The objective of this study was to evaluate the ear-tag-based accelerometer system Smartbow (Smartbow GmbH, Weibern, Austria) for detecting rumination time, chewing cycles, and rumination bouts in ...indoor-housed dairy cows. For this, the parameters were determined by analyses of video recordings as reference and compared with the results of the accelerometer system. Additionally, we tested the intra- and inter-observer reliability as well as the agreement of direct cow observations and video recordings. Ten Simmental dairy cows in early lactation were equipped with 10-Hz accelerometer ear tags and kept in a pen separated from herd mates. A total mixed ration was fed twice a day via a roughage intake control system. During the study, cows' rumination and other activities were directly observed for 20 h by 2 trained observers. Additionally, cows were video recorded for 19 d, 24 h a day. After exclusion of unsuitable videos, 2,490 h of cow individual 1-h video sequences were eligible for further analyses. Out of this, one hundred 1-h video sequences were randomly selected and visually and manually classified by a trained observer using professional video analyses software. Based on these analyses, half of the data was used for development (based on data of 50-h video analyses) and testing (based on data of additional 50-h video analyses) of the Smartbow algorithms, respectively. Inter- and intra-observer reliability as well as the comparison of direct against video observations revealed in high agreements for rumination time and chewing cycles with Pearson correlation coefficients >0.99. The rumination time, chewing cycles, as well as rumination bouts detected by Smartbow were highly associated (r > 0.99) with the analyses of video recordings. Algorithm testing revealed in an underestimation of the average ± standard deviation rumination time per 1-h period by the Smartbow system of 17.0 ± 35.3 s (i.e., −1.2%), compared with visual observations. The average number ± standard deviation of chewing cycles and rumination bouts was overestimated by Smartbow by 59.8 ± 79.6 (i.e., 3.7%) and by 0.5 ± 0.9 (i.e., 1.6%), respectively, compared with the video analyses. In summary, the agreement between the Smartbow system with video analyses was excellent. From a practical and clinical point of view, the detected differences were negligible. However, further research is necessary to test the system under various field conditions and to evaluate the benefit of incorporating rumination data into herd management decisions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Aiming at the problem that the deterministic errors caused by non-orthogonal installation, calibration factor, zero bias and other factors in production and in the use of accelerometers need to be ...calibrated by high-precision instruments, support vector machine regression is used to process the original data output by the accelerometer, and the processed data of each axis are used to establish a parameter calibration model without reference datum through the relationship between the output value of each axis of accelerometer, gravity acceleration and coaxial reversal in the paper. Then, the adaptive mutation rate is used to dynamically adjust the number of reverse learning particles, and the particles of particle swarm optimization algorithm are selected and adjusted according to the reverse learning, which solves the problems that particle swarm optimization algorithm tends to fall into localoptimum and the convergence speed is slow, through which a fast, accurate and simple calibration can be realized, and the performance of particle swarm optimization algorithm is improved. The calibration experiment shows that the improved particle swarm optimization algorithm has higher accuracy and faster convergence speed than the particle swarm optimization algorithm, and the calibration parameter accuracy is higher than that of the least square method, which does not need the datum of each axis. The calibration model proposed in this paper can realize a benchmark-free calibration outside the laboratory. At the same time, the improved particle swarm optimization algorithm can obtain calibration parameters with higher accuracy and faster speed in the rapid calibration, which provides the idea of a new model for accelerometer calibration and expands the application environment of accelerometer.
Display omitted
•The relationship between the gravity acceleration and the output values of each axis of the accelerometer is used.•According to the established model, SVR is used to preprocess the input data of the model.•Reverse learning and mutation rate are proposed to modify the particles of PSO.
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Abstract Background Rapid improvements in inexpensive, low-power, movement and environmental sensors have sparked a revolution in animal behavior research by enabling the creation of data loggers ...(henceforth, tags) that can capture fine-grained behavioral data over many months. Nevertheless, development of tags that are suitable for use with small species, for example, birds under 25 g, remains challenging because of the extreme mass (under 1 $$\textrm{g}$$ g ) and power (average current under 1 $$\upmu$$ μ A) constraints. These constraints dictate that a tag should carry exactly the sensors required for a given experiment and the data collection protocol should be specialized to the experiment. Furthermore, it can be extremely challenging to design hardware and software to achieve the energy efficiency required for long tag life. Results We present an activity monitor, BitTag, that can continuously collect activity data for 4–12 months at 0.5–0.8 $$\textrm{g}$$ g , depending upon battery choice, and which has been used to collect more than 500,000 h of data in a variety of experiments. The BitTag architecture provides a general platform to support the development and deployment of custom sub- $$\textrm{g}$$ g tags. This platform consists of a flexible tag architecture, software for both tags and host computers, and hardware to provide the host/tag interface necessary for preparing tags for “flight” and for accessing tag data “post-flight”. We demonstrate how the BitTag platform can be extended to quickly develop novel tags with other sensors while satisfying the 1g/1 $$\upmu$$ μ A mass and power requirements through the design of a novel barometric pressure sensing tag that can collect pressure and temperature data every 60 $$\textrm{s}$$ s for a year with mass under 0.6 $$\textrm{g}$$ g .
