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Journal articles on the topic 'Triaxial accelerometer'

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Published: 4 June 2021
Last updated: 19 February 2023

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1

Zheng, Yuhuang. "Human Activity Recognition Based on the Hierarchical Feature Selection and Classification Framework." Journal of Electrical and Computer Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/140820.

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Human activity recognition via triaxial accelerometers can provide valuable information for evaluating functional abilities. In this paper, we present an accelerometer sensor-based approach for human activity recognition. Our proposed recognition method used a hierarchical scheme, where the recognition of ten activity classes was divided into five distinct classification problems. Every classifier used the Least Squares Support Vector Machine (LS-SVM) and Naive Bayes (NB) algorithm to distinguish different activity classes. The activity class was recognized based on the mean, variance, entropy of magnitude, and angle of triaxial accelerometer signal features. Our proposed activity recognition method recognized ten activities with an average accuracy of 95.6% using only a single triaxial accelerometer.
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2

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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Scheeper, Patrick, Jens Ole Gulløv, and Lars Munch Kofoed. "A piezoelectric triaxial accelerometer." Journal of Micromechanics and Microengineering 6, no. 1 (March 1, 1996): 131–33. http://dx.doi.org/10.1088/0960-1317/6/1/032.

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4

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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5

Yuan, Bo, Zhifeng Tang, Pengfei Zhang, and Fuzai Lv. "Thermal Calibration of Triaxial Accelerometer for Tilt Measurement." Sensors 23, no. 4 (February 13, 2023): 2105. http://dx.doi.org/10.3390/s23042105.

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The application of MEMS accelerometers used to measure inclination is constrained by their temperature dependence, and each accelerometer needs to be calibrated individually to increase stability and accuracy. This paper presents a calibration and thermal compensation method for triaxial accelerometers that aims to minimize cost and processing time while maintaining high accuracy. First, the number of positions to perform the calibration procedure is optimized based on the Levenberg-Marquardt algorithm, and then, based on this optimized calibration number, thermal compensation is performed based on the least squares method, which is necessary for environments with large temperature variations, since calibration parameters change at different temperatures. The calibration procedures and algorithms were experimentally validated on marketed accelerometers. Based on the optimized calibration method, the calibrated results achieved nearly 100 times improvement. Thermal drift calibration experiments on the triaxial accelerometer show that the thermal compensation scheme in this paper can effectively reduce drift in the temperature range of −40 °C to 60 °C. The temperature drifts of x- and y-axes are reduced from −13.2 and 11.8 mg to −0.9 and −1.1 mg, respectively. The z-axis temperature drift is reduced from −17.9 to 1.8 mg. We have conducted various experiments on the proposed calibration method and demonstrated its capacity to calibrate the sensor frame error model (SFEM) parameters. This research proposes a new low-cost and efficient strategy for increasing the practical applicability of triaxial accelerometers.
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6

de Graauw, Suzanne M., Janke F. de Groot, Marco van Brussel, Marjolein F. Streur, and Tim Takken. "Review of Prediction Models to Estimate Activity-Related Energy Expenditure in Children and Adolescents." International Journal of Pediatrics 2010 (2010): 1–14. http://dx.doi.org/10.1155/2010/489304.

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Purpose. To critically review the validity of accelerometry-based prediction models to estimate activity energy expenditure (AEE) in children and adolescents.Methods. The CINAHL, EMBASE, PsycINFO, and PubMed/MEDLINE databases were searched. Inclusion criteria were development or validation of an accelerometer-based prediction model for the estimation of AEE in healthy children or adolescents (6–18 years), criterion measure: indirect calorimetry, or doubly labelled water, and language: Dutch, English or German.Results. Nine studies were included. Median methodological quality was5.5±2.0 IR (out of a maximum 10 points). Prediction models combining heart rate and counts explained 86–91% of the variance in measured AEE. A prediction model based on a triaxial accelerometer explained 90%. Models derived during free-living explained up to 45%.Conclusions. Accelerometry-based prediction models may provide an accurate estimate of AEE in children on a group level. Best results are retrieved when the model combines accelerometer counts with heart rate or when a triaxial accelerometer is used. Future development of AEE prediction models applicable to free-living scenarios is needed.
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7

Gao, Yanbin, Lianwu Guan, and Tingjun Wang. "Triaxial Accelerometer Error Coefficients Identification with a Novel Artificial Fish Swarm Algorithm." Journal of Sensors 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/509143.

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Artificial fish swarm algorithm (AFSA) is one of the state-of-the-art swarm intelligence techniques, which is widely utilized for optimization purposes. Triaxial accelerometer error coefficients are relatively unstable with the environmental disturbances and aging of the instrument. Therefore, identifying triaxial accelerometer error coefficients accurately and being with lower costs are of great importance to improve the overall performance of triaxial accelerometer-based strapdown inertial navigation system (SINS). In this study, a novel artificial fish swarm algorithm (NAFSA) that eliminated the demerits (lack of using artificial fishes’ previous experiences, lack of existing balance between exploration and exploitation, and high computational cost) of AFSA is introduced at first. In NAFSA, functional behaviors and overall procedure of AFSA have been improved with some parameters variations. Second, a hybrid accelerometer error coefficients identification algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS) approaches. This combination leads to maximum utilization of the involved approaches for triaxial accelerometer error coefficients identification. Furthermore, the NAFSA-identified coefficients are testified with 24-position verification experiment and triaxial accelerometer-based SINS navigation experiment. The priorities of MCS-NAFSA are compared with that of conventional calibration method and optimal AFSA. Finally, both experiments results demonstrate high efficiency of MCS-NAFSA on triaxial accelerometer error coefficients identification.
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8

Микола Григорович Черняк, Владислав Володимирович Рибак, and Віктор Анатолійович Палюшок. "Calibration with specified accuracy of triaxial block of navigation accelerometers on the uniaxial rotary stand." MECHANICS OF GYROSCOPIC SYSTEMS, no. 28 (April 1, 2015): 5–15. http://dx.doi.org/10.20535/0203-377128201438955.

