Artykuły w czasopismach na temat „Accelerometer”
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Roth, Marilyn A., i Jennifer S. Mindell. "Who Provides Accelerometry Data? Correlates of Adherence to Wearing an Accelerometry Motion Sensor: The 2008 Health Survey for England". Journal of Physical Activity and Health 10, nr 1 (styczeń 2013): 70–78. http://dx.doi.org/10.1123/jpah.10.1.70.
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Background:Use of objective physical activity measures is rising. We investigated the representativeness of survey participants who wore an accelerometer.Methods:4273 adults aged 16+ from a cross-sectional survey of a random, nationally representative general population sample in England in 2008 were categorized as 1) provided sufficient accelerometry data [4−7 valid days (10+ hrs/d), n = 1724], 2) less than that (n = 237), or 3) declined (n = 302). Multinomial logistic regression identified demographic, socioeconomic, health, lifestyle, and biological correlates of participants in these latter 2 groups, compared with those who provided sufficient accelerometry data (4+ valid days).Results:Those in the random subsample offered the accelerometer were older and more likely to be retired and to report having a longstanding limiting illness than the rest of the adult Health Survey for England participants. Compared with those providing sufficient accelerometery data, those wearing the accelerometer less were younger, less likely to be in paid employment, and more likely to be a current smoker. Those who declined to wear an accelerometer did not differ significantly from those who wore it for sufficient time.Conclusions:We found response bias in wearing the accelerometers for sufficient time, but refusers did not differ from those providing sufficient data. Differences should be acknowledged by data users.
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Kelly, Stephen J., Aron J. Murphy, Mark L. Watsford, Damien Austin i Michael Rennie. "Reliability and Validity of Sports Accelerometers During Static and Dynamic Testing". International Journal of Sports Physiology and Performance 10, nr 1 (styczeń 2015): 106–11. http://dx.doi.org/10.1123/ijspp.2013-0408.
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Purpose:To investigate the validity and reliability of accelerometry of the SPI-ProX II dual data logger (GPSports, Canberra, Australia).Methods:Controlled laboratory assessments determined the accuracy and reproducibility of raw accelerometer data. Intra- and interdevice reliability assessed the ability of the SPI-ProX II accelerometers to repeatedly measure peak gravitational accelerations (g) during impact-based testing. Static and dynamic validity testing assessed the accuracy of SPI-ProX II accelerometers against a criterion-referenced accelerometer. Dynamic validity was assessed over a range of frequencies from 5 to 15 Hz.Results:Intradevice reliability found no differences (P < .05) between 4 SPI-ProX II accelerometers, with a low coefficient of variation (1.87–2.21%). SPI-ProX II accelerometers demonstrated small to medium effect-size (ES) differences (0.10–0.44) between groups and excellent interdevice reliability, with no difference found between units (F = 0.826, P = .484). Validity testing revealed significant differences between devices (P = .001), with high percentage differences (27.5–30.5%) and a large ES (>3.44).Conclusions:SPI-ProX II accelerometers demonstrated excellent intra- and interaccelerometer reliability. However, static and dynamic validity were poor, and caution is recommended when measuring the absolute magnitude of acceleration, particularly for high-frequency movements. Regular assessment of individual devices is advised, particularly for mechanical damage and signal-drift errors. It is recommended that guidelines be provided by the manufacturer on measuring shifts in the base accelerometer signal, including time frames for assessing accelerometer axis, magnitude of errors, and calibration of accelerometers from a stable reference point.
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Xie, Yilin, Song Zhang, Xiaolin Meng, Dinh Tung Nguyen, George Ye i Haiyang Li. "An Innovative Sensor Integrated with GNSS and Accelerometer for Bridge Health Monitoring". Remote Sensing 16, nr 4 (6.02.2024): 607. http://dx.doi.org/10.3390/rs16040607.
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This paper presents an innovative integrated sensor that combines GNSS and a low-cost accelerometer for bridge health monitoring. GNSS and accelerometers are both significant and effective sensors for structural monitoring, but they each have limitations. The sampling rate of GNSS data is relatively low, making it challenging to capture high-frequency vibrations, while accelerometers struggle with low-frequency signals and are susceptible to environmental changes. Additionally, GNSS receivers and accelerometers are often installed separately, leading to challenges in data fusion processing due to differing temporal and geospatial references. The proposed integrated sensor addresses these issues by synchronizing GNSS and an accelerometer’s time and geospatial coordinate reference. This allows for a more accurate and reliable deformation and vibration measurement for bridge monitoring. The performance of the new sensor was assessed using a high-quality/cost Leica GM30 GNSS receiver and a Sherborne A545 accelerometer. Experiments conducted on the Wilford suspension bridge demonstrate the effectiveness of this innovative integrated sensor in measuring deformation and vibration for bridge health monitoring. The limitation of the low-cost MEMS (Micro Electromechanical System) accelerometer for the weak motion frequency detection is also pointed out.
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Qin, Xuan, i Ludan Tang. "An Environmental Monitoring Method of Ancient Buildings Based on the Micro Electro Mechanical System Accelerometers". Journal of Nanoelectronics and Optoelectronics 19, nr 1 (1.01.2024): 36–45. http://dx.doi.org/10.1166/jno.2024.3521.
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In order to evaluate and compare the performance of MEMS accelerometers for the environmental monitoring of ancient buildings, four MEMS accelerometers of different types and a G1B-type force-balanced accelerometer are selected and installed on the same location in an ancient building for field testing. The ambient environmental monitoring of the building recorded by the MEMS accelerometers is compared with the G1B accelerometer in terms of time history, Fourier spectrum, and modal frequency identification. In addition, the earthquake-induced structural responses of the ancient building recorded by MEMS-I type accelerometer is compared with those recorded by the G1B accelerometer in both time and frequency domain. The test results show that the noise levels of the four MEMS accelerometers are all higher than that of the G1B accelerometer. Among them, the MEMS-I type accelerometer has a relatively lower level of sensor noise and achieves a good match with the G1B accelerometer in terms of modal frequency identification and earthquake-induced structural environmental measurement, which proves that the MEMS-I type accelerometer can record the strong structural vibration with acceptable accuracy and is feasible for daily environmental monitoring of the ancient buildings.
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Clark, Cain C. T., Claire M. Barnes, Mark Holton, Huw D. Summers i Gareth Stratton. "SlamTracker Accuracy under Static and Controlled Movement Conditions". Sport Science Review 25, nr 5-6 (1.12.2016): 374–83. http://dx.doi.org/10.1515/ssr-2016-0020.
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Abstract Accelerometry is the de facto standard in objective physical activity monitoring. However traditional accelerometer units undergo proprietary pre-processing, resulting in the ‘black-box’ phenomenon, where researchers are unaware of the processes and filters used on their data. Raw accelerometers where all frequencies related to human movement are included in the signal, would facilitate novel analyses, such as frequency domain analysis and pattern recognition. The aim of this study was to quantify the mean, standard deviation and variance of the SlamTracker raw accelerometer at a range of speeds. Four tri-axial accelerometers underwent a one minute static condition test nine movement condition tests. Accelerometers were assessed for mean, standard deviation, sample variance and coefficient of variation throughout in all axes for all experimental conditions. The sample variance was <0.001g across all speeds and axes during the movement condition tests. In conclusion, the SlamTracker is shown to be an accurate and reliable device for measuring the raw accelerations of movement.
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Walter, Patrick L. "Review: Fifty Years Plus of Accelerometer History for Shock and Vibration (1940–1996)". Shock and Vibration 6, nr 4 (1999): 197–207. http://dx.doi.org/10.1155/1999/281718.
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This article summarizes the history of accelerometer development and the subsequent evolution of the commercial accelerometer industry. The focus is primarily on piezoelectric and piezoresistive accelerometers, although early resistance-bridge-type accelerometers are also described. The pioneer accelerometer manufacturing companies are identified and a chronology of technology development through today is presented.
