-model predictions were in closer agreement with selected references than those from other count-based models, both for PAEE during the urban-circuit (RMSE = 6.19 vs 7.90 for SLM and 9.62 kJ/min for Freedson) and for EE over the 14-day trial, reaching Actiheart performances in the latter (PAEE: RMSE = 0.93 vs. 1.53 for SLM, 1.43 for Freedson, 0.91 MJ/day for Actiheart; TEE: RMSE = 1.05 vs. 1.57 for SLM, 1.70 for Freedson, 0.95 MJ/day for Actiheart). Overall, the AAR model resulted in a 43% increase of daily PAEE variance explained by accelerometry predictions.NEW & NOTEWORTHY Although triaxial accelerometry is widely used in free-living conditions to assess the impact of physical activity energy expenditure (PAEE) on health, its precision and accuracy are often debated. Here we developed and validated an activity-specific model which, coupled with an automatic activity-recognition algorithm, improved the variance explained by the predictions from accelerometry counts by 43% of daily PAEE compared with models relying on a simple relationship between accelerometry counts and EE.
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Wang, Shi Tao, Yu Bin Jia, Bin Zhen Zhang, Xue Song Liu, Qin Wen Huang, and Yi Long Hao. "Analysis and Improvement of a 3 Axis Accelerometer." Key Engineering Materials 503 (February 2012): 163–68. http://dx.doi.org/10.4028/www.scientific.net/kem.503.163.
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In this paper, an integrated 3-axis MEMS accelerometer was analyzed. Because of asymmetrical structure, z-axis sensing element, which was imbedded in the proof mass of lateral accelerometers, had large mechanical coupling. Simulation result showed that the cross talk in z-axis was as high as 64.3%. To solve the problem, a fully symmetrical structure with vertical springs was adopted in z-axis sensing element. The movement of z-axis was linear vertical displacement instead of torsional displacement. Simulation results showed there was no obvious cross talk in z-axis sensing element.
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D'Emilia, Giulio, Antonella Gaspari, and Emanuela Natale. "Amplitude–phase calibration of tri-axial accelerometers in the low-frequency range by a LDV." Journal of Sensors and Sensor Systems 8, no. 1 (May 23, 2019): 223–31. http://dx.doi.org/10.5194/jsss-8-223-2019.
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Abstract. A method for amplitude–phase calibration of tri-axial accelerometers in the low-frequency range (0 to 20 Hz) is proposed, based on a linear slide, used to excite all the axes of the accelerometer at the same time, and a laser Doppler vibrometer (LDV) as a reference. For the phase evaluation different methods, like cross-correlation analysis and cross-spectrum analysis, have also been used for validation purposes. The procedure includes many further validation actions in order to verify the correctness of modelling of the systems being tested, of the data processing and to reduce the calibration uncertainty. Results show that the phase is a critical aspect to consider in calibration, more than the amplitude, and the comparison with the theoretical model is useful to verify the hypotheses. Different behaviours result depending on the elements of the measurement chain and not only on the type of accelerometer.
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Abbaspour-Sani, Ebrahim, Ruey-Shing Huang, and Chee Yee Kwok. "A linear electromagnetic accelerometer." Sensors and Actuators A: Physical 44, no. 2 (August 1994): 103–9. http://dx.doi.org/10.1016/0924-4247(94)00792-6.
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Marco-Ahulló, Adrià, Lluïsa Montesinos-Magraner, Luis-Millán Gonzalez, Roberto Llorens, Xurxo Segura-Navarro, and Xavier García-Massó. "Validation of Using Smartphone Built-In Accelerometers to Estimate the Active Energy Expenditures of Full-Time Manual Wheelchair Users with Spinal Cord Injury." Sensors 21, no. 4 (February 22, 2021): 1498. http://dx.doi.org/10.3390/s21041498.
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This study aimed to investigate the validity of using built-in smartphone accelerometers to estimate the active energy expenditures of full-time manual wheelchair users with spinal cord injury (SCI). Twenty participants with complete SCI completed 10 5-min daily activities that involved the upper limbs, during which their oxygen consumption and upper limb activity were registered using a portable gas analyzer and a smartphone (placed on the non-dominant arm), respectively. Time series of 1-min averaged oxygen consumption and 55 accelerometer variables (13 variables for each of the four axes and three additional variables for the correlations between axes) were used to estimate three multiple linear models, using a 10-fold cross-validation method. The results showed that models that included either all variables and models or that only included the linear variables showed comparable performance, with a correlation of 0.72. Slightly worse general performance was demonstrated by the model that only included non-linear variables, although it proved to be more accurate at estimating the energy expenditures (EE) during specific tasks. These results suggest that smartphones could be a promising low-cost alternative to laboratory-grade accelerometers to estimate the energy expenditure of wheelchair users with spinal cord injury during daily activities.
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Ramirez-Marrero, Farah A., John Miles, Michael J. Joyner, and Timothy B. Curry. "Self-Reported and Objective Physical Activity in Postgastric Bypass Surgery, Obese and Lean Adults: Association With Body Composition and Cardiorespiratory Fitness." Journal of Physical Activity and Health 11, no. 1 (January 2014): 145–51. http://dx.doi.org/10.1123/jpah.2012-0048.