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The paper is devoted to solving the problem of calibration with specified precision of triaxial block of navigation accelerometers on the uniaxial rotary stand.In paper introduced all the characteristics, for calibration of triaxial block of navigation accelerometers on the uniaxial rotary stand, instrumental error sources upon which was obtained mathematical errors model of calibration. This model allows to calculate the error which the coefficients of metrology model of triaxial accelerometer unit was identified, if we have the numerical values of precision equipment errors.Using the mathematical errors model of calibration, and the quality criterion of calibration of triaxial block of navigation accelerometers unit, were obtained inequality that used to determine requirements for accuracy characteristics bench equipment, on which the calibration is performed. These requirements ensure the calibration of triaxial block of navigation accelerometers on the uniaxial rotary stand with preset accuracy.Experimental verification was conducted on comparable accuracy errors existing equipment and the requirements to this equipment , confirm the adequacy of the obtained inequalities.As the result of research were identified the most influential sources of instrumental errors, and provided recommendations to reduce their impacts.
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9

Sun, Yifan, and Xiang Xu. "Calibration of MEMS Triaxial Accelerometers Based on the Maximum Likelihood Estimation Method." Mathematical Problems in Engineering 2020 (September 21, 2020): 1–10. http://dx.doi.org/10.1155/2020/4617365.

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As a widely used inertial device, a MEMS triaxial accelerometer has zero-bias error, nonorthogonal error, and scale-factor error due to technical defects. Raw readings without calibration might seriously affect the accuracy of inertial navigation system. Therefore, it is necessary to conduct calibration processing before using a MEMS triaxial accelerometer. This paper presents a MEMS triaxial accelerometer calibration method based on the maximum likelihood estimation method. The error of the MEMS triaxial accelerometer comes into question, and the optimal estimation function is established. The calibration parameters are obtained by the Newton iteration method, which is more efficient and accurate. Compared with the least square method, which estimates the parameters of the suboptimal estimation function established under the condition of assuming that the mean of the random noise is zero, the parameters calibrated by the maximum likelihood estimation method are more accurate and stable. Moreover, the proposed method has low computation, which is more functional. Simulation and experimental results using the consumer low-cost MEMS triaxial accelerometer are presented to support the abovementioned superiorities of the maximum likelihood estimation method. The proposed method has the potential to be applied to other triaxial inertial sensors.
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10

Hyyti, Heikki, and Arto Visala. "A DCM Based Attitude Estimation Algorithm for Low-Cost MEMS IMUs." International Journal of Navigation and Observation 2015 (November 30, 2015): 1–18. http://dx.doi.org/10.1155/2015/503814.

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An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost microelectromechanical-system (MEMS) triaxial accelerometers and gyroscopes, that is, inertial measurement units (IMUs). Although these MEMS sensors are relatively cheap, they give more inaccurate measurements than conventional high-quality gyroscopes and accelerometers. To be able to use these low-cost MEMS sensors with precision in all situations, a novel attitude estimation algorithm is proposed for fusing triaxial gyroscope and accelerometer measurements. An extended Kalman filter is implemented to estimate attitude in direction cosine matrix (DCM) formation and to calibrate gyroscope biases online. We use a variable measurement covariance for acceleration measurements to ensure robustness against temporary nongravitational accelerations, which usually induce errors when estimating attitude with ordinary algorithms. The proposed algorithm enables accurate gyroscope online calibration by using only a triaxial gyroscope and accelerometer. It outperforms comparable state-of-the-art algorithms in those cases when there are either biases in the gyroscope measurements or large temporary nongravitational accelerations present. A low-cost, temperature-based calibration method is also discussed for initially calibrating gyroscope and acceleration sensors. An open source implementation of the algorithm is also available.
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11

Ikurior, Seer J., Nelly Marquetoux, Stephan T. Leu, Rene A. Corner-Thomas, Ian Scott, and William E. Pomroy. "What Are Sheep Doing? Tri-Axial Accelerometer Sensor Data Identify the Diel Activity Pattern of Ewe Lambs on Pasture." Sensors 21, no. 20 (October 13, 2021): 6816. http://dx.doi.org/10.3390/s21206816.

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Monitoring activity patterns of animals offers the opportunity to assess individual health and welfare in support of precision livestock farming. The purpose of this study was to use a triaxial accelerometer sensor to determine the diel activity of sheep on pasture. Six Perendale ewe lambs, each fitted with a neck collar mounting a triaxial accelerometer, were filmed during targeted periods of sheep activities: grazing, lying, walking, and standing. The corresponding acceleration data were fitted using a Random Forest algorithm to classify activity (=classifier). This classifier was then applied to accelerometer data from an additional 10 ewe lambs to determine their activity budgets. Each of these was fitted with a neck collar mounting an accelerometer as well as two additional accelerometers placed on a head halter and a body harness over the shoulders of the animal. These were monitored continuously for three days. A classification accuracy of 89.6% was achieved for the grazing, walking and resting activities (i.e., a new class combining lying and standing activity). Triaxial accelerometer data showed that sheep spent 64% (95% CI 55% to 74%) of daylight time grazing, with grazing at night reduced to 14% (95% CI 8% to 20%). Similar activity budgets were achieved from the halter mounted sensors, but not those on a body harness. These results are consistent with previous studies directly observing daily activity of pasture-based sheep and can be applied in a variety of contexts to investigate animal health and welfare metrics e.g., to better understand the impact that young sheep can suffer when carrying even modest burdens of parasitic nematodes.
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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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13

Łuczak, Sergiusz, Maciej Zams, and Karol Bagiński. "Selected Aging Effects in Triaxial MEMS Accelerometers." Journal of Sensors 2019 (November 18, 2019): 1–11. http://dx.doi.org/10.1155/2019/5184907.