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Physical activity (PA) quantification by estimating energy expenditure (EE) is essential to health. Reference methods for EE estimation often involve expensive and cumbersome systems to wear. To ...address these problems, light-weighted and cost-effective portable devices are developed. Respiratory magnetometer plethysmography (RMP) is among such devices, based on the measurements of thoraco-abdominal distances. The aim of this study was to conduct a comparative study on EE estimation with low to high PA intensity with portable devices including the RMP. Fifteen healthy subjects aged <inline-formula><tex-math notation="LaTeX">23.84\pm 4.36</tex-math></inline-formula> years were equipped with an accelerometer, a heart rate (HR) monitor, a RMP device and a gas exchange system, while performing 9 sedentary and physical activities: sitting, standing, lying, walking at 4 and 6 km/h, running at 9 and 12 km/h, biking at 90 and 110 W. An artificial neural network (ANN) as well as a support vector regression algorithm were developed using features derived from each sensor separately and jointly. We compared also three validation approaches for the ANN model: leave one out subject, 10 fold cross-validation, and subject-specific. Results showed that 1. for portable devices the RMP provided better EE estimation compared to accelerometer and HR monitor alone; 2. combining the RMP and HR data further improved the EE estimation performances; and 3. the RMP device was also reliable in EE estimation for various PA intensities.
We propose a novel noniterative orientation estimation method based on the physical and geometrical properties of the acceleration, angular rate, and magnetic field vectors to estimate the ...orientation of motion sensor units. The proposed algorithm aims that the vertical (up) axis of the earth coordinate frame is as close as possible to the measured acceleration vector and that the north axis of the earth makes an angle with the detected magnetic field vector as close as possible to the estimated value of the magnetic dip angle. We obtain the sensor unit orientation based on the rotational quaternion transformation between the earth and the sensor unit frames. We evaluate the proposed method by incorporating it into an activity recognition scheme for daily and sports activities, which requires accurately estimated sensor unit orientations to achieve invariance to the orientations at which the units are worn on the body. Using four different classifiers on a publicly available data set, the proposed methodology achieves an average activity recognition accuracy higher than the state-of-the-art methods, as well as being computationally efficient enough to be executed in real time.
Bedload movement is fundamentally probabilistic. Our quantitative understanding of gravel transport is particularly limited when flow conditions just exceed thresholds of motion, in part because of ...difficulties in measuring transport statistics during natural floods. We used accelerometer‐embedded tracer clasts to precisely measure the timing of grain motions and rests during snowmelt floods in Halfmoon Creek, a gravel‐bed mountain stream in Colorado, USA. These new data let us explore how probabilities of tracer movement varied as functions of discharge and time. Bedload hysteresis occurred over both daily and seasonal timescales and included clockwise, counterclockwise, and figure‐eight patterns. We empirically explain the hysteresis by modifying a bedload transport model to have an evolving threshold of motion parameter. We calculate how the thresholds of motion progressively evolved through time over 22 days during the 2015 snowmelt flood. Our results quantitatively show that thresholds of motion are functions of both (a) cumulative shear stress and (b) temporal changes in shear stress during floods.
Plain Language Summary
Predicting the effects of floods on mountain river channels remains difficult but is important because floods affect people, communities, and ecosystems. Our research shows that the amount and timing of gravel transported downstream depends not only on how much water is flowing in the channel but also on the “history” of flow and sediment movement that has occurred previously during the flood or previous recent floods. We developed “smartrocks” that each hold sensors and batteries to measure the exact timing of movement of these artificial tracer gravels. We collected field data during a month‐long flood in a stream in the Rocky Mountains near Leadville, Colorado, USA. By measuring exactly when rocks move during floods, we can better understand how to predict when channels will be stable or will change during future floods of different sizes and how much change is likely to occur.