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Background:This study aimed to 1) describe physical activity (PA) in 15 post gastric bypass surgery (GB), 16 obese (Ob), and 14 lean (L) participants (mean ± se: age = 37.1 ± 1.6, 30.8 ± 1.9, 32.7 ± 2.3 yrs.; BMI = 29.7 ± 1.2, 38.2 ± 0.8, 22.9 ± 0.5 kg/m2, respectively); and 2) test associations between PA, body composition, and cardiorespiratory fitness (VO2max).Methods:Participants completed a PA questionnaire after wearing accelerometers from 5–7 days. Body composition was determined with DEXA and CT scans, and VO2max with open circuit spirometry. ANOVA was used to detect differences between groups, and linear regressions to evaluate associations between PA (self-reported, accelerometer), body composition, and VO2max.Results:Self-reported moderate to vigorous PA (MVPA) in GB, Ob, and L participants was 497.7 ± 215.9, 988.6 ± 230.8, and 770.7 ± 249.3 min/week, respectively (P = .51); accelerometer MVPA was 185.9 ± 41.7, 132.3 ± 51.1, and 322.2 ± 51.1 min/week, respectively (P = .03); and steps/day were 6647 ± 141, 6603 ± 377, and 9591 ± 377, respectively (P = .03). Ob showed a marginally higher difference between self-report and accelerometer MVPA (P = .06). Accelerometer-MVPA and steps/day were inversely associated with percent fat (r = –0.53, –0.46), and abdominal fat (r = –0.36, –0.40), and directly associated with VO2max (r = .36).Conclusions:PA was similar between GB and Ob participants, and both were less active than L. Higher MVPA was associated with higher VO2max and lower body fat.
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Hale, Michael T. "Spectral Density Matrix Transformations." Journal of the IEST 60, no. 1 (January 1, 2017): 21–30. http://dx.doi.org/10.17764/1098-4321.60.1.21.
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Abstract Reference criteria for a multiple degree-of-freedom (MDOF) random vibration test is generally provided in terms of an acceleration-based spectral density matrix (SDM). This SDM may be developed in terms of the auto-spectral densities (ASDs) and cross-spectral densities (CSDs) computed from the time histories acquired from an appropriately placed and oriented set of linear accelerometers. Such a direct measurement linear accelerometer based reference criteria will be denoted as SDMmeas. A second technique for defining a reference SDM is in terms of the accelerations associated with the six classical motion degrees-of-freedom as defined at an arbitrary point of origin. Such a reference will be denoted as SDMmotion. The objective at hand is to demonstrate the method of transforming between these two reference criteria spaces.
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Rothney, Megan P., Megan Neumann, Ashley Béziat, and Kong Y. Chen. "An artificial neural network model of energy expenditure using nonintegrated acceleration signals." Journal of Applied Physiology 103, no. 4 (October 2007): 1419–27. http://dx.doi.org/10.1152/japplphysiol.00429.2007.
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Accelerometers are a promising tool for characterizing physical activity patterns in free living. The major limitation in their widespread use to date has been a lack of precision in estimating energy expenditure (EE), which may be attributed to the oversimplified time-integrated acceleration signals and subsequent use of linear regression models for EE estimation. In this study, we collected biaxial raw (32 Hz) acceleration signals at the hip to develop a relationship between acceleration and minute-to-minute EE in 102 healthy adults using EE data collected for nearly 24 h in a room calorimeter as the reference standard. From each 1 min of acceleration data, we extracted 10 signal characteristics (features) that we felt had the potential to characterize EE intensity. Using these data, we developed a feed-forward/back-propagation artificial neural network (ANN) model with one hidden layer (12 × 20 × 1 nodes). Results of the ANN were compared with estimations using the ActiGraph monitor, a uniaxial accelerometer, and the IDEEA monitor, an array of five accelerometers. After training and validation (leave-one-subject out) were completed, the ANN showed significantly reduced mean absolute errors (0.29 ± 0.10 kcal/min), mean squared errors (0.23 ± 0.14 kcal2/min2), and difference in total EE (21 ± 115 kcal/day), compared with both the IDEEA ( P < 0.01) and a regression model for the ActiGraph accelerometer ( P < 0.001). Thus ANN combined with raw acceleration signals is a promising approach to link body accelerations to EE. Further validation is needed to understand the performance of the model for different physical activity types under free-living conditions.
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Chang, Chun-Hao, Yi-Ju Hsu, Fang Li, Yu-Tsai Tu, Wei-Lun Jhang, Chih-Wen Hsu, Chi-Chang Huang, and Chin-Shan Ho. "Reliability and validity of the physical activity monitor for assessing energy expenditures in sedentary, regularly exercising, non-endurance athlete, and endurance athlete adults." PeerJ 8 (August 24, 2020): e9717. http://dx.doi.org/10.7717/peerj.9717.