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Sui, Li, Jing Hua Zhang, Jian Feng Liu i Geng Chen Shi. "Design, Analysis and Test for Micro-Mechanical Piezoresistive Accelerometer". Advanced Materials Research 340 (wrzesień 2011): 46–51. http://dx.doi.org/10.4028/www.scientific.net/amr.340.46.
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First of all, this paper analyzes the piezoresistive accelerometers’ research achievements at home and abroad. Then, design, manufacturing and testing method of the accelerometer array is presented. According to the detection requirements of fuze’s environmental forces, this paper provides an array accelerometers structure. In this way, each independent chip has 2*2 accelerometers, and every two accelerometers have the same structure sizes. So, the accelerometer array has two different measurement ranges. In order to reduce the influence of cross sensitivity, the accelerometer uses criss-cross beams. Every single accelerometer comprises sensing unit, signal processing circuit and self-test unit. According to the characteristics of processing plant, an entire series of independent processes for micro-mechanical piezoresistive fabrication is designed, and also given the layouts. The accelerometer is fabricated and its sensitivity and self-test performances are tested in this paper, finally this paper gives the reasons which cause test errors.
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Bolton, Samantha, Nick Cave, Naomi Cogger i G. R. Colborne. "Use of a Collar-Mounted Triaxial Accelerometer to Predict Speed and Gait in Dogs". Animals 11, nr 5 (27.04.2021): 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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Lazar, Drew, Munni Begum, Md Monzur Murshed, Benjamin Nelson, Joshua M. Bock, Mary Imboden, Leonard Kaminsky i Alexander Montoye. "Statistical Learning Methods to Predict Activity Intensity from Body-Worn Accelerometers". Journal of Biomedical Analytics 3, nr 1 (21.08.2020): 27–50. http://dx.doi.org/10.30577/jba.v3i1.57.
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Physical activity, especially when performed at moderate or vigorous intensity, has short- and long-term health benefits, but measurement of free-living physical activity is challenging. Accelerometers are popular tools to assess physical activity, although accuracy of conventional accelerometer analysis methods is suboptimal. This study developed and tested statistical learning models for assessing activity intensity from body-worn accelerometers. Twenty-eight adults performed 10-21 activities of daily living in two visits while wearing four accelerometers (right hip, right ankle, both wrists). Accelerometer placement is of crucial practical concern and this paper addresses this issue. Boosting, bagging, random forest and decision tree models were created for each accelerometer and for two-, three-, and four-accelerometer combinations to predict activity intensity. Research staff observations of activity intensity served as the criterion. Point estimates of error for the ankle accelerometer were 2.2-4.7 percentage points lower than other single-accelerometer placements, and the left wrist-ankle combination had errors 0.8-5.8 percentage points lower than other two-accelerometer combinations. Decision trees had poorer accuracy than the other models. Using an accelerometer worn on the lower limb, by itself or in combination with an upper-limb accelerometer, appears to offer optimal accuracy for activity intensity measurement.
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Dorofeev, N. V., Oleg R. Kuzichkin i A. V. Tsaplev. "Accelerometric Method of Measuring the Angle of Rotation of the Kinematic Mechanisms of Nodes". Applied Mechanics and Materials 770 (czerwiec 2015): 592–97. http://dx.doi.org/10.4028/www.scientific.net/amm.770.592.
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This article discusses the use of accelerometers to measure the angle of rotation of the kinematic pairs. The main problems of accelerometer methods and justified phasemetric method of forming the differential signal transducer. The application phase metric method accelerometeric measuring the angle of rotation of the kinematic pair eliminates the multiplicative error at the preliminary stage of the measurement.
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Staunton, Craig A., Mikael Swarén, Thomas Stöggl, Dennis-Peter Born i 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, nr 3 (1.03.2022): 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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Evenson, Kelly R., Elissa Scherer, Kennedy M. Peter, Carmen C. Cuthbertson i Stephanie Eckman. "Historical development of accelerometry measures and methods for physical activity and sedentary behavior research worldwide: A scoping review of observational studies of adults". PLOS ONE 17, nr 11 (21.11.2022): e0276890. http://dx.doi.org/10.1371/journal.pone.0276890.
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This scoping review identified observational studies of adults that utilized accelerometry to assess physical activity and sedentary behavior. Key elements on accelerometry data collection were abstracted to describe current practices and completeness of reporting. We searched three databases (PubMed, Web of Science, and SPORTDiscus) on June 1, 2021 for articles published up to that date. We included studies of non-institutionalized adults with an analytic sample size of at least 500. The search returned 5686 unique records. After reviewing 1027 full-text publications, we identified and abstracted accelerometry characteristics on 155 unique observational studies (154 cross-sectional/cohort studies and 1 case control study). The countries with the highest number of studies included the United States, the United Kingdom, and Japan. Fewer studies were identified from the continent of Africa. Five of these studies were distributed donor studies, where participants connected their devices to an application and voluntarily shared data with researchers. Data collection occurred between 1999 to 2019. Most studies used one accelerometer (94.2%), but 8 studies (5.2%) used 2 accelerometers and 1 study (0.6%) used 4 accelerometers. Accelerometers were more commonly worn on the hip (48.4%) as compared to the wrist (22.3%), thigh (5.4%), other locations (14.9%), or not reported (9.0%). Overall, 12.7% of the accelerometers collected raw accelerations and 44.6% were worn for 24 hours/day throughout the collection period. The review identified 155 observational studies of adults that collected accelerometry, utilizing a wide range of accelerometer data processing methods. Researchers inconsistently reported key aspects of the process from collection to analysis, which needs addressing to support accurate comparisons across studies.
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Oliver, Melody, Hannah Badland, Suzanne Mavoa, Mitch J. Duncan i Scott Duncan. "Combining GPS, GIS, and Accelerometry: Methodological Issues in the Assessment of Location and Intensity of Travel Behaviors". Journal of Physical Activity and Health 7, nr 1 (styczeń 2010): 102–8. http://dx.doi.org/10.1123/jpah.7.1.102.
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Background:Global positioning systems (GPS), geographic information systems (GIS), and accelerometers are powerful tools to explain activity within a built environment, yet little integration of these tools has taken place. This study aimed to assess the feasibility of combining GPS, GIS, and accelerometry to understand transport-related physical activity (TPA) in adults.Methods:Forty adults wore an accelerometer and portable GPS unit over 7 consecutive days and completed a demographics questionnaire and 7-day travel log. Accelerometer and GPS data were extracted for commutes to/from workplace and integrated into a GIS database. GIS maps were generated to visually explore physical activity intensity, GPS speeds and routes traveled.Results:GPS, accelerometer, and survey data were collected for 37 participants. Loss of GPS data was substantial due to a range of methodological issues, such as low battery life, signal drop out, and participant noncompliance. Nonetheless, greater travel distances and significantly higher speeds were observed for motorized trips when compared with TPA.Conclusions:Pragmatic issues of using GPS monitoring to understand TPA behaviors and methodological recommendations for future research were identified. Although methodologically challenging, the combination of GPS monitoring, accelerometry and GIS technologies holds promise for understanding TPA within the built environment.
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Sjöros, Tanja, Henri Vähä-Ypyä, Saara Laine, Taru Garthwaite, Eliisa Löyttyniemi, Harri Sievänen, Kari K. Kalliokoski, Juhani Knuuti, Tommi Vasankari i 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, nr 9 (6.05.2021): 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 i 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, nr 1 (23.07.2020): 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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Courtney Musson i Mark Kramer. "Accelerometery vs. video-derived stroke parameters in high-level swimmers". South African Journal of Sports Medicine 33, nr 1 (21.04.2021): 1–6. http://dx.doi.org/10.17159/2078-516x/2021/v33i1a9483.
