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The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) satellites are equipped with high-precision three-axis accelerometers to measure all non-gravitational accelerations acting on the satellites. Precise knowledge of these perturbations is a major prerequisite for successful Gravity Field Recovery (GFR). Unfortunately, after only one month in orbit the accelerometer on one of the two satellites produced decreasingly accurate measurements. Due to this, the GRACE-D accelerometer data has to be replaced by artificial data for the use in the GFR process. In most existing approaches, which are called transplants, this data is constructed from GRACE-C measurements. We are developing a GRACE-D accelerometer product that relies mainly on modelled acceleration data instead of a full transplant. By using physical models to generate acceleration data, we are able to better understand the accelerometer signal and its characteristics, which is beneficial for subsequent processes involving accelerometer data. We present the evaluation of our modelled data in terms of comparison to the official Science Data System (SDS) accelerometer data. For the first GRACE-FO satellite real accelerometer is used as a reference, but for the second satellite the main comparisons are done with respect to the ACH1B transplant data product. To get information about environmental changes and long-term effects data sets covering one year and nearly the whole mission duration are presented. In terms of gravity field solutions the performance of purely modelled accelerometer data for GRACE-D and a minimalistic transplant approach of estimated density values is compared to transplant products of other processing centres for the year 2019 as well as one month of 2023. Through this, the modelled solution can act as a cross-reference to the transplant, contributing to an improved implementation of the external perturbation characteristics and the influence of higher solar activity on our models and the subsequent gravity field solutions can be determined. Comparison of the artificial acceleration data to the real ACT1B data for GRACE-C showed that models related to the atmospheric drag are the limiting factors in our high-precision environment modelling approach. Nevertheless, it was still possible to generate monthly gravity field solutions with a combination of ACT1B data for GRACE-C and artificial data for GRACE-D that showed hydrological signals. Application of the transplant that substitutes the limiting modelled thermospheric density with estimated values obtained at GRACE-C positions reduces the residuals between artificial and real acceleration data significantly. Estimation of gravity fields showed that the improvements due to the transplant directly transfer into the gravity field solutions. Our minimalistic and physically motivated transplant is shown to be a valuable alternative to the transplant data from TUG and JPL. The GROOPS software is utilized to generate monthly gravity field solution to guarantee comparability of the presented solutions for the geodesy community. The presented results not only show the quality of our transplant product but also enabled us to identify potential areas of improvement in the data generation process and our in–house gravity field recovery tool. The ZARM GRACE-D transplant product, all radiation accelerations and estimated density is available for download at: https://www.zarm.uni-bremen.de/zarm_daten/. [ABSTRACT FROM AUTHOR]

Multiple Sclerosis (MS) is a chronic inflammatory autoimmune, neurodegenerative disease that affects regular mobility and leads predominantly to physical disability. Poor sleep quality, commonly reported in MS patients, impacts their physical activity (PA). Accelerometers monitor 24-h activity patterns, offering insights into disease progression in daily life. To test if the sleep quality variables of MS patients, as assessed with wrist-worn accelerometers, differ from those of controls and are associated with PA and disease severity variables. Seven-day raw accelerometer data collected from 40 MS patients and 24 controls was processed using an open-source GGIR package, from which variables of sleep quality (sleep efficiency, wake after sleep onset (WASO), sleep regularity index (SRI), intradaily variability (IV)) and PA (of different intensities: inactivity, light (LPA), moderate (MPA), vigorous (VPA)) were analyzed. The variables were compared between the two study groups and in MS patients, correlation tested associations among the variables of sleep quality, PA, and disease severity (assessed with the Expanded Disability Status Scale, EDSS). Sleep efficiency was the only variable that differed significantly between MS patients and controls (lower in MS, p = 0.01). Both SRI (positively) and IV (negatively) correlated with the time spent in LPA and MPA. WASO correlated negatively with inactivity. This is one of the few studies with a wrist-worn accelerometer that shows a difference in sleep efficiency between MS patients and controls and, in MS, an association of sleep quality variables with PA variables. • Sleep quality was measured in MS patients using wrist-worn motion sensors. • MS patients showed a lower sleep efficiency when compared to healthy controls. • Variables of sleep quality were associated with physical activity in MS patients. [ABSTRACT FROM AUTHOR]