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Natural aging of commercial triaxial low-g MEMS accelerometers, manufactured by surface micromachining, was evaluated in terms of changes of their offset voltages and scale factors, assigned to each sensitive axis. Two pieces of two models of triaxial accelerometers (ADXL 330 and ADXL 327 by Analog Devices Inc.) with analog outputs were tested within a period of ca. 4.5 years. Two different computer-controlled test rigs were used for performing relevant experimental studies, employing tilt angles as the reference source. Methodology of determining the proposed indicators of aging was based on cyclic repetition of the calibration procedure for each accelerometer. Changes of the output signals of the tested accelerometers were observed, resulting in respective indication errors of ca. 0.8% or even 2.2% while related to determining tilt. Since the accelerometers were operated under mild conditions while tested, much bigger errors are to be expected in the case of harsh conditions. Both pieces of ADXL 330 accelerometers ceased to operate properly within the testing period, approximately at the same time, for no apparent reason; thus, it is recommended to introduce redundancy in relevant reliable measuring circuits by doubling the number of the applied accelerometers.
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Yang, Fan, Ye Yuan, Zhong Yi Ma, and Xue Liu. "Structure Design of a Novel Triaxial Micro-Accelerometer." Advanced Materials Research 683 (April 2013): 745–49. http://dx.doi.org/10.4028/www.scientific.net/amr.683.745.

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This paper reports a new capacitive triaxial micro-accelerometer which consists of four identical dual beam-mass structure. Considering the temperature characteristic, beam consistency and zero bias and other factors of the accelerometer, the arrangement and anchor position, as well as matching capacitor are studied using ANSYS software to complete the design of the overall structure of the accelerometer. The research methed having been uesd is significant for optimizing structure of the micro-accelerometer.
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Huang, Peng-Sheng, Tian-Ling Ren, Qi-Wei Lou, Jian-She Liu, Li-Tian Liu, and Zhi-Jian Li. "Design of a Triaxial Piezoelectric Accelerometer." Integrated Ferroelectrics 56, no. 1 (June 2003): 1115–22. http://dx.doi.org/10.1080/10584580390259722.

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Plaza, J. A., H. Chen, J. Esteve, and E. Lora-Tamayo. "New bulk accelerometer for triaxial detection." Sensors and Actuators A: Physical 66, no. 1-3 (April 1998): 105–8. http://dx.doi.org/10.1016/s0924-4247(97)01735-4.

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Sipos, Martin, Pavel Paces, Jan Rohac, and Petr Novacek. "Analyses of Triaxial Accelerometer Calibration Algorithms." IEEE Sensors Journal 12, no. 5 (May 2012): 1157–65. http://dx.doi.org/10.1109/jsen.2011.2167319.

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Oguma, Yuko, Yusuke Osawa, Michiyo Takayama, Yukiko Abe, Shigeho Tanaka, I.-Min Lee, and Yasumichi Arai. "Validation of Questionnaire-Assessed Physical Activity in Comparison With Objective Measures Using Accelerometers and Physical Performance Measures Among Community-Dwelling Adults Aged ≥85 Years in Tokyo, Japan." Journal of Physical Activity and Health 14, no. 4 (April 2017): 245–52. http://dx.doi.org/10.1123/jpah.2016-0208.

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Background:To date, there is no physical activity (PA) questionnaire with convergent and construct validity for the oldest-old. The aim of the current study was to investigate the validity of questionnaire-assessed PA in comparison with objective measures determined by uniaxial and triaxial accelerometers and physical performance measures in the oldest-old.Methods:Participants were 155 elderly (mean age 90 years) who were examined at the university and agreed to wear an accelerometer for 7 days in the 3-year-follow-up survey of the Tokyo Oldest-Old Survey of Total Health. Fifty-nine participants wore a uniaxial and triaxial accelerometer simultaneously. Self-rated walking, exercise, and household PA were measured using a modified Zutphen PA Questionnaire (PAQ). Several physical performance tests were done, and the associations among PAQ, accelerometer-assessed PA, and physical performances were compared by Spearman’s correlation coefficients.Results:Significant, low to moderate correlations between PA measures were seen on questionnaire and accelerometer assessments (ρ = 0.19 to 0.34). Questionnaireassessed PA measure were correlated with a range of lower extremity performance (ρ = 0.21 to 0.29).Conclusions:This PAQ demonstrated convergent and construct validity. Our findings suggest that the PAQ can reasonably be used in this oldest-old population to rank their PA level.
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Jiang, Zhi Hua, Zong Yi Ma, and Ye Yuan. "Signal Detecting and Characteristic Measurement of a Capacitive Triaxial Micro-Accelerometer." Advanced Materials Research 765-767 (September 2013): 2164–67. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.2164.

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This paper introduces the principle of capacitive detection and specific method of signal detecting based on a triaxial micro-accelerometer. The corresponding detecting circuit is designed, and a suitable test system is set up. The sensitivity and accuracy test results of the triaxial micro-accelerometer show that all the masses sensitivity has nice consistency, the micro-accelerometer is feasible in theory and practice, and with the capability of precisely measuring the input acceleration in three directions.
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Staunton, Craig A., Mikael Swarén, Thomas Stöggl, Dennis-Peter Born, and Glenn Björklund. "The Relationship Between Cardiorespiratory and Accelerometer-Derived Measures in Trail Running and the Influence of Sensor Location." International Journal of Sports Physiology and Performance 17, no. 3 (March 1, 2022): 474–83. http://dx.doi.org/10.1123/ijspp.2021-0220.