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Background: Swimming is a multifaceted sport with nuanced performance parameters that tend to vary according to the swimmer’s stroke style. The extraction and analyses of swim parameters, such as lap time (LT), stroke length (SL), stroke rate (SR) and velocity are time-consuming. This may be eased and to some extent automated by the use of cost-effective tri- axial accelerometers.
Objectives: To determine the validity of tri-axial accelerometers across all four stroke styles, and to investigate kinematic differences in stroke styles using accelerometer- based data.
Methods: Twelve elite swimmers were recruited for the study. The group consisted of five male (age: 22.2 ± 2.6 years; height: 1.84 ± 0.08 m; weight: 76.2 ± 3.6 kg) and seven female (age: 20.7 ± 2.1 years; height: 1.68 ± 0.08 cm; weight: 62.0 ± 6.3 kg) swimmers.
Results: There was a small but significant bias for accelerometery data compared to video data across most parameters and stroke styles except for stroke length and stroke count (p > 0.05). However, accelerometery-derived SR, SL and velocity can be considered practically useful based on the training requirements of coaches. Parameters derived from video analysis compared to accelerometery were highly correlated (r > 0.91) and therefore consistent regardless of the method of analysis.
Conclusion: Although slight differences were present between the video and accelerometer data, these differences were not practically meaningful.
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Wundersitz, Daniel W. T., Paul B. Gastin, Samuel J. Robertson i Kevin J. Netto. "Validity of a Trunk-Mounted Accelerometer to Measure Physical Collisions in Contact Sports". International Journal of Sports Physiology and Performance 10, nr 6 (wrzesień 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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Song, Sangho, Hyun Chan Kim, Jung Woong Kim, Debora Kim i Jaehwan Kim. "Performance improvement of miniaturized ZnO nanowire accelerometer fabricated by refresh hydrothermal synthesis". Royal Society Open Science 4, nr 9 (wrzesień 2017): 170557. http://dx.doi.org/10.1098/rsos.170557.
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Miniaturized accelerometers are necessary for evaluating the performance of small devices, such as haptics, robotics and simulators. In this study, we fabricated miniaturized accelerometers using well-aligned ZnO nanowires. The layer of ZnO nanowires is used for active piezoelectric layer of the accelerometer, and copper was chosen as a head mass. Seedless and refresh hydrothermal synthesis methods were conducted to grow ZnO nanowires on the copper substrate and the effect of ZnO nanowire length on the accelerometer performance was investigated. The refresh hydrothermal synthesis exhibits longer ZnO nanowires, 12 µm, than the seedless hydrothermal synthesis, 6 µm. Performance of the fabricated accelerometers was verified by comparing with a commercial accelerometer. The sensitivity of the fabricated accelerometer by the refresh hydrothermal synthesis is shown to be 37.7 pA g −1 , which is about 30 times larger than the previous result.
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Takeshita, Adam, Jonah Madrid, Ezekiel Granillo i Abdessattar Abdelkefi. "Insights on the Impacts of Accelerometer Location on the Dynamics and Characteristics of Complex Structures". Sensors 23, nr 24 (14.12.2023): 9830. http://dx.doi.org/10.3390/s23249830.
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There exists a high level of difficulty in understanding the physical responses of complex dynamical systems. To this end, researchers have previously used different measurement techniques, such as displacement sensors or accelerometers, in the laboratory to capture a system’s dynamics. A well-known structure in the literature is the Box Assembly with Removable Component (BARC) whose purpose is to gain a deep understanding of testing complex systems. Further breaking down the structure, the Removable Component (RC) portion is often used as a relatively simplified version which retains significant complexity from the original system. However, the placement of accelerometers on the RC have varied greatly throughout the literature which presents a challenge in comparing results and may not accurately represent the system’s dynamics. Finite Element Analysis (FEA) is performed for three common accelerometer locations to determine how their placement affects the frequencies and mode shapes for the RC and results are compared against those without accelerometers. Free vibration experiments are carried out to understand the variation of frequencies and damping for each accelerometer location to obtain the overall response for the first mode of vibration. Next, random vibration experiments are run to gain insight on the interaction between linear and nonlinear responses based on excitation level, while showing the influence of an accelerometer’s location on system dynamics. The results demonstrate that the location of the accelerometer is highly influential on the linear and nonlinear characteristics of the system. It is proved that for the first mode of vibration, nonlinear softening and nonlinear damping behaviors may take place due to the interaction between the location of accelerometers, direction of excitation, and response axis analyzed.
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Qian, Leping, i Decai Li. "Use of Magnetic Fluid in Accelerometers". Journal of Sensors 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/375623.
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Magnetic fluid accelerometer is designed based on the special physical properties of magnetic fluid. Compared with the conventional acceleration sensors, magnetic fluid accelerometer has stronger shock resistance capability, higher sensitivity, lower energy consumption, and better performance in low frequency response. It satisfies the growing requirements of acceleration sensors. In this paper, the dynamic model and the theory of magnetic fluid accelerometers were presented. The structure characteristics of typical magnetic fluid accelerometers were investigated, and the development trend of magnetic fluid accelerometers in the future was also predicted. Besides, a novel accelerometer with linearity better than 1.5% and sensitivity better than 75 mV/g was proposed.
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Cui, Rubiao, Jingzehua Xu, Botao Huang, Huakun Xu, Miao Peng, Jingwen Yang, Jintao Zhang i in. "A Temperature Compensation Approach for Micro-Electro-Mechanical Systems Accelerometer Based on Gated Recurrent Unit–Attention and Robust Local Mean Decomposition–Sample Entropy–Time-Frequency Peak Filtering". Micromachines 15, nr 4 (30.03.2024): 483. http://dx.doi.org/10.3390/mi15040483.
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MEMS accelerometers are significantly impacted by temperature and noise, leading to a considerable compromise in their accuracy. In response to this challenge, we propose a parallel denoising and temperature compensation fusion algorithm for MEMS accelerometers based on RLMD-SE-TFPF and GRU-attention. Firstly, we utilize robust local mean decomposition (RLMD) to decompose the output signal of the accelerometer into a series of product function (PF) signals and a residual signal. Secondly, we employ sample entropy (SE) to classify the decomposed signals, categorizing them into noise segments, mixed segments, and temperature drift segments. Next, we utilize the time-frequency peak filtering (TFPF) algorithm with varying window lengths to separately denoise the noise and mixed signal segments, enabling subsequent signal reconstruction and training. Considering the strong inertia of the temperature signal, we innovatively introduce the accelerometer’s output time series as the model input when training the temperature compensation model. We incorporate gated recurrent unit (GRU) and attention modules, proposing a novel GRU-MLP-attention model (GMAN) architecture. Simulation experiments demonstrate the effectiveness of our proposed fusion algorithm. After processing the accelerometer output signal through the RLMD-SE-TFPF denoising algorithm and the GMAN temperature drift compensation model, the acceleration random walk is reduced by 96.11%, with values of 0.23032 g/h/Hz for the original accelerometer output signal and 0.00895695 g/h/Hz for the processed signal.
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Montoye, Alexander H. K., Rebecca W. Moore, Heather R. Bowles, Robert Korycinski i Karin A. Pfeiffer. "Reporting accelerometer methods in physical activity intervention studies: a systematic review and recommendations for authors". British Journal of Sports Medicine 52, nr 23 (18.08.2016): 1507–16. http://dx.doi.org/10.1136/bjsports-2015-095947.