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Background Inertial sensors, such as accelerometers, serve as convenient devices to predict the energy expenditures (EEs) during physical activities by a predictive equation. Although the accuracy of estimate EEs especially matter to athletes receive physical training, most EE predictive equations adopted in accelerometers are based on the general population, not athletes. This study included the heart rate reserve (HRR) as a compensatory parameter for physical intensity and derived new equations customized for sedentary, regularly exercising, non-endurance athlete, and endurance athlete adults. Methods With indirect calorimetry as the criterion measure (CM), the EEs of participants on a treadmill were measured, and vector magnitudes (VM), as well as HRR, were simultaneously recorded by a waist-worn accelerometer with a heart rate monitor. Participants comprised a sedentary group (SG), an exercise-habit group (EHG), a non-endurance group (NEG), and an endurance group (EG), with 30 adults in each group. Results EE predictive equations were revised using linear regression with cross-validation on VM, HRR, and body mass (BM). The modified model demonstrates valid and reliable predictions across four populations (Pearson correlation coefficient, r: 0.922 to 0.932; intraclass correlation coefficient, ICC: 0.919 to 0.930). Conclusion Using accelerometers with a heart rate monitorcan accurately predict EEs of athletes and non-athletes with an optimized predictive equation integrating the VM, HRR, and BM parameters.
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Rizun, Peter. "Optimal Wiener Filter for a Body Mounted Inertial Attitude Sensor." Journal of Navigation 61, no. 3 (June 26, 2008): 455–72. http://dx.doi.org/10.1017/s0373463308004736.
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An optimal attitude estimator is presented for a human body-mounted inertial measurement unit employing orthogonal triads of gyroscopes, accelerometers and magnetometers. The estimator continuously fuses gyroscope and accelerometer measurements together in a manner that minimizes the mean square error in the estimate of the gravity vector, based on known spectral characteristics for the gyroscope noise and the linear acceleration of points on the human body. The gyroscope noise is modelled as a white noise process of power spectral density δn2/2 while the linear acceleration is modelled as the derivative of a band-limited white noise process of power spectral density δv2/2. The estimator is robust to centripetal acceleration and guaranteed to have zero mean error regardless of the motion of the sensor. The mean square angular error in attitude is shown to be independent of the module's angular velocity and equal to 21/2g−1/2δn3/2δv1/2.
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Yu, W.-W., U. R. Acharya, T.-C. Lim, and H. W. Low. "Non-linear analysis of body responses to functional electrical stimulation on hemiplegic subjects." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 223, no. 6 (May 22, 2009): 653–62. http://dx.doi.org/10.1243/09544119jeim535.
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Functional electrical stimulation (FES) is a method of applying low-level electrical currents to restore or improve body functions lost through nervous system impairment. FES is applied to peripheral nerves that control specific muscles or muscle groups. Application of advanced signal computing techniques to the medical field has helped to achieve practical solutions to the health care problems accurately. The physiological signals are essentially non-stationary and may contain indicators of current disease, or even warnings about impending diseases. These indicators may be present at all times or may occur at random on the timescale. However, to study and pinpoint these subtle changes in the voluminous data collected over several hours is tedious. These signals, e.g. walking-related accelerometer signals, are not simply linear and involve non-linear contributions. Hence, non-linear signal-processing methods may be useful to extract the hidden complexities of the signal and to aid physicians in their diagnosis. In this work, a young female subject with major neuromuscular dysfunction of the left lower limb, which resulted in an asymmetric hemiplegic gait, participated in a series of FES-assisted walking experiments. Two three-axis accelerometers were attached to her left and right ankles and their corresponding signals were recorded during FES-assisted walking. The accelerometer signals were studied in three directions using the Hurst exponent H, the fractal dimension (FD), the phase space plot, and recurrence plots (RPs). The results showed that the H and FD values increase with increasing FES, indicating more synchronized variability due to FES for the left leg (paralysed leg). However, the variation in the normal right leg is more chaotic on FES.
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Mansurov, Tofig M., and Chingiz P. Aliyev. "THREE-DIMENSIONAL PIEZOELECTRIC ACCELEROMETER FOR MEASURING DYNAMIC PARAMETERS OF MOVING OBJECTS." SYNCHROINFO JOURNAL 6, no. 6 (2020): 10–16. http://dx.doi.org/10.36724/2664-066x-2020-6-6-10-16.