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Purpose: To examine the relationship between cardiorespiratory and accelerometer-derived measures of exercise during trail running and determine the influence of accelerometer location. Methods: Eight trail runners (7 males and 1 female; age 26 [5] y; maximal oxygen consumption [] 70 [6] mL·kg−1·min−1) completed a 7-km trail run (elevation gain: 486 m), with concurrent measurements of , heart rate, and accelerations recorded from 3 triaxial accelerometers attached at the upper spine, lower spine, and pelvis. External exercise intensity was quantified from the accelerometers using PlayerLoad™ per minute and accelerometry-derived average net force. External exercise volume was calculated using accumulated PlayerLoad and the product of average net force and duration (impulse). Internal intensity was calculated using heart rate and -metrics; internal volume was calculated from total energy expenditure (work). All metrics were analyzed during both uphill (UH) and downhill (DH) sections of the trail run. Results: PlayerLoad and average net force were greater during DH compared with UH for all sensor locations (P ≤ .004). For all accelerometer metrics, there was a sensor position × gradient interaction (F2,1429.003; P <.001). The upper spine was lower compared with both pelvis (P ≤ .003) and lower spine (P ≤ .002) for all accelerometer metrics during both UH and DH running. Relationships between accelerometer and cardiorespiratory measures during UH running ranged from moderate negative to moderate positive (r = −.31 to .41). Relationships were stronger during DH running where there was a nearly perfect correlation between work and impulse (r = .91; P < .001). Conclusions: Simultaneous monitoring of cardiorespiratory and accelerometer-derived measures during trail running is suggested because of the disparity between internal and external intensities during changes in gradient. Sensor positioning close to the center of mass is recommended.
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Skotte, Jørgen, Mette Korshøj, Jesper Kristiansen, Christiana Hanisch, and Andreas Holtermann. "Detection of Physical Activity Types Using Triaxial Accelerometers." Journal of Physical Activity and Health 11, no. 1 (January 2014): 76–84. http://dx.doi.org/10.1123/jpah.2011-0347.

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Background:The aim of this study was to validate a triaxial accelerometer setup for identifying everyday physical activity types (ie, sitting, standing, walking, walking stairs, running, and cycling).Methods:Seventeen subjects equipped with triaxial accelerometers (ActiGraph GT3X+) at the thigh and hip carried out a standardized test procedure including walking, running, cycling, walking stairs, sitting, and standing still. A method was developed (Acti4) to discriminate between these physical activity types based on threshold values of standard deviation of acceleration and the derived inclination. Moreover, the ability of the accelerometer placed at the thigh to detect sitting posture was separately validated during free living by comparison with recordings of pressure sensors in the hip pockets.Results:Sensitivity for discriminating between the physical activity types sitting, standing, walking, running, and cycling in the standardized trials were 99%–100% and 95% for walking stairs. Specificity was higher than 99% for all activities. During free living (140 hours of measurements), sensitivity and specificity for detection of sitting posture were 98% and 93%, respectively.Conclusion:The developed method for detecting physical activity types showed a high sensitivity and specificity for sitting, standing, walking, running, walking stairs, and cycling in a standardized setting and for sitting posture during free living.
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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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Wundersitz, Daniel W. T., Paul B. Gastin, Samuel J. Robertson, and Kevin J. Netto. "Validity of a Trunk-Mounted Accelerometer to Measure Physical Collisions in Contact Sports." International Journal of Sports Physiology and Performance 10, no. 6 (September 2015): 681–86. http://dx.doi.org/10.1123/ijspp.2014-0381.

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Context: Accelerometer peak impact accelerations are being used to measure player physical demands in contact sports. However, their accuracy to do so has not been ascertained. Purpose: To compare peak-impact-acceleration data from an accelerometer contained in a wearable tracking device with a 3-dimensional motion-analysis (MA) system during tackling and bumping. Methods: Twenty-five semielite rugby athletes wore a tracking device containing a 100-Hz triaxial accelerometer (MinimaxX S4, Catapult Innovations, Australia). A single retroreflective marker was attached to the device, with its position recorded by a 12-camera MA system during 3 physical-collision tasks (tackle bag, bump pad, and tackle drill; N = 625). The accuracy, effect size, agreement, precision, and relative errors for each comparison were obtained as measures of accelerometer validity. Results: Physical-collision peak impact accelerations recorded by the accelerometer overestimated (mean bias 0.60 g) those recorded by the MA system (P < .01). Filtering the raw data at a 20-Hz cutoff improved the accelerometer’s relationship with MA data (mean bias 0.01 g; P > .05). When considering the data in 9 magnitude bands, the strongest relationship with the MA system was found in the 3.0-g or less band, and the precision of the accelerometer tended to reduce as the magnitude of impact acceleration increased. Of the 3 movements performed, the tackle-bag task displayed the greatest validity with MA. Conclusions: The findings indicate that the MinimaxX S4 accelerometer can accurately measure physical-collision peak impact accelerations when data are filtered at a 20-Hz cutoff frequency. As a result, accelerometers may be useful to measure physical collisions in contact sports.
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Schlegel, Christian, Gabriela Kiekenap, Holger Kahmann, and Rolf Kumme. "Mechanical influences in sinusoidal force measurement." ACTA IMEKO 4, no. 2 (June 29, 2015): 57. http://dx.doi.org/10.21014/acta_imeko.v4i2.206.

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The paper describes mechanical influences which disturb a sinusoidal force calibration and hence have an influence on measurement uncertainty. The measurements are based on the application of a scanning vibrometer and the use of triaxial accelerometers. The measuring of many acceleration points on the top mass of the transducer makes it possible to obtain acceleration distributions from which a standard deviation can be derived; the triaxial accelerometer allows the observance of certain effects, like rocking modes, or other problems related to specific excitation frequencies of the force transducer. Both measurements can be related to each other. The rocking effects are discussed with FEM model calculations.
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Kobsar, Dylan, Chad Olson, Raman Paranjape, and John M. Barden. "The Validity of Gait Variability and Fractal Dynamics Obtained From a Single, Body-Fixed Triaxial Accelerometer." Journal of Applied Biomechanics 30, no. 2 (April 2014): 343–47. http://dx.doi.org/10.1123/jab.2013-0107.