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ObjectiveThis systematic review assessed the completeness of accelerometer reporting in physical activity (PA) intervention studies and assessed factors related to accelerometer reporting.DesignThe PubMed database was used to identify manuscripts for inclusion. Included studies were PA interventions that used accelerometers, were written in English and were conducted between 1 January 1998 and 31 July 2014. 195 manuscripts from PA interventions that used accelerometers to measure PA were included. Manuscript completeness was scored using 12 questions focused on 3 accelerometer reporting areas: accelerometer information, data processing and interpretation and protocol non-compliance. Variables, including publication year, journal focus and impact factor, and population studied were evaluated to assess trends in reporting completeness.ResultsThe number of manuscripts using accelerometers to assess PA in interventions increased from 1 in 2002 to 29 in the first 7 months of 2014. Accelerometer reporting completeness correlated weakly with publication year (r=0.24, p<0.001). Correlations were greater when we assessed improvements over time in reporting data processing in manuscripts published in PA-focused journals (r=0.43, p=0.002) compared to manuscripts published in non-PA-focused journals (r=0.19, p=0.021). Only 7 of 195 (4%) manuscripts reported all components of accelerometer use, and only 132 (68%) reported more than half of the components.ConclusionsAccelerometer reporting of PA in intervention studies has been poor and improved only minimally over time. We provide recommendations to improve accelerometer reporting and include a template to standardise reports.
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Suorsa, Kristin, Anna Pulakka, Tuija Leskinen, Jaana Pentti, Andreas Holtermann, Olli J. Heinonen, Juha Sunikka, Jussi Vahtera i Sari Stenholm. "Comparison of Sedentary Time Between Thigh-Worn and Wrist-Worn Accelerometers". Journal for the Measurement of Physical Behaviour 3, nr 3 (1.09.2020): 234–43. http://dx.doi.org/10.1123/jmpb.2019-0052.
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Background: The accuracy of wrist-worn accelerometers in identifying sedentary time has been scarcely studied in free-living conditions. The aim of this study was to compare daily sedentary time estimates between a thigh-worn accelerometer, which measured sitting and lying postures, and a wrist-worn accelerometer, which measured low levels of movement. Methods: The study population consisted of 259 participants (Mage = 62.8 years, SD = 0.9) from the Finnish Retirement and Aging Study (FIREA). Participants wore an Axivity AX3 accelerometer on their mid-thigh and an Actigraph wActiSleep-BT accelerometer on their non-dominant wrist simultaneously for a minimum of 4 days in free-living conditions. Two definitions to estimate daily sedentary time were used for data from the wrist-worn accelerometer: 1) the count cutpoint, ≤1853 counts per minute; and 2) the Euclidean Norm Minus One (ENMO) cutpoint, <30 mg. Results: Compared to the thigh-worn accelerometer, daily sedentary time estimate was 63 min (95% confidence interval [CI] = −53 to −73) lower by the count cutpoint and 50 min (95% CI = 34 to 67) lower by the ENMO cutpoint. The limits of agreement in daily sedentary time estimates between the thigh- and cutpoint methods for wrist-worn accelerometers were wide (the count cutpoint: −117 to 243, the ENMO cutpoint: −212 to 313 min). Conclusions: Currently established cutpoint-based methods to estimate sedentary time from wrist-worn accelerometers result in underestimation of daily sedentary time compared to posture-based estimates of thigh-worn accelerometers. Thus, sedentary time estimates obtained from wrist-worn accelerometers using currently available cutpoint-based methods should be interpreted with caution and future work is needed to improve their accuracy.
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Nedergaard, Niels J., Mark A. Robinson, Elena Eusterwiemann, Barry Drust, Paulo J. Lisboa i Jos Vanrenterghem. "The Relationship Between Whole-Body External Loading and Body-Worn Accelerometry During Team-Sport Movements". International Journal of Sports Physiology and Performance 12, nr 1 (styczeń 2017): 18–26. http://dx.doi.org/10.1123/ijspp.2015-0712.
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Purpose:To investigate the relationship between whole-body accelerations and body-worn accelerometry during team-sport movements.Methods:Twenty male team-sport players performed forward running and anticipated 45° and 90° side-cuts at approach speeds of 2, 3, 4, and 5 m/s. Whole-body center-of-mass (CoM) accelerations were determined from ground-reaction forces collected from 1 foot–ground contact, and segmental accelerations were measured from a commercial GPS accelerometer unit on the upper trunk. Three higher-specification accelerometers were also positioned on the GPS unit, the dorsal aspect of the pelvis, and the shaft of the tibia. Associations between mechanical load variables (peak acceleration, loading rate, and impulse) calculated from both CoM accelerations and segmental accelerations were explored using regression analysis. In addition, 1-dimensional statistical parametric mapping (SPM) was used to explore the relationships between peak segmental accelerations and CoM-acceleration profiles during the whole foot–ground contact.Results:A weak relationship was observed for the investigated mechanical load variables regardless of accelerometer location and task (R2 values across accelerometer locations and tasks: peak acceleration .08–.55, loading rate .27–.59, and impulse .02–.59). Segmental accelerations generally overestimated whole-body mechanical load. SPM analysis showed that peak segmental accelerations were mostly related to CoM accelerations during the first 40–50% of contact phase.Conclusions:While body-worn accelerometry correlates to whole-body loading in team-sport movements and can reveal useful estimates concerning loading, these correlations are not strong. Body-worn accelerometry should therefore be used with caution to monitor whole-body mechanical loading in the field.
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He, Wen Tao, De Yong Chen, Guang Bei Li i Jun Bo Wang. "Low Frequency Electrochemical Accelerometer with Low Noise Based on MEMS". Key Engineering Materials 503 (luty 2012): 75–80. http://dx.doi.org/10.4028/www.scientific.net/kem.503.75.
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Petroleum prospecting and early warning of some geological disaster increasingly depend on the accelerometers which can detect vibrate of frequency below 1Hz, but it’s embarrassing that accelerometers based on Si or SiO2 structure make an awful performance in this frequency range. Electrochemical accelerometers were developed in 1990s. With fluidics to be inertial mass, electrochemical accelerometer not only show an excellent property in low frequency, but also has a wide dynamic range. However, traditional fabrication process of electrochemical accelerometer is rather complex and can’t eliminate the noise due to the inconsistency and asymmetry of electrodes. To solve these problems, a scheme based on MEMS is proposed here, including design, fabrication and package. Properties of electrochemical accelerometer (EAM) are tested in two conditions at last.
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Yu, Run Xiang, Geng Chen Shi i Dan Hu. "Study on a Novel Piezoelectric Accelerometer with Switch Characteristic". Applied Mechanics and Materials 329 (czerwiec 2013): 329–33. http://dx.doi.org/10.4028/www.scientific.net/amm.329.329.
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A novel piezoelectric accelerometer with switch characteristic was introduced. The accelerometer is composed of top head, cross elastic beam, base core, insulation cylinder, mass block, piezoelectric elements, and the base etc. The accelerometers structure and operating principle were presented and its mathematic model was established. Test results show that the accelerometer can filter out high frequency vibration signal, which the out signal is smooth compared with the conventional piezoelectric accelerometer, furthermore with good linearity. It can be used in the smart fuze to take the place of conventional piezoelectric accelerometer in order to recognize the target accurately.
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Vanderloo, Leigh M., Natascja A. Di Cristofaro, Nicole A. Proudfoot, Patricia Tucker i Brian W. Timmons. "Comparing the Actical and ActiGraph Approach to Measuring Young Children’s Physical Activity Levels and Sedentary Time". Pediatric Exercise Science 28, nr 1 (luty 2016): 133–42. http://dx.doi.org/10.1123/pes.2014-0218.