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Analysis of structural construction of existing three-dimensional accelerometers is carried out, in which due to the opposite direction of sensitivity vectors and direction of measured inertial force, they allow to measure only linear inertia and accelerations varying in relatively small limits. On the other hand, due to the presence of elements in them that create electromagnetic fields, their construction is somewhat complicated. In addition, in known accel-erometers, due to the absence of a measurement object position sensor and an electronic control circuit, the func-tionality of the accelerometer is limited, Due to lack of integrator for acceleration integration, speed measurement is not provided, Due to rigid attachment of piezoelectric sensing elements through their bases, during measurement they generate interference signals, The amplitude of which exceeds the amplitude of the useful signal, which does not ensure reliability of the measured acceleration or speed and due to the presence of sensitive piezoelectric ele-ments, Having higher rigidity and requiring relatively large mechanical forces for generation of signals during mo-tion of acceleration and speed measurement object in automatic mode, which reduces sensitivity of accelerometer. Invention proposes new design and control scheme of three-dimensional piezoelectric accelerometer for measure-ment of dynamic parameters of moving objects in automatic mode. Wherein providing the position sensor of the moving measurement object with a three-axis signal detection unit to determine a direction of motion with meas-urement of acceleration or linear velocity when the measurement object moves along the coordinate axis; With the help of differential operational amplifiers through pulse generators and integrators, Speed measurement is provided by damping piezoelectric elements when the measurement object moves along one of the coordinate axes; Across the other two axes, the generated interference signals by amplitude are significantly reduced by their redemption; Having a piezoelectric element in the structure in the form of two-layer flat plates with an excitation section and a sensor section; Which generates signals at fast-changing acceleration and speed of moving object, amplitude of signal and sensitivity increases in 4-5 due to generation of signal by sensitive elements in vibration excitation mode created in accelerometer. Mathematical basis for accelerometer control circuits, mathematical model of its functioning is developed, applica-tion of which increases sensitivity of measurement of linear accelerations and speeds of moving objects and expands functional capabilities.
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Cappa, Paolo, Lorenzo Masia, and Fabrizio Patanè. "Numerical Validation of Linear Accelerometer Systems for the Measurement of Head Kinematics." Journal of Biomechanical Engineering 127, no. 6 (July 11, 2005): 919–28. http://dx.doi.org/10.1115/1.2049329.
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The purpose of this study was to analytically exploit the capabilities of head-mounted systems instrumented with linear accelerometers (ACs) for field use in redundant configurations. We simulated different headsets equipped with uni-, bi- or triaxial sensors with a number of axes that lie in the range of 12–24; the ACs were located on a hemispherical surface by adopting a priori criterion while their orientation was randomized. In addition, for a comparative purpose the nine accelerometer scheme (one triaxial AC and three biaxial ACs addressed in the following as “3-2-2-2 configuration”) was also analyzed in the present paper. We simulated and statistically assessed the performances of hemispherical headsets in the test case of a healthy subject walking freely at normal pace over level ground. The numerical results indicated that a well designed instrumented headset can retrieve the angular acceleration and (a0−g) component with rms errors of about 2% and 0.5%, respectively, and angular velocity with a drift error of about 20% in a 6s trial. On the contrary, the pose of the headset cannot be evaluated because of the drift induced by the integration process. In general, we can state that headsets with uni-, bi- or triaxial ACs have comparable performances. The main implications of the above-mentioned observations are (a) neither expensive triaxial ACs nor assembling procedure based on the use of orthogonal mounting blocks are needed; (b) redundant arrays of low-cost uni- or biaxial ACs can effectively be used to reach adequate performances in biomechanical studies where head acceleration and velocity are investigated; (c) while estimates of angular acceleration with accelerometers are accurate, estimations of angular velocities, linear velocities and pose are not.
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Rowson, Steven, Jonathan G. Beckwith, Jeffrey J. Chu, Daniel S. Leonard, Richard M. Greenwald, and Stefan M. Duma. "A Six Degree of Freedom Head Acceleration Measurement Device for Use in Football." Journal of Applied Biomechanics 27, no. 1 (February 2011): 8–14. http://dx.doi.org/10.1123/jab.27.1.8.
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The high incidence rate of concussions in football provides a unique opportunity to collect biomechanical data to characterize mild traumatic brain injury. The goal of this study was to validate a six degree of freedom (6DOF) measurement device with 12 single-axis accelerometers that uses a novel algorithm to compute linear and angular head accelerations for each axis of the head. The 6DOF device can be integrated into existing football helmets and is capable of wireless data transmission. A football helmet equipped with the 6DOF device was fitted to a Hybrid III head instrumented with a 9 accelerometer array. The helmet was impacted using a pneumatic linear impactor. Hybrid III head accelerations were compared with that of the 6DOF device. For all impacts, peak Hybrid III head accelerations ranged from 24 g to 176 g and 1,506 rad/s2to 14,431 rad/s2. Average errors for peak linear and angular head acceleration were 1% ± 18% and 3% ± 24%, respectively. The average RMS error of the temporal response for each impact was 12.5 g and 907 rad/s2.
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Bammann, Karin, Nicola K. Thomson, Birte Marie Albrecht, Duncan S. Buchan, and Chris Easton. "Generation and validation of ActiGraph GT3X+ accelerometer cut-points for assessing physical activity intensity in older adults. The OUTDOOR ACTIVE validation study." PLOS ONE 16, no. 6 (June 3, 2021): e0252615. http://dx.doi.org/10.1371/journal.pone.0252615.