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A single triaxial accelerometer has the ability to collect a large amount of continuous gait data to quantitatively assess the control of gait. Unfortunately, there is limited information on the validity of gait variability and fractal dynamics obtained from this device. The purpose of this study was to test the concurrent validity of the variability and fractal dynamic measures of gait provided by a triaxial accelerometer during a continuous 10 minute walk in older adults. Forty-one healthy older adults were fitted with a single triaxial accelerometer at the waist, as well as a criterion footswitch device before completing a ten minute overground walk. The concurrent validity of six outcome measures was examined using intraclass correlation coefficients (ICC) and 95% limits of agreement. All six dependent variables measured by the accelerometer displayed excellent agreement with the footswitch device. Mean parameters displayed the highest validity, followed by measures of variability and fractal dynamics in stride times and measures of variability and fractal dynamics in step times. These findings suggest that an accelerometer is a valid and unique device that has the potential to provide clinicians with valid quantitative data for assessing their clients’ gait.
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Trisno, Roth, Parvathy Nair, Daniel Martin, Maryam S. Baghini, Hoam Chung, Gita Pendharkar, and Jayashri Kulkarni. "Using accelerometer as a diagnostic tool to detect drug-induced parkinsonism (DIP) secondary to first-generation anti-psychotic medications." Australasian Psychiatry 28, no. 3 (February 24, 2020): 348–53. http://dx.doi.org/10.1177/1039856220901467.

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Objective: The objective of this study is to examine the effectiveness of an accelerometer-based compact system in detecting and quantifying drug-induced parkinsonism (DIP) in patients with schizophrenia. Method: A pilot study controlled clinical trial comprising 6 people with schizophrenia and 11 control subjects was conducted at Alfred Health, Melbourne. Participants had their movements assessed using Barnes Akathisia Rating Scale (BARS), Simpson Angus Scale (SAS) and Movement Disorder Society Unified Parkinson’s Disease Rating Scale Part III (MDS-UPDRS III) followed by an assessment of gait using three triaxial accelerometers. Results: Median BARS, SAS, MDS-UPDRS III and accelerometer scores were significantly higher for patients with schizophrenia than controls. Accelerometers detected three times more rest tremor than clinical rating scales. Patients with schizophrenia had 70% of their dynamic acceleration at frequencies between 4 and 10 Hz, which is almost twice that observed in the control population (38%). Accelerometer scores were significantly correlated with BARS scores. Conclusion: Accelerometers were able to accurately detect patients with DIP better than some clinical rating scale including the SAS. Further larger-scale studies must be conducted to further demonstrate the accuracy of accelerometers in detecting DIP.
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Lotters, J. C., W. Olthuis, P. H. Veltink, and B. Piet. "On the design of a triaxial accelerometer." Journal of Micromechanics and Microengineering 5, no. 2 (June 1, 1995): 128–31. http://dx.doi.org/10.1088/0960-1317/5/2/018.

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Mayagoitia, Ruth E., Joost C. Lötters, Peter H. Veltink, and Hermie Hermens. "Standing balance evaluation using a triaxial accelerometer." Gait & Posture 16, no. 1 (August 2002): 55–59. http://dx.doi.org/10.1016/s0966-6362(01)00199-0.

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Bernmark, Eva, and Christina Wiktorin. "A triaxial accelerometer for measuring arm movements." Applied Ergonomics 33, no. 6 (November 2002): 541–47. http://dx.doi.org/10.1016/s0003-6870(02)00072-8.

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Ye, Lin, Ying Guo, and Steven W. Su. "An Efficient Autocalibration Method for Triaxial Accelerometer." IEEE Transactions on Instrumentation and Measurement 66, no. 9 (September 2017): 2380–90. http://dx.doi.org/10.1109/tim.2017.2706479.

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VAN HEES, VINCENT T., SANDER M. SLOOTMAKER, GERT DE GROOT, WILLEM VAN MECHELEN, and ROB C. VAN LUMMEL. "Reproducibility of a Triaxial Seismic Accelerometer (DynaPort)." Medicine & Science in Sports & Exercise 41, no. 4 (April 2009): 810–17. http://dx.doi.org/10.1249/mss.0b013e31818ff636.

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McHugh, M. P., S. Y. Kwiecien, M. P. Hannon, and R. J. Stewart. "G-Force Exposure in a Contact Sport: The Use of Accelerometers to Quantify Physical Stress." Journal of Sports Research 1, no. 1 (September 15, 2014): 12–21. http://dx.doi.org/10.18488/journal.90/2014.1.1/90.1.12.21.

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GPS-based analyses of movement patterns are inadequate for quantifying the physical stress imposed on athletes in contact sports. Accelerometers may be useful for monitoring such athletes. The purpose of this study was to use triaxial accelerometers to record G-force exposure in Gaelic football players to examine differences in G-force exposure between games and practices and between playing positions. A small triaxial accelerometer with a flash memory chip data logger was fitted to the waistband of players’ shorts. Game and practice data were acquired at 100 Hz (scale ±16G) from 19 club level players (age 25±7 yr). Resultant G-force was: calculated for each data point from the raw accelerometer data collected in all three planes of motion and analyzed by quantifying the time spent above different G-force thresholds. Player positions were categorized as central (half backs/half forwards/midfield) and peripheral (full back/full forward) with central players typically more involved in continuous running. ANOVA with Bonferroni corrections was used to compare G-force exposure between games vs. practices, and between central vs. peripheral players (practice not position dependent). Differences between games and practices were apparent for time >3G, >4G, and >5G with more time at these thresholds in practices versus games (P=0.003), indicating higher G-force exposure in practices versus games. In games central players had greater time at >2G and >3G (P<0.001). Accelerometry analysis was effective in distinguishing player position-dependent differences in G-force exposure, and differences between games and practices. These differences indicate that the method of analysis of G-force exposure used here may be of utility for quantifying the physical stresses imposed on athletes in contact sports.
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Wang, Jian Yan, Ting Ting Wang, and Hang Guo. "A New Design of a Piezoelectric Triaxial Micro-Accelerometer." Key Engineering Materials 645-646 (May 2015): 841–46. http://dx.doi.org/10.4028/www.scientific.net/kem.645-646.841.