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Young children’s activity and sedentary time were simultaneously measured via the Actical method (i.e., Actical accelerometer and specific cut-points) and the ActiGraph method (i.e., ActiGraph accelerometer and specific cut-points) at both 15-s and 60-s epochs to explore possible differences between these 2 measurement approaches. For 7 consecutive days, participants (n = 23) wore both the Actical and ActiGraph side-by-side on an elastic neoprene belt. Device-specific cut-points were applied. Paired sample t tests were conducted to determine the differences in participants’ daily average activity levels and sedentary time (min/h) measured by the 2 devices at 15-s and 60-s time sampling intervals. Bland-Altman plots were used to examine agreement between Actical and ActiGraph accelerometers. Regardless of epoch length, Actical accelerometers reported significantly higher rates of sedentary time (15 s: 42.7 min/h vs 33.5 min/h; 60 s: 39.4 min/h vs 27.1 min/h). ActiGraph accelerometers captured significantly higher rates of moderate-to-vigorous physical activity (15 s: 9.2 min/h vs 2.6 min/h; 60 s: 8.0 min/h vs 1.27 min/h) and total physical activity (15 s: 31.7 min/h vs 22.3 min/h; 60 s: = 39.4 min/h vs 25.2 min/h) in comparison with Actical accelerometers. These results highlight the present accelerometry-related issues with interpretation of datasets derived from different monitors.
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Tomczyk, Krzysztof, i Małgorzata Kowalczyk. "Accuracy Assessment of Charge-Mode Accelerometers Using Multivariate Regression of the Upper Bound of the Dynamic Error". Energies 16, nr 23 (26.11.2023): 7784. http://dx.doi.org/10.3390/en16237784.
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This paper presents the mathematical basis and related procedures for the regression of the upper bound of the dynamic error produced by charge-mode accelerometers. The integral-square error obtained in response to simulation signals with one constraint appearing at the input of the accelerometer is considered. Physical models of accelerometers are presented with related equations and mathematical formulae that make it possible to obtain the error and the corresponding constrained signal. Examples of the regression for predefined values of the accelerometer parameters are also discussed. The solutions presented in this paper may contribute to increasing the accuracy of the charge-mode accelerometers commonly used in energy systems. Development of the functions approximating the integral-square error for the given ranges of accelerometer parameters constitutes the original contribution of this paper.
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Grecheneva, A. V., N. V. Dorofeev, O. R. Kuzichkin, R. V. Romanov i D. I. Surzhik. "The method and mathematical support for calibration of a goniometric system based on the accelerometers". MATEC Web of Conferences 272 (2019): 01043. http://dx.doi.org/10.1051/matecconf/201927201043.
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The article is devoted to the development of a calibration method for the goniometric system, which includes accelerometers. The complexity of the technological process of mechanical calibration of accelerometers was noted. It is proposed to apply software-algorithmic correction of measurement results. A mathematical model of signals of an accelerometer converter is described, which takes into account the influence of measurement errors. It is noted that in order to find the parameters of the mathematical model of an accelerometer signal, it is necessary to perform calibration. A mathematical model and the principle of calibration of the misalignment angle of the axes of the accelerometer are proposed and described. To evaluate the effectiveness of the proposed calibration method, experimental studies and data processing of the accelerometer were carried. As a result of experimental studies, an estimation of the degree of error compensation of the ADIS 16534 accelerometer measurements was performed with the application of the modified multi-position calibration method and the calibration method proposed by the authors of this article.
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FENATO JUNIOR, ALEXANDRE, LARISSA MARTINS GARCIA, GLEICI DA SILVA CASTRO PERDONÁ i DANIEL AUGUSTO MARANHO. "MEASUREMENT OF PELVIC RETROVERSION DURING HIP FLEXION: EVALUATION WITH ACCELEROMETERS". Acta Ortopédica Brasileira 28, nr 2 (kwiecień 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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Wang, Xing Hua, Zhi Hua Chen, Ding Bang Xiao i Xue Zhong Wu. "Design and Analysis of a Monolithic 3-Axis Micro-Accelerometer". Key Engineering Materials 503 (luty 2012): 122–27. http://dx.doi.org/10.4028/www.scientific.net/kem.503.122.
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Due to many inherently problems of accelerometers on market, such as complex fabrication process and low precision, a monolithic three-axis accelerometer is proposed and fabricated. The 3-axis accelerometer consists of four individual seismic mass, each has a wafer-thick of 240μm and is fabricated by anisotropic wet etching technology. In this paper, the design, fabrication, and characterization of the 3-axis accelerometer are presented. The performance is characterized and demonstrated.
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Esliger, Dale W., Jennifer L. Copeland, Joel D. Barnes i Mark S. Tremblay. "Standardizing and Optimizing the Use of Accelerometer Data for Free-Living Physical Activity Monitoring". Journal of Physical Activity and Health 2, nr 3 (lipiec 2005): 366–83. http://dx.doi.org/10.1123/jpah.2.3.366.
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The unequivocal link between physical activity and health has prompted researchers and public health officials to search for valid, reliable, and logistically feasible tools to measure and quantify free-living physical activity. Accelerometers hold promise in this regard. Recent technological advances have led to decreases in both the size and cost of accelerometers while increasing functionality (e.g., greater memory, waterproofing). A lack of common data reduction and standardized reporting procedures dramatically limit their potential, however. The purpose of this article is to expand on the utility of accelerometers for measuring free-living physical activity. A detailed example profile of physical activity is presented to highlight the potential richness of accelerometer data. Specific recommendations for optimizing and standardizing the use of accelerometer data are provided with support from specific examples. This descriptive article is intended to advance and ignite scholarly dialogue and debate regarding accelerometer data capture, reduction, analysis, and reporting.
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Fraser, Sarah J., Justin J. Chapman, Wendy J. Brown, Harvey A. Whiteford i Nicola W. Burton. "The Feasibility of Using Questionnaires and Accelerometers to Measure Physical Activity and Sedentary Behavior Among Inpatient Adults With Mental Illness". Journal of Physical Activity and Health 13, nr 5 (maj 2016): 551–57. http://dx.doi.org/10.1123/jpah.2015-0223.
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Background:The aim of this study was to assess the feasibility of using questionnaires and accelerometers to measure physical activity and sedentary behavior among inpatient adults with mental illness.Methods:Participants completed a physical activity and sitting time questionnaire and wore an accelerometer for 7 consecutive days. Feasibility was assessed in terms of participant engagement, self-reported ease/difficulty of completing study components, extreme self-report data values and adherence to accelerometer wear time criteria. Ease/difficulty ratings were examined by level of distress.Results:177 inpatients were invited to the study, 101 completed the questionnaires and 36 provided valid accelerometry data. Participants found it more difficult to complete sitting time and physical activity questionnaires than to wear the accelerometer during waking hours (z = 3.787, P < .001; z = 2.824, P = .005 respectively). No significant differences were found in ease/difficulty ratings by level of distress for any of the study components. Extreme values for self-reported sitting time were identified in 27% of participants.Conclusion:Inpatient adults with mental illness can engage with self-report and objective methods of measuring physical activity and sedentary behavior. They were initially less willing to participate in objective measurement, which may however be more feasible than self-report measures.
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Dubé, Dany, i Philippe Cardou. "THE CALIBRATION OF AN ARRAY OF ACCELEROMETERS". Transactions of the Canadian Society for Mechanical Engineering 35, nr 2 (czerwiec 2011): 251–67. http://dx.doi.org/10.1139/tcsme-2011-0015.
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An accelerometer-array calibration method is proposed in this paper by which we estimate not only the accelerometer offsets and scale factors, but also their sensitive directions and positions on a rigid body. These latter parameters are computed from the classical equations that describe the kinematics of rigid bodies, and by measuring the accelerometer-array displacements using a magnetic sensor. Unlike calibration schemes that were reported before, the one proposed here guarantees that the estimated accelerometer-array parameters are globally optimum in the least-squares sense. The calibration procedure is tested on OCTA, a rigid body equipped with six biaxial accelerometers. It is demonstrated that the new method significantly reduces the errors when computing the angular velocity of a rigid body from the accelerometer measurements.