Thermosphere mass density and crosswind can be derived from accelerometer and GNSS tracking data. However, present datasets are often provided without comprehensive uncertainty specifications. We present a newly developed method that propagates measurement noise and errors in the satellite specification, thermosphere models, and radiation flux data to density observations to quantify their uncertainty. We focus specifically on density observations derived only from GNSS tracking data, which are limited in resolution along the orbit due to unavoidable smoothing. While the method can be applied to simulated and real data, making it useful for existing datasets and mission design, we demonstrated it using data from the GRACE B satellite. First, we compare the aerodynamic acceleration derived separately from the accelerometer and GNSS tracking data, highlighting the role of two significant noise sources: noise due to the differentiation of the positions and noise from the evaluation of the gravity vector at a noisy position. Averaging substantially reduces the noise in the aerodynamic acceleration as long as the differentiation noise dominates, which is the case at frequencies higher than the orbital frequency. Below, gravity vector evaluation noise becomes the dominating noise source, and consequently, averaging over longer periods leads to only marginal uncertainty reduction. Further, we investigate the uncertainty in the radiation pressure acceleration and demonstrate that averaging over one orbit substantially reduces the uncertainty in the along-track radiation pressure acceleration. We show that the uncertainty of density observations derived from the accelerometer data is about 4% of the density for data from 2003 when the GRACE B satellite was at 490 km altitude during high solar activity. In 2008, solar activity was very low, and the altitude was still 476 km, resulting in an uncertainty of 5%–20% because GNSS tracking noise and radiation pressure modeling errors play a much larger role as the aerodynamic acceleration becomes smaller. In the case of density observations derived only from GNSS tracking data, the uncertainty is about 5% in 2003 and 20%–50% in 2008 when averaging over one-third orbit. In 2008, GNSS tracking noise explains nearly all uncertainty in the density observation. Averaging over one orbit reduces the uncertainty to 4% and 5% in 2003 and 2008, respectively. [ABSTRACT FROM AUTHOR]

Twenty years of gravity observations from various satellite missions have provided unique data about mass redistribution processes in the Earth system, such as melting of Greenland's ice shields, sea level changes, ground and underground water depletion, droughts, floods, etc. The ongoing climate change underlines the urgent need to continue this kind of observations with future gravimetry missions using enhanced concepts and sensors. This paper studies the benefit of enhanced electrostatic and novel optical accelerometers and gradiometers for future gravimetry missions. One of the limiting factors in the current space gravimetry missions is the drift of the Electrostatic Accelerometers (EA) which dominates the error contribution at low frequencies (<1mHz). This study focuses on the modeling of enhanced EAs with laser-interferometric readout, so-called optical accelerometers, and on evaluating their performance for gravity field recovery in future satellite missions. In this paper, we simulate gravimetry missions in multiple scopes, applying various software modules for satellite dynamics integration, accelerometer (ACC) and gradiometer simulation and gravity field recovery. The total noise budgets of the modeled enhanced electrostatic and optical ACCs show a similar sensitivity as the ACC concepts from other research groups. Parametrization w.r.t. the weight of the test mass (TM) of ACCs and the gap between the TM and the surrounding electrode housing confirmed the fact known from previous results that an ACC with a heavier TM and a larger gap will perform better. Our results suggest that the anticipated gain of novel ACCs might at some point be potentially limited by noise from the inter-satellite laser ranging interferometry. In order to present the advantage of the novel sensors, time-variable background models and associated aliasing errors were not considered in our simulations. The utilization of enhanced EAs and optical ACCs shows a significant improvement of accuracy compared to the currently used GRACE-like EA. In addition, their benefit in double satellite pairs in a so-called Bender constellation as well as in the combination of low-low satellite-to-satellite tracking with cross-track gradiometry has been investigated. [ABSTRACT FROM AUTHOR]