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Accelerometer in MEMS always is made by capacitive or piezoresistive, whose dynamic response is not good, the operating frequency is narrow, and the cross-axis sensitivity is low. A new type of piezoelectric micro-accelerometer is designed, and its structure is “x” type. The sensing unit is piezoelectric PZT films, which is achieved by sol-gel method. The accelerometer is a triaxial accelerometer. The theoretical and simulation analysis is used to achieve the charge sensitivity and response frequency, and also get the optimal structural parameters. A new circuit connection is proposed to improve the sensitivity and avoid the cross-axis sensitivity. The design achieves the z-axis sensitivity with more than 40 pC/g, x, y-axis sensitivity with more than 8pC/g, and the response frequency is about 3000Hz.
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Lynch, Brian A., Tara K. Kaufman, Tamim I. Rajjo, K. Mohammed, Seema Kumar, M. Hassan Murad, Natalie E. Gentile, Gabriel A. Koepp, Shelly K. McCrady-Spitzer, and James A. Levine. "Accuracy of Accelerometers for Measuring Physical Activity and Levels of Sedentary Behavior in Children: A Systematic Review." Journal of Primary Care & Community Health 10 (January 2019): 215013271987425. http://dx.doi.org/10.1177/2150132719874252.

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Objectives: This systematic review evaluated the accuracy of triaxial and omnidirectional accelerometers for measuring physical activity and sedentary behavior in children. Design: Systematic review of the literature. Methods: We comprehensively searched several databases for studies published from January 1996 through June 2018 that reported diagnostic accuracy measures in children and adolescents (age 3-18 years) and compared accelerometers with energy expenditure using indirect calorimetry. Results: We included 11 studies that enrolled 570 participants. All studies used indirect calorimetry as the reference standard. Across the studies, median sensitivity ranged from 46% to 96% and median specificity ranged from 71% to 96%. Median area under the curve ranged from 69% to 98%. Conclusions: Accuracy measures were greatest when detecting sedentary behavior and lowest when detecting light physical activity. Accuracy was higher when the accelerometer was placed on the hip compared with the wrist. The current evidence suggests that triaxial and omnidirectional accelerometers are accurate in measuring sedentary behavior and physical activity levels in children.
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Eston, Roger G., Ann V. Rowlands, and David K. Ingledew. "Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children’s activities." Journal of Applied Physiology 84, no. 1 (January 1, 1998): 362–71. http://dx.doi.org/10.1152/jappl.1998.84.1.362.

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Eston, Roger G., Ann V. Rowlands, and David K. Ingledew.Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children’s activities. J. Appl. Physiol. 84(1): 362–371, 1998.—Heart rate telemetry is frequently used to estimate daily activity in children and to validate other methods. This study compared the accuracy of heart rate monitoring, pedometry, triaxial accelerometry, and uniaxial accelerometry for estimating oxygen consumption during typical children’s activities. Thirty Welsh children (mean age 9.2 ± 0.8 yr) walked (4 and 6 km/h) and ran (8 and 10 km/h) on a treadmill, played catch, played hopscotch, and sat and crayoned. Heart rate, body accelerations in three axes, pedometry counts, and oxygen uptake were measured continuously during each 4-min activity. Oxygen uptake was expressed as a ratio of body mass raised to the power of 0.75 [scaled oxygen uptake (sV˙o 2)]. All measures correlated significantly ( P < 0.001) with sV˙o 2. A multiple-regression equation that included triaxial accelerometry counts and heart rate predicted sV˙o 2 better than any measure alone ( R 2 = 0.85, standard error of the estimate = 9.7 ml ⋅ kg−0.75 ⋅ min−1). The best of the single measures was triaxial accelerometry ( R 2 = 0.83, standard error of the estimate = 10.3 ml ⋅ kg−0.75 ⋅ min−1). It is concluded that a triaxial accelerometer provides the best assessment of activity. Pedometry offers potential for large population studies.
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Krasnoff, Joanne B., Michael A. Kohn, Frankie K. K. Choy, Julie Doyle, Kirsten Johansen, and Patricia L. Painter. "Interunit and Intraunit Reliability of the RT3 Triaxial Accelerometer." Journal of Physical Activity and Health 5, no. 4 (July 2008): 527–38. http://dx.doi.org/10.1123/jpah.5.4.527.

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Background:Interest in the quantification of physical activity is on the rise. Tri-axial accelerometry has frequently been used; however, research on the reliability of these devices is limited. We examine the interunit and intraunit reliability of 22 RT3 triaxial accelerometers using a performance-documented laboratory agitator.Methods:The RT3 units were tested while moving in 2 directions (antero-posterior, medio-lateral) and speeds (150 and 275 RPM) on a shaker with simultaneous documented performance output for three 24-hour periods.Results:Minimal shaker variance was recorded for all trials (coefficients of variation [CVs] < 0.52%). Our data demonstrate good reliability within RT3s (CVs < 1.81%) but poor reliability among the 22 units (CVs range = 9.5% to 34.7%).Conclusions:In longitudinal studies, each subject should use the same RT3 unit at each assessment. The use of multiple RT3 units in cross-sectional studies is not recommended because data interpretation would be compromised by the high between-unit variability.
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Hettiarachchi, Pasan, Katarina Aili, Andreas Holtermann, Emmanuel Stamatakis, Magnus Svartengren, and Peter Palm. "Validity of a Non-Proprietary Algorithm for Identifying Lying Down Using Raw Data from Thigh-Worn Triaxial Accelerometers." Sensors 21, no. 3 (January 29, 2021): 904. http://dx.doi.org/10.3390/s21030904.