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The study of physical activity in older adults is becoming more and more relevant. For evaluation of physical activity recommendations, intensity-specific accelerometer cut-points are utilized. However, research on accelerometer cut-points for older adults is still scarce. The aim of the study was to generate placement-specific cut-points of ActiGraph GT3X+ activity counts and raw measures of acceleration to determine physical activity intensity in older adults. A further aim was to compare the validity of the generated cut-points for a range of different physical activities. The study was a single experimental trial using a convenience sample. Study participants were 20 adults aged 59 to 73 years. Accelerometers were worn at six different placements (one on each wrist, one on each ankle, and two at the hip) and breath-by-breath indirect calorimetry was used as the reference for energy. The experiment comprised of two parts; a) The first required participants to walk on a treadmill at incremental speeds (3.0–5.0 km·h-1), and b) Five different everyday activities (reading, cleaning, shopping, cycling, aerobics) were staged in the laboratory setting. Accelerometer cut-points (activity counts, raw data) were derived for each of the investigated placements by linear regression using the treadmill part. Performance of the cut-points was assessed by applying the cut-points to the everyday activities. We provide cut-points for six placements and two accelerometer metrics in the specific age group. However, the derived cut-points did not outperform published ones. More research and innovative approaches are needed for improving internal and external validity of research results across populations and age groups.
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Staunton, Craig, Daniel Wundersitz, Brett Gordon, Edhem Custovic, Jonathan Stanger, and Michael Kingsley. "The Effect of Match Schedule on Accelerometry-Derived Exercise Dose during Training Sessions throughout a Competitive Basketball Season." Sports 6, no. 3 (July 23, 2018): 69. http://dx.doi.org/10.3390/sports6030069.
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Accelerometry-derived exercise dose (intensity × duration) was assessed throughout a competitive basketball season. Nine elite basketballers wore accelerometers during a Yo-Yo intermittent recovery test (Yo-Yo-IR1) and during three two-week blocks of training that represented phases of the season defined as easy, medium, and hard based on difficulty of match schedule. Exercise dose was determined using accumulated impulse (accelerometry-derived average net force × duration). Relative exercise intensity was quantified using linear relationships between average net force and oxygen consumption during the Yo-Yo-IR1. Time spent in different intensity zones was computed. Influences of match schedule difficulty and playing position were evaluated. Exercise dose reduced for recovery and pre-match tapering sessions during the medium match schedule. Exercise dose did not vary during the hard match schedule. Exercise dose was not different between playing positions. The majority of activity during training was spent performing sedentary behaviour or very light intensity activity (64.3 ± 6.1%). Front-court players performed a greater proportion of very light intensity activity (mean difference: 6.8 ± 2.8%), whereas back-court players performed more supramaximal intensity activity (mean difference: 4.5 ± 1.0%). No positional differences existed in the proportion of time in all other intensity zones. Objective evaluation of exercise dose might allow coaches to better prescribe and monitor the demands of basketball training.
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Claudino Budal Arins, Gabriel, Carla Elane da Silva dos Santos, Maruí Weber Corseuil Giehl, Tânia Rosane Bertoldo Benedetti, Cesar De Oliveira, Eleonora D’Orsi, and Cassiano Ricardo Rech. "Neighborhood environmental characteristics and sedentary behavior in later life: the EpiFloripa Study." Revista Brasileira de Atividade Física & Saúde 23 (August 14, 2018): 1–7. http://dx.doi.org/10.12820/rbafs.23e0007.
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Little is known about the relationship between perceived environmental characteristics and sedentary behavior (SB) using accelerometry in older adults. e aim of this study was to investigate the association between perceived neighborhood environmental characteristics and SB using accelerometry in 423 older adults from Florianopolis, Brazil. e time spent in SB was measured by an accelerometer (Actigraph-GT3X and GT3X+) for seven days and it was defined as < 100 counts per minute. Neighborhood characteristics were assessed using the 17-item of the A-NEWS scale. Linear regression was used to examine the association between perceived neighborhood environmental characteristics and SB. The results showed that older adults spent about 631.9 minutes/day in SB which corresponds to 66% of their waking time/day. Men who reported “access to shops” (β = -66.87; 95%CI: -113.80; -19.66), “access to services” (β = -65.65; 95%CI: -118.63; -12.61), “access to food shops” (β = -78.38; 95%CI: -123.79; -32.93) and “access to bus stop” (β = -66.69; 95%CI: -110.32; -22.95) spent over one hour less in SB. In women, lower SB was associated to easier “access to clubs and gyms” (β = -24.57; 95%CI: -48.13; -0.89) and “access to open spaces gyms” (β = -31.67 95%CI: -58.80; -4.21). These findings indicate that better access and greater diversity of places in the neighborhood environment could be an important factor to reduce SB in older Brazilian adults.
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Abbaspour-Sani, Ebrahim, Ruey-Shing Huang, and Chee Yee Kwok. "A wide-range linear optical accelerometer." Sensors and Actuators A: Physical 49, no. 3 (July 1995): 149–54. http://dx.doi.org/10.1016/0924-4247(95)01024-6.
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Lukyanov, Dmitry P., Alexander M. Boronakhin, Sergey Yu Shevchenko, Mariya A. Khivrich, and Temurmalik A. Amirov. "Microaccelerometer on Surface Acoustic Waves with a Ring Resonator on Anisotropic Material." Journal of the Russian Universities. Radioelectronics 22, no. 5 (December 4, 2019): 116–29. http://dx.doi.org/10.32603/1993-8985-2019-22-5-116-129.