Repetitive impacts during running are associated with some running injuries. Tibial acceleration is a proxy for tibial loading, and interventions that can decrease it are likely to be of interest to the running community. What effect do running gait cues have on peak vertical tibial acceleration at a comfortable and moderate running pace, and how will these cues be executed? Twenty-seven participants ran on a treadmill according to the following cues in random order: run softly and lightly, run with shorter steps, and increase preferred step rate by 7.5 %. Participants maintained each condition for one minute before returning to their 'preferred' running pattern for two minutes. Two tibia-mounted inertial measurement unit sensors were used to collect tibial acceleration data at a 'comfortable' and 'moderate' run pace. A repeated measures analysis of variance test was used to compare the means between running conditions. Compared to preferred running, the decrease step length (−8 %, p = 0.002, Cohen's d =0.33) and run softly and lightly (−9 %, p = 0.040, Cohen's d =0.38) cues provided a significant reduction in peak vertical tibial acceleration during a comfortable run pace. No significant difference was observed with an increase in step rate. Compared to preferred running, there was no significant difference in peak vertical tibial acceleration with any of the running gait cues during a moderate run pace. Instructing runners to decrease step length or run softly and lightly can result in small reductions in peak vertical tibial acceleration during a comfortable run pace, but running gait cues during a moderate run pace provide no effects. Differences in the execution of each cue are likely to influence overall tibial loading throughout the stride cycle. These findings provide novel biomechanical evidence for the potential effects of running retraining strategies for reducing tibial accelerations at different running paces. • Running gait cues can be effective in reducing tibial loads at a comfortable pace. • Using gait cues to reduce tibial loads at a moderate pace is more of a challenge. • Cues to increase step rate and decrease step length do not provide the same effect. [ABSTRACT FROM AUTHOR]

Pump thrombosis (PT) and related adverse complications contributed to the HeartWare Ventricular Assist Device (HVAD) market withdrawal. Many patients still receive lifelong support, with deficient PT surveillance based on pump power trends. Analysis of pump vibrations is better for detecting PT. Here, we investigated the feasibility of an extracorporeal accelerometer to detect PT from pump vibrations propagated out on the driveline. In a porcine HVAD model (n = 6), an accelerometer was attached to the pump as a reference and another to the driveline for comparisons of signals. In total, 59 thrombi were injected into the heart to induce PT, followed by intermittent thrombus washout maneuvers. Signals were compared visually in spectrograms and quantitatively in third harmonic saliences (S 3H) by correlation analysis. Receiver operating characteristic curves expressed the method's outcome in sensitivity vs specificity, with the overall diagnostic performance in the area under the curve (AUC) score. Five experiments had good driveline signal strength, with clear spectrographic relationships between the 2 accelerometers. Third harmonic driveline vibrations were visible 20 vs 30 times in the reference. The comparison in S 3H showed a strong correlation and yielded an AUC of 0.85. Notably, S 3H proved robust regarding noise and false PT detections. An extracorporeal accelerometer on the driveline can be a readily available method for accurate HVAD PT detection before an accelerometer integration with left ventricular assist device is feasible. [Display omitted] [ABSTRACT FROM AUTHOR]

Left ventricular assist devices (LVAD) provide circulatory blood pump support for severe heart failure patients. Pump inflow obstructions may lead to stroke and pump malfunction. We aimed to verify in vivo that gradual inflow obstructions, representing prepump thrombosis, are detectable by a pump-attached accelerometer, where the routine use of pump power (P LVAD) is deficient. In a porcine model (n = 8), balloon-tipped catheters obstructed HVAD inflow conduits by 34% to 94% in 5 levels. Afterload increases and speed alterations were conducted as controls. We computed nonharmonic amplitudes (NHA) of pump vibrations captured by the accelerometer for the analysis. Changes in NHA and P LVAD were tested by a pairwise nonparametric statistical test. Detection sensitivities and specificities were investigated by receiver operating characteristics with areas under the curves (AUC). NHA remained marginally affected during control interventions, unlike P LVAD. NHA elevated during obstructions within 52-83%, while mass pendulation was most pronounced. Meanwhile, P LVAD changed far less. Increased pump speeds tended to amplify the NHA elevations. The corresponding AUC was 0.85-1.00 for NHA and 0.35-0.73 for P LVAD. Elevated NHA provides a reliable indication of subclinical gradual inflow obstructions. The accelerometer can potentially supplement P LVAD for earlier warnings and localization of pump. [ABSTRACT FROM AUTHOR]