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Body postural allocation during daily life is important for health, and can be assessed with thigh-worn accelerometers. An algorithm based on sedentary bouts from the proprietary ActivePAL software can detect lying down from a single thigh-worn accelerometer using rotations of the thigh. However, it is not usable across brands of accelerometers. This algorithm has the potential to be refined. Aim: To refine and assess the validity of an algorithm to detect lying down from raw data of thigh-worn accelerometers. Axivity-AX3 accelerometers were placed on the thigh and upper back (reference) on adults in a development dataset (n = 50) and a validation dataset (n = 47) for 7 days. Sedentary time from the open Acti4-algorithm was used as input to the algorithm. In addition to the thigh-rotation criterion in the existing algorithm, two criteria based on standard deviation of acceleration and a time duration criterion of sedentary bouts were added. The mean difference (95% agreement-limits) between the total identified lying time/day, between the refined algorithm and the reference was +2.9 (−135,141) min in the development dataset and +6.5 (−145,159) min in the validation dataset. The refined algorithm can be used to estimate lying time in studies using different accelerometer brands.
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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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Łuczak, Sergiusz, Maciej Zams, Bogdan Dąbrowski, and Zbigniew Kusznierewicz. "Tilt Sensor with Recalibration Feature Based on MEMS Accelerometer." Sensors 22, no. 4 (February 15, 2022): 1504. http://dx.doi.org/10.3390/s22041504.

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The main errors of MEMS accelerometers are misalignments of their sensitivity axes, thermal and long-term drifts, imprecise factory calibration, and aging phenomena. In order to reduce these errors, a two-axial tilt sensor comprising a triaxial MEMS accelerometer, an aligning unit, and solid cubic housing was built. By means of the aligning unit it was possible to align the orientation of the accelerometer sensitive axes with respect to the housing with an accuracy of 0.03°. Owing to the housing, the sensor could be easily and quickly recalibrated, and thus errors such as thermal and long-term drifts as well as effects of aging were eliminated. Moreover, errors due to local and temporal variations of the gravitational acceleration can be compensated for. Procedures for calibrating and aligning the accelerometer are described. Values of thermal and long-term drifts of the tested sensor, resulting in tilt errors of even 0.4°, are presented. Application of the sensor for monitoring elevated loads is discussed.
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Ohkawara, Kazunori, Yoshitake Oshima, Yuki Hikihara, Kazuko Ishikawa-Takata, Izumi Tabata, and Shigeho Tanaka. "Real-time estimation of daily physical activity intensity by a triaxial accelerometer and a gravity-removal classification algorithm." British Journal of Nutrition 105, no. 11 (January 25, 2011): 1681–91. http://dx.doi.org/10.1017/s0007114510005441.

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We have recently developed a simple algorithm for the classification of household and locomotive activities using the ratio of unfiltered to filtered synthetic acceleration (gravity-removal physical activity classification algorithm, GRPACA) measured by a triaxial accelerometer. The purpose of the present study was to develop a new model for the immediate estimation of daily physical activity intensities using a triaxial accelerometer. A total of sixty-six subjects were randomly assigned into validation (n 44) and cross-validation (n 22) groups. All subjects performed fourteen activities while wearing a triaxial accelerometer in a controlled laboratory setting. During each activity, energy expenditure was measured by indirect calorimetry, and physical activity intensities were expressed as metabolic equivalents (MET). The validation group displayed strong relationships between measured MET and filtered synthetic accelerations for household (r 0·907, P < 0·001) and locomotive (r 0·961, P < 0·001) activities. In the cross-validation group, two GRPACA-based linear regression models provided highly accurate MET estimation for household and locomotive activities. Results were similar when equations were developed by non-linear regression or sex-specific linear or non-linear regressions. Sedentary activities were also accurately estimated by the specific linear regression classified from other activity counts. Therefore, the use of a triaxial accelerometer in combination with a GRPACA permits more accurate and immediate estimation of daily physical activity intensities, compared with previously reported cut-off classification models. This method may be useful for field investigations as well as for self-monitoring by general users.
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41

Łuczak, Sergiusz, Robert Grepl, and Maciej Bodnicki. "Selection of MEMS Accelerometers for Tilt Measurements." Journal of Sensors 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/9796146.

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In order to build a tilt sensor having a desired sensitivity and measuring range, one should select an appropriate type, orientation, and initial position of an accelerometer. Various cases of tilt measurements are considered: determining exclusively pitch, axial tilt, or both pitch and roll, where Cartesian components of the gravity acceleration are measured by means of low-g uni-, bi-, tri-, or multiaxial micromachined accelerometers. 15 different orientations of such accelerometers are distinguished (each illustrated with respective graphics) and related to the relevant mathematical formulas. Results of the performed experimental study revealed inherent misalignments of the sensitive axes of micromachined accelerometers as large as 1°. Some of the proposed orientations make it possible to avoid a necessity of using the most misaligned pairs of the sensitive axes; some increase the accuracy of tilt measurements by activating all the sensitive axes or reducing the effects of anisotropic properties of micromachined triaxial accelerometers; other orientations make it possible to reduce a necessary number of the sensitive axes at full measurement range. An increase of accuracy while using multiaxial accelerometers is discussed. Practical guidelines for an optimal selection of a particular micromachined accelerometer for a specific case of tilt measurement are provided.
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42

Komarizadehasl, Seyedmilad, Fidel Lozano, Jose Antonio Lozano-Galant, Gonzalo Ramos, and Jose Turmo. "Low-Cost Wireless Structural Health Monitoring of Bridges." Sensors 22, no. 15 (July 30, 2022): 5725. http://dx.doi.org/10.3390/s22155725.

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Nowadays, low-cost accelerometers are getting more attention from civil engineers to make Structural Health Monitoring (SHM) applications affordable and applicable to a broader range of structures. The present accelerometers based on Arduino or Raspberry Pi technologies in the literature share some of the following drawbacks: (1) high Noise Density (ND), (2) low sampling frequency, (3) not having the Internet’s timestamp with microsecond resolution, (4) not being used in experimental eigenfrequency analysis of a flexible and a less-flexible bridge, and (5) synchronization issues. To solve these problems, a new low-cost triaxial accelerometer based on Arduino technology is presented in this work (Low-cost Adaptable Reliable Accelerometer—LARA). Laboratory test results show that LARA has a ND of 51 µg/√Hz, and a frequency sampling speed of 333 Hz. In addition, LARA has been applied to the eigenfrequency analysis of a short-span footbridge and its results are compared with those of a high-precision commercial sensor.
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43

HIIRAGI, Yukinobu. "Evaluation of Postural Sway Using a Triaxial Accelerometer." Rigakuryoho Kagaku 19, no. 4 (2004): 305–9. http://dx.doi.org/10.1589/rika.19.305.