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Introduction. Diagnostic systems are designed to monitor the condition of operational components (for example, on the railway). It is imperative that micro-electromechanical systems (MEMS) equipped with acceleration sensors (accelerometers) be used as part of measuring diagnostic systems. It is known that accelerometers are operated under increased vibration and repeated shock loads. This imposes a limitation both on the accelerometer design and the properties of materials from which these devices are produced.Aim. To develop a micromechanical accelerometer (MMA) for surface acoustic waves (SAW), capable of measuring shock effects.Materials and methods. The theoretical part of the study was carried out using the mathematical theory of differential equations, theoretical mechanics, finite element analysis and elements of SAW theory. In the course of the work, the following methods of mathematical processing were applied: MATLAB, Mathcad, Maple, COMSOL Multiphysics, OOFELIE: Multiphysics, Bluehill3 software, CorelDRAW. Experimental studies were also conducted using the INSTRON 5985 floor automated test system.Results. An original design of MMA on a SAW capable of measuring shock effects in hundreds of g was proposed. A sensing element (SE) of the sensor was developed. An analysis of the plate materials for their use as part of the SAW-based MMA design showed that SE from the quartz ST-cut material has a wider range of measured accelerations and a higher sensitivity threshold than SE from the YX-128˚ cut-off lithium niobate material. Requirements were developed to increase the SE sensitivity threshold. Design requirements were developed, and an interdigital transducer (IDT) topology in the form of a ring resonator was proposed. The following output characteristics were assessed: sensitivity threshold, dynamic range and scale factor. In addition, a procedure was developed for calculating MMA on a SAW with a ring resonator on an anisotropic material. It was found that the developed SE is characterized by a high sensitivity threshold, a wide dynamic range and a low transverse sensitivity.Conclusion. The technique proposed for designing a sensing element for use in solid-state linear acceleration sensors facilitates, depending on technical requirements, selection of construction materials and sensor design. Due to the originality of the design and engineering solutions, the proposed accelerometer allows measurements to be carried out across a wide range of impact loads.
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Ekelund, Ulf, Hanna Sepp, Sören Brage, Wulf Becker, Rupert Jakes, Mark Hennings, and Nicholas J. Wareham. "Criterion-related validity of the last 7-day, short form of the International Physical Activity Questionnaire in Swedish adults." Public Health Nutrition 9, no. 2 (April 2006): 258–65. http://dx.doi.org/10.1079/phn2005840.
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AbstractObjectiveTo examine the validity of the short, last 7-day, self-administered form of the International Physical Activity Questionnaire (IPAQ).DesignAll subjects wore an accelerometer for seven consecutive days and completed the IPAQ questionnaire on the eighth day. Criterion validity was assessed by linear regression analysis and by modified Bland–Altman analysis. Specificity and sensitivity were calculated for classifying respondents according to the physical activity guidelines of the American College of Sports Medicine/Centers for Disease Control and Prevention.SettingWorkplaces in Uppsala, Sweden.SubjectsOne hundred and eighty-five (87 males) participants, aged 20 to 69 years.ResultsTotal self-reported physical activity (PA) (MET-min day−1) was significantly correlated with average intensity of activity (counts min−1) from accelerometry (r=0.34, P<0.001). Gender, age, education and body mass index did not affect this relationship. Further, subcomponents of self-reported PA (time spent sitting, time in PA, time in moderate and vigorous activity (MVPA)) were significantly correlated with objectively measured PA (P<0.05). Self-reported time in PA was significantly different from time measured by accelerometry (mean difference: −25.9 min day−1; 95% limits of agreement: −172 to 120 min day−1; P<0.001). IPAQ identified 77% (specificity) of those who met the current PA guidelines of accumulating more than 30 min day−1 in MVPA as determined by accelerometry, whereas only 45% (sensitivity) of those not meeting the guidelines were classified correctly.ConclusionsOur results indicate that the short, last 7-days version of the IPAQ has acceptable criterion validity for use in Swedish adults. However, the IPAQ instrument significantly overestimated self-reported time spent in PA. The specificity to correctly classify people achieving current PA guidelines was acceptable, whereas the sensitivity was low.
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Steel, Chelsea, Carolina Bejarano, and Jordan A. Carlson. "Time Drift Considerations When Using GPS and Accelerometers." Journal for the Measurement of Physical Behaviour 2, no. 3 (September 1, 2019): 203–7. http://dx.doi.org/10.1123/jmpb.2019-0004.