Key Points
“Smartrock” tracer cobbles were used to measure the timing of gravel transport during a natural snowmelt flood
Thresholds of motion increased with cumulative discharge but decreased after days of high peak discharge
Evolving thresholds of motion can explain observed bedload hysteresis
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This study was the first to compare the differences in trunk/shoulder kinematics and impact vibration of the upper extremity during backhand strokes in wheelchair tennis players and the able-bodied ...players relative to standing and sitting positions, adopting an electromagnetic system along with wearable tri-axial accelerometers upon target body segments. A total of 15 wheelchair tennis players and 15 able-bodied tennis players enrolled. Compared to players in standing positions, wheelchair players demonstrated significant larger forward trunk rotation in the pre-preparation, acceleration, and deceleration phase. Significant higher trunk angular velocity/acceleration and shoulder flexion/internal rotation angular velocity/acceleration were also found. When able-bodied players changed from standing to sitting positions, significant changes were observed in the degree of forward rotation of the trunk and shoulder external rotation. These indicated that when the functions of the lower limbs and trunk are lacking or cannot be used effectively, "biomechanical solutions" such as considerable reinforcing movements need to be made before the hitting movement. The differences between wheelchair tennis players and able-bodied players in sitting positions could represent the progress made as the wheelchair players evolve from novices to experts. Knowledge about how sport biomechanics change regarding specific disabilities can facilitate safe and inclusive participation in disability sports such as wheelchair tennis.
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Introduction
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Wrist-worn accelerometer has gained popularity recently in commercial and research use for physical activity tracking. Yet, no consensus exists for standardized wrist-worn data ...processing, and physical activity data derived from wrist-worn accelerometer cannot be directly compared with data derived from the historically used hip-worn accelerometer. In this work, through a systematic review, we aim to identify and analyze discrepancies between wrist-worn versus hip-worn ActiGraph accelerometers in measuring adult physical activity.
Methods
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A systematic review was conducted on studies involving free-living data comparison between hip- and wrist-worn ActiGraph accelerometers among adult users. We assessed the population, study protocols, data processing criteria (axis, epoch, wear-time correction, etc.), and outcome measures (step count, sedentary activity time, moderate-to-vigorous physical activity, etc.). Step count and activity count discrepancy were analyzed using meta-analysis, while meta-analysis was not attempted for others due to heterogeneous data processing criteria among the studies.
Results
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We screened 235 studies with 19 studies qualifying for inclusion in the systematic review. Through meta-analysis, the wrist-worn sensor recorded, on average, 3,537 steps/day more than the hip-worn sensor. Regarding sedentary activity time and moderate-to-vigorous physical activity estimation, the wrist sensor consistently overestimates moderate-to-vigorous physical activity time while underestimating sedentary activity time, with discrepancies ranging from a dozen minutes to several hours.
Discussions
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Our findings quantified the substantial discrepancies between wrist and hip sensors. It calls attention to the need for a cautious approach to interpreting data from different wear locations. These results may also serve as a reference for data comparisons among studies using different sensor locations.
Inertial measurement units (IMUs) are used in biomechanical and clinical applications for quantifying joint kinematics. This study aimed to assist researchers new to IMUs and wanting to develop an ...inexpensive IMU system to estimate the relative angle between IMUs, while understanding the different algorithms for estimating angular kinematics. Thus, there were three subgoals: 1) to present a low-cost and convenient IMU system utilizing two 6-axis IMUs for computing the relative angle between the IMUs; 2) to examine seven methods for estimating the angular kinematics of an IMU; and 3) to provide an open-source code and working principles of these methods. The raw gyroscopic and accelerometer data were preprocessed. The seven methods included gyroscopic integration (GI), accelerometer inclination (AC), basic complementary filter (BCF), Kalman filter (KF), digital motion processor (DMP, a proprietary algorithm), Madgwick filter (MW), and Mahony filter (MH). An apparatus was designed to test nine conditions that computed angles for rotation about three axes (roll, pitch, yaw) and three movement speeds (50°/s, 150°/s, 300°/s). Each trial lasted 25 min. The root-mean-squared error (RMSE) between the gold-standard value measured from the apparatus' encoder and the value calculated from each of the seven methods was determined. For roll and pitch, all methods accurately quantified angles (RMSE < 6°) at all speeds. For yaw, all methods except AC and DMP displayed RMSE < 6° at all speeds. AC could not be used for yaw angle computation, and DMP displayed RMSE >6°. Researchers can utilize appropriate methods based on their study's application.
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