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Reichenbach, Ralf, Dietrich Schubert, and Gerald Gerlach. "Dreiachsiger Beschleunigungssensor in Oberflächenmikromechanik (Surface Micromachined Triaxial Accelerometer)." tm - Technisches Messen 70, no. 5-2003 (May 2003): 225–32. http://dx.doi.org/10.1524/teme.70.5.225.20044.

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Brown, David A., Boris Aronov, Lawrence Reinhart, Glenn Volkema, and Tetsuro Oishi. "Prototype high‐sensitivity triaxial pressure gradient acoustic accelerometer." Journal of the Acoustical Society of America 110, no. 5 (November 2001): 2753. http://dx.doi.org/10.1121/1.4777591.

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Maddison, Ralph, Yannan Jiang, Stephen Vander Hoorn, Cliona Ni Mhurchu, Carlene M. M. Lawes, Anthony Rodgers, and Elaine Rush. "Estimating Energy Expenditure With the RT3 Triaxial Accelerometer." Research Quarterly for Exercise and Sport 80, no. 2 (June 2009): 249–56. http://dx.doi.org/10.1080/02701367.2009.10599559.

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Neri, Thomas, Antoine Lamotte, Tommaso Bonanzinga, Frederic Farizon, and Remi Philippot. "Comparison of the use of a laximeter and a triaxial accelerometer for Anterolateral ligament injury diagnosis in ACL deficient knee." Orthopaedic Journal of Sports Medicine 7, no. 5_suppl3 (May 1, 2019): 2325967119S0020. http://dx.doi.org/10.1177/2325967119s00206.

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Objectives: The objective of this study was to compare the use of a laximeter and a triaxial accelerometer, for Anterolateral ligament injury diagnosis of in ACL deficient knee. We hypothesized that a triaxial accelerometer was more effective than a laximeter. Methods: A total of 11 cadaver knees were studied according to a new conservative dissection protocol without damage to the lateral structures. A GnRB® laximeter (Genourob, France) was used to determine anterior tibial translation (AP) of the tibia. Simultaneously, a KiRA® triaxial accelerometer (Kinetic Rapid Assessment) (OrthoKey, Italy) was used to determine two parameters: the AP translation and the Pivot Shift (PS). For each knee, 5 conditions were successively applied: intact knee (intact), knee with ALL (ALLsec) isolated section, knee with ALL and ACL section (ALL + ACLsec). Results: For the laximeter, the ACL and ALL sections led to a significant AP translation increase: + 2.1 mm for the ACL section, and + 0.9 mm for the ALL section. This difference was significant regardless of the level of force applied (p <0.05). For the triaxial accelerometer, the ACL and the ALL sections led to a significant AP translation increase: + 2.8 mm for ACL, and + 1.5 mm for ALL section. In contrast, for the PS, the increase was more consistent. There was a multiplier factor between the ACLsec condition and the ACL + ALLsec condition comparable to that between the intact condition and the ACLsec condition (P> 0.05). Conclusion: Whatever the device, the AP translation difference induced by the ALL injury, of the order of mm, remains too small to make the diagnosis of an ALL injury. The evaluation of the AP translation is therefore not a relevant to diagnostic an ALL injury. With greater increase, the evaluation of the rotatory laxity, through the PS test, is more relevant. In current practice, there is no clinical interest to use a laximeter or accelerometer on AP translation assessment to diagnosis an ALL injury in a deficient ACL knee. On the other hand, the use of a triaxial accelerometer to quantify the lateral tibial plateau acceleration in the pivot shift test appears to be relevant for detecting an ALL injury on a deficient ACL knee. These findings help provide clinical guidelines for more effective objective measures to diagnose ALL injury, and determine the most effective management for each patient.
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Shimoda, T., W. Kokuyama, and H. Nozato. "A low-acceleration measurement using anti-vibration table with low-frequency resonance." ACTA IMEKO 9, no. 5 (December 31, 2020): 369. http://dx.doi.org/10.21014/acta_imeko.v9i5.1003.

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This manuscript describes how NMIJ isolates interferometer optics from the ground vibration for low-acceleration measurement by installing an anti-vibration table. Such a vibration isolation system is designed for an accelerometer calibration system to reduce vibration noise from the microtremor or from reaction of the vibration exciter. Mitigating the vibration of optics enables evaluation of accelerometers at small amplitudes, which is required in aerospace or infrastructure monitoring applications. In this manuscript, vibration transmissibility of the anti-vibration table is measured using a triaxial seismometer, and its benefit in the calibration system is discussed.
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Downer, Josh, and Timothy G. Haskell. "Ice-floe kinematics in the Ross Sea marginal ice zone using GPS and accelerometers." Annals of Glaciology 33 (2001): 345–49. http://dx.doi.org/10.3189/172756401781818923.

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AbstractAn experiment to investigate wave-induced floe response and floe-floe interactions was conducted in the Ross Sea marginal ice zone during austral summer 1999. Three types of sensors were used: global positioning system (GPS) receivers; triaxial accelerometers; and compasses. The accelerometer data reveal consistent bands of energy centred at about 0.1 and 1.35 Hz, the latter an unexplained but common feature of such experiments. The GPS data also contain energy near 0.1 Hz, which may suggest that GPS receivers can detect the ocean-wave-induced lateral motion of ice floes.
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Zheng, Yonglei, Weng-Keen Won, Xinze Guan, and Stewart Trost. "Physical Activity Recognition from Accelerometer Data Using a Multi-Scale Ensemble Method." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 2 (July 14, 2013): 1575–81. http://dx.doi.org/10.1609/aaai.v27i2.18997.

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Accurate and detailed measurement of an individual’s physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.
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