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Purpose: To investigate potential time drift between devices when using Global Positioning Systems (GPS) and accelerometers in field-based research. Methods: Six Qstarz BT-Q1000XT GPS trackers, activPAL3 accelerometers, and ActiGraph GT3X+ and GT3X accelerometers were tested over 1–3 waves, each lasting 9–14 days. Once per day an event marker was created on each pair of devices concurrently. The difference in seconds between the time stamps for each event marker were calculated between each pair of GPS and activPAL devices and GPS and ActiGraph devices. Mixed-effects linear regression tested time drift across days and waves and between two rooms/locations (in an inner room vs. on a windowsill in an outer room). Results: The GPS trackers remained within one second of the computer clock across days and waves and between rooms. The activPAL devices drifted an average of 8.38 seconds behind the GPS devices over 14 days (p < .001). The ActiGraph GT3X+ devices drifted an average of 11.67 seconds ahead of the GPS devices over 14 days (p < .001). The ActiGraph GT3X devices drifted an average of 28.83 seconds behind the GPS devices over 9 days (p < .001). Time drift did not differ across waves but did differ between rooms and across devices. Conclusions: Time drift between the GPS and accelerometer models tested was minimal and is unlikely to be problematic when addressing many common research questions. However, studies that require high levels of precision when matching short (e.g., 1-second) time intervals may benefit from consideration of time drift and potential adjustments.
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Wood, Brian M., Herman Pontzer, Jacob A. Harris, Audax Z. P. Mabulla, Marc T. Hamilton, Theodore W. Zderic, Bret A. Beheim, and David A. Raichlen. "Step Counts From Satellites: Methods for Integrating Accelerometer and GPS Data for More Accurate Measures of Pedestrian Travel." Journal for the Measurement of Physical Behaviour 3, no. 1 (March 1, 2020): 58–66. http://dx.doi.org/10.1123/jmpb.2019-0016.
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The rapid adoption of lightweight activity tracking sensors demonstrates that precise measures of physical activity hold great value for a wide variety of applications. The corresponding growth of physical activity data creates an urgent need for methods to integrate such data. In this paper, we demonstrate methods for 1) synchronizing accelerometer and Global Positioning System (GPS) data with optimal corrections for device-related time drift, and 2) producing principled estimates of step counts from GPS data. These methods improve the accuracy of time-resolved physical activity measures and permit pedestrian travel from either sensor to be expressed in terms of a common currency, step counts. We show that sensor-based estimates of step length correspond well with expectations based on independent measures, and functional relationships between step length, height, and movement speed expected from biomechanical models. Using 123 person-days of data in which Hadza hunter-gatherers wore both GPS devices and accelerometers, we find that GPS-based estimates of daily step counts have a good correspondence with accelerometer-recorded values. A multivariate linear model predicting daily step counts from distance walked, mean movement speed, and height has an R2 value of 0.96 and a mean absolute percent error of 16.8% (mean absolute error = 1,354 steps; mean steps per day = 15,800; n = 123). To best represent step count estimation error, we fit a Bayesian model and plot the distributions of step count estimates it generates. Our methods more accurately situate accelerometer-based measures of physical activity in space and time, and provide new avenues for comparative research in biomechanics and human movement ecology.
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Meydan, T. "Recent trends in linear and angular accelerometers." Sensors and Actuators A: Physical 59, no. 1-3 (April 1997): 43–50. http://dx.doi.org/10.1016/s0924-4247(97)80146-x.
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Agafonov, V. M., E. V. Egorov, and D. L. Zaitsev. "Molecular electronic linear accelerometers. Preliminary test results." Gyroscopy and Navigation 1, no. 4 (October 2010): 246–51. http://dx.doi.org/10.1134/s2075108710040024.
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Ding, Ding, James F. Sallis, Gregory J. Norman, Lawrence D. Frank, Brian E. Saelens, Jacqueline Kerr, Terry L. Conway, et al. "Neighborhood Environment and Physical Activity Among Older Adults: Do the Relationships Differ by Driving Status?" Journal of Aging and Physical Activity 22, no. 3 (July 2014): 421–31. http://dx.doi.org/10.1123/japa.2012-0332.
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Some attributes of neighborhood environments are associated with physical activity among older adults. This study examined whether the associations were moderated by driving status. Older adults from neighborhoods differing in walkability and income completed written surveys and wore accelerometers (N = 880, mean age = 75 years, 56% women). Neighborhood environments were measured by geographic information systems and validated questionnaires. Driving status was defined on the basis of a driver’s license, car ownership, and feeling comfortable to drive. Outcome variables included accelerometer-based physical activity and self-reported transport and leisure walking. Multilevel generalized linear regression was used. There was no significant Neighborhood Attribute × Driving Status interaction with objective physical activity or reported transport walking. For leisure walking, almost all environmental attributes were positive and significant among driving older adults but not among nondriving older adults (five significant interactions at p < .05). The findings suggest that driving status is likely to moderate the association between neighborhood environments and older adults’ leisure walking.
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Tate, Eleanor B., Anuja Shah, Malia Jones, Mary Ann Pentz, Yue Liao, and Genevieve Dunton. "Toward a Better Understanding of the Link Between Parent and Child Physical Activity Levels: The Moderating Role of Parental Encouragement." Journal of Physical Activity and Health 12, no. 9 (September 2015): 1238–44. http://dx.doi.org/10.1123/jpah.2014-0126.