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Gao, Zan, Wenxi Liu, Daniel J. McDonough, Nan Zeng i Jung Eun Lee. "The Dilemma of Analyzing Physical Activity and Sedentary Behavior with Wrist Accelerometer Data: Challenges and Opportunities". Journal of Clinical Medicine 10, nr 24 (18.12.2021): 5951. http://dx.doi.org/10.3390/jcm10245951.
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Physical behaviors (e.g., physical activity and sedentary behavior) have been the focus among many researchers in the biomedical and behavioral science fields. The recent shift from hip- to wrist-worn accelerometers in these fields has signaled the need to develop novel approaches to process raw acceleration data of physical activity and sedentary behavior. However, there is currently no consensus regarding the best practices for analyzing wrist-worn accelerometer data to accurately predict individuals’ energy expenditure and the times spent in different intensities of free-living physical activity and sedentary behavior. To this end, accurately analyzing and interpreting wrist-worn accelerometer data has become a major challenge facing many clinicians and researchers. In response, this paper attempts to review different methodologies for analyzing wrist-worn accelerometer data and offer cutting edge, yet appropriate analysis plans for wrist-worn accelerometer data in the assessment of physical behavior. In this paper, we first discuss the fundamentals of wrist-worn accelerometer data, followed by various methods of processing these data (e.g., cut points, steps per minute, machine learning), and then we discuss the opportunities, challenges, and directions for future studies in this area of inquiry. This is the most comprehensive review paper to date regarding the analysis and interpretation of free-living physical activity data derived from wrist-worn accelerometers, aiming to help establish a blueprint for processing wrist-derived accelerometer data.
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Droogendijk, H., M. J. de Boer, R. G. P. Sanders i G. J. M. Krijnen. "A biomimetic accelerometer inspired by the cricket's clavate hair". Journal of The Royal Society Interface 11, nr 97 (6.08.2014): 20140438. http://dx.doi.org/10.1098/rsif.2014.0438.
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Crickets use so-called clavate hairs to sense (gravitational) acceleration to obtain information on their orientation. Inspired by this clavate hair system, a one-axis biomimetic accelerometer has been developed and fabricated using surface micromachining and SU-8 lithography. An analytical model is presented for the design of the accelerometer, and guidelines are derived to reduce responsivity due to flow-induced contributions to the accelerometer's output. Measurements show that this microelectromechanical systems (MEMS) hair-based accelerometer has a resonance frequency of 320 Hz, a detection threshold of 0.10 ms −2 and a dynamic range of more than 35 dB. The accelerometer exhibits a clear directional response to external accelerations and a low responsivity to airflow. Further, the accelerometer's physical limits with respect to noise levels are addressed and the possibility for short-term adaptation of the sensor to the environment is discussed.
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Kwon, Soyang, Patricia Zavos, Katherine Nickele, Albert Sugianto i Mark V. Albert. "Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities". International Journal of Environmental Research and Public Health 16, nr 14 (21.07.2019): 2598. http://dx.doi.org/10.3390/ijerph16142598.
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Although accelerometry data are widely utilized to estimate physical activity and sedentary behavior among children age 3 years or older, for toddlers age 1 and 2 year(s), accelerometry data recorded during such behaviors have been far less examined. In particular, toddler’s unique behaviors, such as riding in a stroller or being carried by an adult, have not yet been examined. The objective of this study was to describe accelerometry signal outputs recorded during participation in nine types of behaviors (i.e., running, walking, climbing up/down, crawling, riding a ride-on toy, standing, sitting, riding in a stroller/wagon, and being carried by an adult) among toddlers. Twenty-four toddlers aged 13 to 35 months (50% girls) performed various prescribed behaviors during free play in a commercial indoor playroom while wearing ActiGraph wGT3X-BT accelerometers on a hip and a wrist. Participants’ performances were video-recorded. Based on the video data, accelerometer data were annotated with behavior labels to examine accelerometry signal outputs while performing the nine types of behaviors. Accelerometer data collected during 664 behavior assessments from the 21 participants were used for analysis. Hip vertical axis counts for walking were low (median = 49 counts/5 s). They were significantly lower than those recorded while a toddler was “carried” by an adult (median = 144 counts/5 s; p < 0.01). While standing, sitting, and riding in a stroller, very low hip vertical axis counts were registered (median ≤ 5 counts/5 s). Although wrist vertical axis and vector magnitude counts for “carried” were not higher than those for walking, they were higher than the cut-points for sedentary behaviors. Using various accelerometry signal features, machine learning techniques showed 89% accuracy to differentiate the “carried” behavior from ambulatory movements such as running, walking, crawling, and climbing. In conclusion, hip vertical axis counts alone may be unable to capture walking as physical activity and “carried” as sedentary behavior among toddlers. Machine learning techniques that utilize additional accelerometry signal features could help to recognize behavior types, especially to differentiate being “carried” from ambulatory movements.
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Hurter, Liezel, Anna M. Cooper-Ryan, Zoe R. Knowles, Lorna A. Porcellato, Stuart J. Fairclough i Lynne M. Boddy. "A Novel Mixed Methods Approach to Assess Children’s Sedentary Behaviors". Journal for the Measurement of Physical Behaviour 3, nr 1 (1.03.2020): 78–86. http://dx.doi.org/10.1123/jmpb.2019-0040.
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Purpose: Accurately measuring sedentary behavior (SB) in children is challenging by virtue of its complex nature. While self-report questionnaires are susceptible to recall errors, accelerometer data lacks contextual information. This study aimed to explore the efficacy of using accelerometry combined with the Digitising Children’s Data Collection (DCDC) for Health application (app), to capture SB comprehensively. Methods: 74 children (9–10 years old) wore ActiGraph GT9X accelerometers for 7 days. Each received a SAMSUNG Galaxy Tab4 (SM-T230) tablet, with the DCDC app installed and a specially designed sedentary behavior study downloaded. The app uses four data collection tools: 1) Questionnaire, 2) Take a photograph, 3) Draw a picture, and 4) Record my voice. Children self-reported their SB daily. Accelerometer data were analyzed using R-package GGIR. App data were downloaded and individual participant profiles created. SBs reported were grouped into categories and reported as frequencies. Results: Participants spent, on average, 629 min (i.e., 73% of their waking time) sedentary. App data revealed most of their out-of-school SB consisted of screen time (112 photos, 114 drawings, and screen time mentioned 135 times during voice recordings). Playing with toys, reading, arts and crafts, and homework were also reported across all four data capturing tools on the app. On an individual level, data from the app often explained irregular patterns in physical activity and SB observed in accelerometer data. Conclusion: This mixed methods approach to assessing SB adds context to accelerometer data, providing researchers with information needed for intervention design.
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Wainberg, Michael, Samuel E. Jones, Lindsay Melhuish Beaupre, Sean L. Hill, Daniel Felsky, Manuel A. Rivas, Andrew S. P. Lim, Hanna M. Ollila i Shreejoy J. Tripathy. "Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank". PLOS Medicine 18, nr 10 (12.10.2021): e1003782. http://dx.doi.org/10.1371/journal.pmed.1003782.
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Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.
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Arvidsson, Daniel, Mark Fitch, Mark L. Hudes, Catrine Tudor-Locke i Sharon E. Fleming. "Accelerometer Response to Physical Activity Intensity in Normal-Weight Versus Overweight African American Children". Journal of Physical Activity and Health 8, nr 5 (lipiec 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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Chen, Tianyu, Gongliu Yang, Qingzhong Cai, Zeyang Wen i Wenlong Zhang. "A Novel Calibration Method for Gyro-Accelerometer Asynchronous Time in Foot-Mounted Pedestrian Navigation System". Sensors 22, nr 1 (29.12.2021): 209. http://dx.doi.org/10.3390/s22010209.