Previously-unpublished data from the Pioneer Venus multiprobe mission are presented, documenting key events in the entry and descent. The data comprise the latter part of the hypersonic entry as documented by accelerometers, and show the deceleration of the vehicle through the transonic region, and the deployment of the parachute. Such data are of interest for comparison with the DAVINCI mission under development, and the parachute deployment record is compared with those of other missions to inform the sample rate needed to characterize key events. [ABSTRACT FROM AUTHOR]

The Gait&Balance (G&B) App has produced valid and reliable measures of gait and balance in young healthy adults but has not been tested in older adults. In healthy middle-to-older aged adults, are G&B App measurements sensitive to age, valid against clinical and kinematic measures, and reliable? Healthy participants (n = 34, 14 male, 42–94 years) completed the G&B App protocol three times within a single session. 3D kinematics were collected concurrently. Clinical balance measures were collected (Modified Clinical Test of Sensory Interaction in Balance (mCTSIB), Mini Balance Evaluation Systems Test (MBT), and Functional Gait Assessment (FGA)). Sensitivity to age was assessed with Pearson's correlations. Validity tests included Pearson's correlations and Bland-Altman limits of agreement. Reliability tests included intra-class correlation coefficients and standard error of the measure. During quiet stance on a compliant surface, the G&B App was sensitive to age-related differences not detectable with the mCTSIB. During walking tasks, there was adequate convergent validity between the MBT and G&B App measures of step length, and between the FGA and G&B App measures of walking speed, step length, and periodicity. The G&B App had moderate-to-excellent validity against 3D kinematics for postural stability during quiet stance (r 0.98 [0.98, 0.99]), step time (r 0.97 [0.96, 0.98]), walking speed (r 0.79 [0.7, 0.86]), and step length (r 0.73 [0.61, 0.81]). Test-retest reliability was moderate-to-excellent for G&B App measures of postural stability, walking speed, periodicity, step length, and step time. G&B App measures of step length asymmetry, step length variability, step time asymmetry, and step time variability had poor validity and reliability. The G&B App was sensitive to age-related differences in balance not detectable with clinical measurement. It provides valid and reliable measures of postural stability, step length, step time, and periodicity, which are not currently available in standard practice. • Standard clinical measures of balance lack sensitivity and responsiveness. • Smartphone-based accelerometry offers an alternative, accessible measurement method. • The proposed Gait&Balance App measures balance and spatiotemporal gait parameters. • These smartphone parameters correlate with standard clinical and kinematic data. • The Gait&Balance App has potential to be more sensitive than clinical measures. [ABSTRACT FROM AUTHOR]

Background: Walking speed strongly correlates with health outcomes, making accurate assessment essential for clinical evaluations. However, assessments tend to be conducted over short distances, often in a laboratory or clinical setting, and may not capture natural walking behavior. To address this gap, the following questions are investigated in this work: Is walking speed significantly influenced by the continuity and duration of a walking bout? Can preferred walking speed be inferred by grouping walking bouts using duration and continuity?Methods: We collected two weeks of continuous data from fifteen healthy young adults using a thigh-worn accelerometer and a heart rate monitor. Walking strides were identified and grouped into walking periods. We quantified the duration and the continuity of each walking period. Continuity is used to parameterize changes in stepping rate related to pauses during a bout of walking. Finally, we analyzed the influence of duration and continuity on estimates of stride speed, and examined how the distribution of walking speed varies depending on different walking modes (defined by duration and continuity).Results: We found that continuity and duration can be used to explain some of the variability in real-world walking speed (p<0.001). Speeds estimated from long continuous walks with many strides (42% of all recorded strides) had the lowest standard deviation. Walking speed during these bouts was 1.41ms-1 (SD = 0.26ms-1).Significance: Walking behavior in the real world is largely variable. Features of real-world walks, like duration and continuity, can be used to explain some of the variability observed in walking speed. As such, we recommend using long continuous walks to confidently isolate the preferred walking behavior of an individual. [ABSTRACT FROM AUTHOR]