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Background:Research on adolescent physical activity is mixed regarding the role of parent activity. This study tested parent encouragement, direct modeling, and perceived influence as moderators of objectively-measured (accelerometer) parent and child moderate-to-vigorous physical activity (MVPA) associations.Methods:Parent-child dyads (n = 423; mean child age = 11.33 yrs.) wore accelerometers for 7 days; parents completed surveys. Hierarchical linear regression models tested moderation using a product of constituent terms interaction.Results:Parent-reported encouragement moderated the association between parent and child MVPA (β = –.15, P = .01, ΔR2 = .02, P < .01). Among parents with lower MVPA, child MVPA was higher for children receiving high encouragement (mean = 3.06, SE = .17) vs. low (mean = 3.03, SE = .15, P = .02) and moderate encouragement (mean = 3.40, SE = .09) vs. low (P = .04).Conclusions:Physical activity promotion programs may use parent encouragement as a tool to boost child activity, but must consider other child and parent characteristics that could attenuate effects.
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Sit, Cindy H. P., Wendy Y. Huang, Jane J. Yu, and Thomas L. McKenzie. "Accelerometer-Assessed Physical Activity and Sedentary Time at School for Children with Disabilities: Seasonal Variation." International Journal of Environmental Research and Public Health 16, no. 17 (August 30, 2019): 3163. http://dx.doi.org/10.3390/ijerph16173163.
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Schools are salient locations for children with disabilities to accrue physical activity (PA) and to diminish sedentary time (ST). We examined seasonal variation in accelerometer-assessed PA and ST among children with disabilities during the school day in three school settings (physical education (PE) lessons, recess and lunchtime). Children (n = 270) from 13 special schools for those with five disability types (visual impairments, hearing impairments, physical disabilities, intellectual disabilities (ID), and social development problems) participated. Their PA and ST were assessed during three winter and three summer school days using accelerometry. Linear mixed models were performed to determine seasonal variation in the proportion of time they spent in moderate-to-vigorous physical activity (MVPA) and ST in the three settings. On average, the children spent 4.5% (18.6 min) and 4.0% (15.6 min) in MVPA at school during winter and summer days, respectively. They were more physically active during winter (especially during recess and lunchtime), but there were no seasonal differences for ST. Thus, children’s year-round engagement in PA needs to be promoted, especially during summer.
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Van Kann, Dave H. H., Sanne I. de Vries, Jasper Schipperijn, Nanne K. de Vries, Maria W. J. Jansen, and Stef P. J. Kremers. "A Multicomponent Schoolyard Intervention Targeting Children’s Recess Physical Activity and Sedentary Behavior: Effects After 1 Year." Journal of Physical Activity and Health 14, no. 11 (November 1, 2017): 866–75. http://dx.doi.org/10.1123/jpah.2016-0656.
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Background: The aim of the study was to test the 12-month effects of a multicomponent physical activity (PA) intervention at schoolyards on morning recess PA levels of sixth- and seventh-grade children in primary schools, using accelerometry and additional global positioning system data. Methods: A quasi-experimental study design was used with 20 paired intervention and control schools. Global positioning system confirmatory analyses were applied to validate attendance at schoolyards during recess. Accelerometer data from 376 children from 7 pairs of schools were included in the final analyses. Pooled intervention effectiveness was tested by multilevel linear regression analyses, whereas effectiveness of intervention components was tested by multivariate linear regression analyses. Results: Children exposed to the multicomponent intervention increased their time spent in light PA (+5.9%) during recess. No pooled effects on moderate to vigorous PA were found. In-depth analyses of intervention components showed that physical schoolyard interventions particularly predicted a decrease in time spent in sedentary behavior during recess at follow-up. Intervention intensity and the school’s commitment to the project strengthened this effect. Conclusions: The multicomponent schoolyard PA intervention was effective in making children spend a larger proportion of recess time in light PA, which was most likely the result of a shift from sedentary behavior to light PA.
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Sandhu, Fargham, Hazlina Selamat, and Yahaya Md Sam. "Non-Linear Complementary SO(3) Filters for Attitude Estimation and Navigation of Ground Vehicles." Applied Mechanics and Materials 663 (October 2014): 254–58. http://dx.doi.org/10.4028/www.scientific.net/amm.663.254.
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The use of Inertial Navigational System (INS) has been proven to be suitable for vehicular stability and control. The same system can be used for inertial based navigation in the absence of GPS. In this paper, the problem of obtaining good attitude estimates from low cost sensors used for car navigation in the absence of GPS data is discussed. The states to be estimated are using angular velocity and linear accleration signals obtained from the sets of gyros and accelerometers of the INS. The special orthogonal group, the SO(3)-based complementary filters, have been used as the estimators as they are most suited for embedded systems to generate highly efficient algorithms for navigation. The INS has also been integrated with a set of magnetometers to assist in achieving global navigation. This integration requires kinematics equations as well as the inclusion of the gyro and accelerometer calibration and filtering. By using the quatronion representation, not only highly compact algorithms for integration can be generated, but it can also estimate and remove the effects of other biases and misalignments caused by, for instance, inaccurate installations and inherent sensors problems. The results obtained through simulation indicate better performance then Kalman filter approach as well as iterative recursive least square approach even with low grade sensors. The results are comparable with attitude estimation using roll index but with much less computations and better performance.