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Pedestrian Navigation System (PNS) is one of the research focuses of indoor positioning in GNSS-denied environments based on the MEMS Inertial Measurement Unit (MIMU). However, in the foot-mounted pedestrian navigation system with MIMU or mobile phone as the main carrier, it is difficult to make the sampling time of gyros and accelerometers completely synchronous. The gyro-accelerometer asynchronous time affects the positioning of PNS. To solve this problem, a new error model of gyro-accelerometer asynchronous time is built. The effect of gyro-accelerometer asynchronous time on pedestrian navigation is analyzed. A filtering model is designed to calibrate the gyro-accelerometer asynchronous time, and a zero-velocity detection method based on the rate of attitude change is proposed. The indoor experiment shows that the gyro-accelerometer asynchronous time is estimated effectively, and the positioning accuracy of PNS is improved by the proposed method after compensating for the errors caused by gyro-accelerometer asynchronous time.
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Du, Cuicui, i Deren Kong. "Sensitivity calibration of a three-axis accelerometer under different temperature conditions using the hybrid GA–PSO–BPNN algorithm". Sensor Review 42, nr 1 (28.10.2021): 8–18. http://dx.doi.org/10.1108/sr-07-2021-0227.
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Purpose Three-axis accelerometers play a vital role in monitoring the vibrations in aircraft machinery, especially in variable flight temperature environments. The sensitivity of a three-axis accelerometer under different temperature conditions needs to be calibrated before the flight test. Hence, the authors investigated the efficiency and sensitivity calibration of three-axis accelerometers under different conditions. This paper aims to propose the novel calibration algorithm for the three-axis accelerometers or the similar accelerometers. Design/methodology/approach The authors propose a hybrid genetic algorithm–particle swarm optimisation–back-propagation neural network (GA–PSO–BPNN) algorithm. This method has high global search ability, fast convergence speed and strong non-linear fitting capability; it follows the rules of natural selection and survival of the fittest. The authors describe the experimental setup for the calibration of the three-axis accelerometer using a three-comprehensive electrodynamic vibration test box, which provides different temperatures. Furthermore, to evaluate the performance of the hybrid GA–PSO–BPNN algorithm for sensitivity calibration, the authors performed a detailed comparative experimental analysis of the BPNN, GA–BPNN, PSO–BPNN and GA–PSO–BPNN algorithms under different temperatures (−55, 0 , 25 and 70 °C). Findings It has been showed that the prediction error of three-axis accelerometer under the hybrid GA–PSO–BPNN algorithm is the least (approximately ±0.1), which proved that the proposed GA–PSO–BPNN algorithm performed well on the sensitivity calibration of the three-axis accelerometer under different temperatures conditions. Originality/value The designed GA–PSO–BPNN algorithm with high global search ability, fast convergence speed and strong non-linear fitting capability has been proposed to decrease the sensitivity calibration error of three-axis accelerometer, and the hybrid algorithm could reach the global optimal solution rapidly and accurately.
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Lawinger, Elizabeth, Tim L. Uhl, Mark Abel i Srinath Kamineni. "Assessment of Accelerometers for Measuring Upper-Extremity Physical Activity". Journal of Sport Rehabilitation 24, nr 3 (sierpień 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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Sanjuan, Jose, Alexander Sinyukov, Mohanad F. Warrayat i Felipe Guzman. "Gyro-Free Inertial Navigation Systems Based on Linear Opto-Mechanical Accelerometers". Sensors 23, nr 8 (19.04.2023): 4093. http://dx.doi.org/10.3390/s23084093.
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High-sensitivity uniaxial opto-mechanical accelerometers provide very accurate linear acceleration measurements. In addition, an array of at least six accelerometers allows the estimation of linear and angular accelerations and becomes a gyro-free inertial navigation system. In this paper, we analyze the performance of such systems considering opto-mechanical accelerometers with different sensitivities and bandwidths. In the six-accelerometer configuration adopted here, the angular acceleration is estimated using a linear combination of accelerometers’ read-outs. The linear acceleration is estimated similarly but requires a correcting term that includes angular velocities. Accelerometers’ colored noise from experimental data is used to derive, analytically and through simulations, the performance of the inertial sensor. Results for six accelerometers, separated by 0.5 m in a cube configuration show noise levels of 10−7 m s−2 and 10−5 m s−2 (in Allan deviation) for time scales of one second for the low-frequency (Hz) and high-frequency (kHz) opto-mechanical accelerometers, respectively. The Allan deviation for the angular velocity at one second is 10−5 rad s−1 and 5×10−4 rad s−1. Compared to other technologies such as MEMS-based inertial sensors and optical gyroscopes, the high-frequency opto-mechanical accelerometer exhibits better performance than tactical-grade MEMS for time scales shorter than 10 s. For angular velocity, it is only superior for time scales less than a few seconds. The linear acceleration of the low-frequency accelerometer outperforms the MEMS for time scales up to 300 s and for angular velocity only for a few seconds. Fiber optical gyroscopes are orders of magnitude better than the high- and low-frequency accelerometers in gyro-free configurations. However, when considering the theoretical thermal noise limit of the low-frequency opto-mechanical accelerometer, 5×10−11 m s−2, linear acceleration noise is orders of magnitude lower than MEMS navigation systems. Angular velocity precision is around 10−10 rad s−1 at one second and 5×10−7 rad s−1 at one hour, which is comparable to fiber optical gyroscopes. While experimental validation is yet not available, the results shown here indicate the potential of opto-mechanical accelerometers as gyro-free inertial navigation sensors, provided the fundamental noise limit of the accelerometer is reached, and technical limitations such as misalignments and initial conditions errors are well controlled.
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Lecci, Len, Kelly Dugan, Ken Zeiger, Julian Keith, Sasidharan Taravath, Wayland Tseh i Mark Williams. "Validation of an accelerometer-based gait assessment: Establishing test-retest reliability, convergent validity, and predictive validity for concussion symptom endorsement". Journal of Concussion 7 (styczeń 2023): 205970022311579. http://dx.doi.org/10.1177/20597002231157947.
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Background Gait accelerometer (sensor) technology has proven effective in predicting several medical outcomes, but less is known regarding its prediction of concussion symptoms relative to conventional measures of gait and balance. Objective To establish the reliability and validity of gait accelerometer data. We first examine test-retest reliability and the impact of footwear and walking surfaces on gait. We then examine the convergent validity between gait accelerometer data and the NIH 4-meter gait test. Finally, we compare gait accelerometer data to gait speed and balance measures for predicting concussion symptoms. Methods Study 1 used a crossover study design with 60 participants to evaluate retest reliability and examine the effects of footwear (shoes/no-shoes) and walking surface (tile floor/grass) on gait accelerometer data. Study 2 employed a cross-sectional design with 1008 participants to assess gait accelerometer correlations with NIH 4-meter gait and the prediction of Centers for Disease Control and Prevention (CDC) concussion symptoms relative to previously validated gait and balance measures. Results Retest reliability (4-day average retest interval) for the no shoes/tile surface condition ranged from .72-.91 (mean = .80). Significant effects of footwear and especially walking surface revealed by Analysis of Variances (ANOVAs) on gait accelerometer data for the power, stride, balance, and symmetry domains indicate the need to standardize these variables. Gait accelerometer data correlates significantly with NIH 4-meter gait scores. Regression analyses found that gait accelerometer data predicts CDC concussion symptom endorsement, outperforming the BESS and NIH 4-meter gait at least three-fold. Conclusions When standardized on footwear and walking surface, gait accelerometers achieve strong test-retest reliability, converge with established measures of gait speed, and are superior to established measures of gait speed and balance when predicting concussion symptoms. Gait accelerometers represent a rapid tool for collecting additional gait information to quantify the behavioral sequelae of concussion and potentially inform return-to-play decision-making.