Background: Many activity trackers have been developed, but steps can still be inconsistent from one monitor to another.Research Question: What are the differences and associations between the steps of 13 selected consumer-based and research-grade wearable devices during 1 standardized day in a metabolic chamber and 15-day free-living trials?Methods: In total, 19 healthy adults between 21 and 50 years-old participated in this study. Participants were equipped with 12 accelerometer-based active trackers and one pedometer (Yamasa) in order to monitor the number of steps per day. The devices were worn on the waist (ActiGraph, Omron, Actimarker, Lifedorder, Withings, and Yamasa) or non-dominant wrist (Fitbit, Garmin, Misfit, EPSON, and Jawbone), or placed in a pocket (Omron CaloriScan, and TANITA). Participants performed structured activities over a 24 h period in a chamber (Standardized day), and steps were monitored in the same participants in free-living trials for 15 successive days using the same monitors (free-living days).Results: When the 13 monitors were ranked by their steps, waist-worn ActiGraph was located at the center (7th) of the monitors both in the Standardized (12,252 ± 598 steps/day, mean ± SD) and free-living days (9295 ± 4027 steps/day). The correlation between the accelerometer-based devices was very high (r = 0.87-0.99). However, the steps of Yamasa was significantly lower in both trials than ActiGraph. The wrist-worn accelerometers had significantly higher steps than other devices both trials (P < 0.05). The differences between ActiGraph and Actimarker or Lifecorder was less than 100 steps/day in the Standardized day, and the differences between ActiGraph and Active Style Pro was less than 100 steps/day in the free-living days. Regression equation was also performed for inter-device compatibility.Significance: Step obtained from the wrist-worn, waist-worn, and pocket-type activity trackers were significantly different from each other but still highly correlated in free-living conditions. [ABSTRACT FROM AUTHOR]

The piezoelectric voltage constant (g 33) is a material parameter critical to piezoelectric voltage-type sensors for detecting vibrations or strains. Here, we report a lead-free (K,Na)NbO 3 (KNN)-based piezoelectric accelerometer with voltage sensitivity enhanced by taking advantage of a high g 33. To achieve a high g 33 , the magnitudes of piezoelectric charge constant d 33 and dielectric permittivity ε r of KNN were best coupled by manipulating the intrinsic polymorphic phase boundaries effectively with the help of Bi-based perovskite oxide additives. For the KNN composition that derives benefit from the combination of ε r and d 33 , the value of g 33 was found to be 46.9 × 10−3 V·m/N, which is significantly higher than those (20 – 30 × 10−3 V·m/N) found in well-known polycrystalline lead-based ceramics including commercial Pb(Zr,Ti)O 3 (PZT). Finally, the accelerometer sensor prototype built using the modified KNN composition demonstrated higher voltage sensitivity (183 mV/g) when measuring vibrations, showing a 29% increase against the PZT-based sensor (142 mV/g). [ABSTRACT FROM AUTHOR]

Background: Different supports for hydration can influence total body mass and affect running biomechanics.Research Question: Do different hydration supports affect the perceived exertion and comfort, stride kinematics, and impact accelerations during running?Methods: This was a crossover study design. Thirteen trail runners completed a treadmill running test divided into four different durations and randomized hydration supports conditions, lasting 8 min each at moderate intensity: A) waist bag (0.84 kg); B) medium load backpack (0.84 kg); C) full load backpack (3.40 kg); and D) a control condition without water support. Impact accelerations were measured for 30 s in 4, 6, and 8 min. The rate of perceived exertion and heart rate were registered on minutes 4 and 8. At the last minute of each condition, comfort perception was registered RESULTS AND SIGNIFICANCE: No condition affected the stride kinematics. Full load backpack condition reduced head acceleration peak (-0.21 g; p = 0.04; ES=0.4) and head acceleration magnitude (-0.23 g; p = 0.03; ES=0.4), and increased shock attenuation (3.08 g; p = 0.04; ES=0.3). It also elicited higher perceived exertion (p < 0.05; ES>0.8) being considered heavier (p < 0.01; ES > 1.1). The waist bag condition was more comfortable in terms of noise (p = 0.006; ES=1.3) and humidity/heat (p = 0.001; ES=0.8). The waist bag was the most comfortable support. On the other hand, the full backpack elicited lower comfort and was the only generating compensatory adjustments. These results may help to improve design of full load backpack aiming at comfort for runners. [ABSTRACT FROM AUTHOR]