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Trisno, Roth, Parvathy Nair, Daniel Martin, Maryam S. Baghini, Hoam Chung, Gita Pendharkar i Jayashri Kulkarni. "Using accelerometer as a diagnostic tool to detect drug-induced parkinsonism (DIP) secondary to first-generation anti-psychotic medications". Australasian Psychiatry 28, nr 3 (24.02.2020): 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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Schmitz, Dylan G., Darryl G. Thelen i Stephanie G. Cone. "A Kalman Filter Approach for Estimating Tendon Wave Speed from Skin-Mounted Accelerometers". Sensors 22, nr 6 (16.03.2022): 2283. http://dx.doi.org/10.3390/s22062283.
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Shear wave tensiometry is a noninvasive approach for assessing in vivo tendon forces based on the speed of a propagating shear wave. Wave speed is measured by impulsively exciting a shear wave in a tendon and then assessing the wave travel time between skin-mounted accelerometers. Signal distortion with wave travel can cause errors in the estimated wave travel time. In this study, we investigated the use of a Kalman filter to fuse spatial and temporal accelerometer measurements of wave propagation. Spatial measurements consist of estimated wave travel times between accelerometers. Temporal measurements are the change in wave arrival at a fixed accelerometer between successive impulsive taps. The Kalman filter substantially improved the accuracy of estimated wave speeds when applied to simulated tensiometer data. The variability of estimated wave speed was reduced by ~55% in the presence of random sensor noise. It was found that increasing the number of accelerometers from two to three further reduced wave speed errors by 45%. The use of redundant accelerometers (>2) also improved the robustness of wave speed measures in the presence of uncertainty in accelerometer location. We conclude that the use of a Kalman filter and redundant accelerometers can enhance the fidelity of using shear wave tensiometers to track tendon wave speed and loading during movement.
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Warmath, Clara R., Courtney C. Choy, Elizabeth A. Frame, Lauren B. Sherar, Rachel L. Duckham, Christina Soti-Ulberg, Take Naseri, Muagututia S. Reupena i Nicola L. Hawley. "Comparability of The Netherlands Physical Activity Questionnaire with Accelerometer-Measured Physical Activity in Samoan Children: A Retrospective Analysis of Ola Tuputupua’e Data". International Journal of Environmental Research and Public Health 18, nr 16 (10.08.2021): 8438. http://dx.doi.org/10.3390/ijerph18168438.
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Accurate measurement of physical activity is critical to understand its role in cardiometabolic health and obesity development in children and to monitor trends in behavior and evaluate interventions. An ongoing mixed-longitudinal study of child growth and development in Samoa is collecting physical activity data with both accelerometers and the Netherlands Physical Activity Questionnaire (NPAQ). The aims of our analyses were to (1) describe the response frequency and correlations of individual questions in the NPAQ, (2) develop modified NPAQ scores with selected questions and (3) examine the concordance of modified NPAQ scores with accelerometer outcomes among children aged 2–4 years. We developed two modified NPAQ scores with combinations of questions and assessed concordance of the modified scores with accelerometer data using estimated marginal means adjusted for monitor wear time. Although the evenly distributed tertiles of the modified 15-point NPAQ score showed promising trends of increasing minutes of accelerometer-assessed high-intensity physical activity with increasing tertile, the estimated marginal means were imprecise with high variance, demonstrating that NPAQ score could not accurately assess physical activity levels of preschool-aged children in Samoa. Considering that questionnaires are often considered more cost-effective tools for physical activity measurement than accelerometry, further research is necessary to develop a culturally and age-appropriate physical activity questionnaire in this population.
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Gurule, Sara C., Melissa Aguirre, Kylee Forrest, Victor V. Flores, John Wenzel, Colin Tobin, Derek Bailey i Jennifer A. Hernandez Gifford. "PSII-16 Potential of sensor technology to detect changes in behavior related to health status of ewes following exposure to mold-contaminated feed". Journal of Animal Science 99, Supplement_3 (8.10.2021): 313–14. http://dx.doi.org/10.1093/jas/skab235.576.
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Abstract Behavior can be a valuable indicator of an animal’s health and wellness state, emphasizing the importance of monitoring changes in behavior. Sensor technologies can identify changes in animal activity, providing the potential to detect abnormal behavior associated with health status and animal welfare. The aim of this study was to investigate sheep behavior before and after illness caused by mold-contaminated feed using tri-axial accelerometers. Twenty-five ewes were fitted with HerdDogg biometric accelerometer ear tags. Thirteen ewes also had Axivity AX3 accelerometers attached on the opposite side ear tag. Tri-axial accelerometers were attached to mature ewes for the purpose of parturition evaluation, when an unexpected ration change occurred. The entire sheep flock was exposed to mold-contaminated feed, symptoms were immediately observed, and symptomatic ewes were treated with a veterinarian directed protocol. Accelerometer data were evaluated 4 days prior to exposure (d -4 to -1); on day of ration change (d 0); and 4 days post exposure (d 1 to 4). Herddogg accelerometer data from 3 ewes displaying symptoms identified a decrease in activity (P ≤ 0.03) for 2 days after feed exposure compared to the 4 days before exposure. Three days after exposure and 2 days after treatment, no difference in activity was detected (P > 0.05) between pre- and post-activity levels. Herddogg accelerometers can identify similar behavioral changes as Axivity accelerometers. The correlation of the standard deviation of movement intensity derived from the Axivity accelerometer and the Herddogg activity metric was 0.67. It is crucial to detect subtle behavioral changes at onset of illness, to allow for prompt producer intervention before animal health is compromised. These results suggest that real-time or near-real time accelerometers, such as Herddogg, have potential to detect illness in ewes in a pen setting.
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Gurule, Sara C., Melissa Aguirre, Kylee Forrest, Victor V. Flores, John Wenzel, Colin Tobin, Derek Bailey i Jennifer A. Hernandez Gifford. "PSII-16 Potential of sensor technology to detect changes in behavior related to health status of ewes following exposure to mold-contaminated feed". Journal of Animal Science 99, Supplement_3 (8.10.2021): 313–14. http://dx.doi.org/10.1093/jas/skab235.576.
Pełny tekst źródłaStreszczenie:
Abstract Behavior can be a valuable indicator of an animal’s health and wellness state, emphasizing the importance of monitoring changes in behavior. Sensor technologies can identify changes in animal activity, providing the potential to detect abnormal behavior associated with health status and animal welfare. The aim of this study was to investigate sheep behavior before and after illness caused by mold-contaminated feed using tri-axial accelerometers. Twenty-five ewes were fitted with HerdDogg biometric accelerometer ear tags. Thirteen ewes also had Axivity AX3 accelerometers attached on the opposite side ear tag. Tri-axial accelerometers were attached to mature ewes for the purpose of parturition evaluation, when an unexpected ration change occurred. The entire sheep flock was exposed to mold-contaminated feed, symptoms were immediately observed, and symptomatic ewes were treated with a veterinarian directed protocol. Accelerometer data were evaluated 4 days prior to exposure (d -4 to -1); on day of ration change (d 0); and 4 days post exposure (d 1 to 4). Herddogg accelerometer data from 3 ewes displaying symptoms identified a decrease in activity (P ≤ 0.03) for 2 days after feed exposure compared to the 4 days before exposure. Three days after exposure and 2 days after treatment, no difference in activity was detected (P > 0.05) between pre- and post-activity levels. Herddogg accelerometers can identify similar behavioral changes as Axivity accelerometers. The correlation of the standard deviation of movement intensity derived from the Axivity accelerometer and the Herddogg activity metric was 0.67. It is crucial to detect subtle behavioral changes at onset of illness, to allow for prompt producer intervention before animal health is compromised. These results suggest that real-time or near-real time accelerometers, such as Herddogg, have potential to detect illness in ewes in a pen setting.