Background: Postural adjustments involve displacements of the center of mass (COM), controlled by the central nervous system (CNS), to maintain equilibrium whilst standing. Postural adjustments can be anticipatory (APAs) or compensatory (CPAs), and are triggered to counteract predictable perturbations.Research Question: Is the new smartphone application, Momentum, a valid and reliable tool for the assessment of body balance, by measuring APAs and CPAs using accelerometer readings?Methods: 20 young adults were exposed to external predictable perturbations induced at the shoulder level, whilst standing. COM linear acceleration was recorded by Momentum (extracting data from a smartphone's accelerometer) and a 3D motion capture system.Results: The key results demonstrated a very high, significant correlation (r ≥ 0.7, p < 0.05) between the two device settings in the APA parameters, which obtained r = 0.65, denoting a high correlation. Considering the reliability, variables that are compensatory in nature are presented on a scale of good to excellent in measurement methods, kinematics, and Momentum. However, the anticipatory variables presented excellent reliability only for the kinematics.Significance: These experiments show that Momentum is a valid method for measuring COM acceleration under predictable perturbations and is reliable for compensatory events. [ABSTRACT FROM AUTHOR]

Precision technology devices can measure and detect relative changes in an animal's behavior to possibly create alerts to intervene and to administer treatments. However, the association of relative changes in daily feeding and activity behaviors in calves with bovine respiratory disease (BRD) status is still largely unexplored. The objective of this case-control study was to determine if daily behavioral patterns of preweaning dairy calves (measured by precision technologies) change before BRD diagnosis. This case-control study enrolled 33 pairs of calves (33 BRD calves matched by age, sex, and birthdate to 33 controls) health scored daily for BRD for the preweaning period (until 50 d on the automated feeder). A pedometer (IceQube, Ice Robotics) was attached to the left rear leg to track activity (lying time, lying bouts, total steps, and acceleration activity index). At 3.0 ± 2.0 d of age, calves were trained to use the automated feeder, which recorded milk and calf starter intake, drinking speed, and feeder visits. Calves were allotted a maximum 10 L/d of milk replacer (Cow's Match, Land O'Lakes Animal Milk Products Co.; 140 g/L) and starter (Special Calf Starter and Grower, Baghdad Feeds), ad libitum. Calves were scored daily for signs of BRD using the Wisconsin scoring system, and their lungs were scored with ultrasonography twice weekly. Outward signs of BRD as defined by the Wisconsin scoring system and an area of consolidated lung ≥3.0 cm2 was identified as BRD (d 0). Relative changes in daily behaviors were calculated using d −5 before BRD diagnosis as the baseline for each calf for each behavior. Linear mixed models were used to investigate the association of BRD status with feeding behaviors, activity, and relative changes in calf behavior over a 5-d period before diagnosis, as well as the BRD status × day interaction. Calves with a BRD bout were diagnosed at an average age of 33.0 ± 9.0 d (mean ± standard deviation) and weighed 56.1 ± 9.7 kg. Over the period, BRD calves had reduced milk and starter intake, greater lying times, and fewer lying bouts, step counts, and activity indices when compared with healthy calves. Furthermore, there was a BRD status × day interaction for relative changes in unrewarded visits, and relative changes in calf starter intake. Specifically, BRD calves had a decline in relative changes in their unrewarded visits on d −4, −2, −1, and 0 compared with healthy calves. This study suggests that there is the potential to use feeding and activity behaviors to identify BRD development in preweaning calves. However, utilization of an animals' daily behavioral patterns in real time is fundamental for developing disease detection algorithms, thus we suggest relative changes in unrewarded visits may be useful for algorithm development when d −5 is used as a baseline. Future research should investigate the potential of feeding behavior and activity levels collectively to indicate BRD status in calves using machine learning techniques. [ABSTRACT FROM AUTHOR]

Physical activity (PA) is increasingly used as an adjunct treatment for alcohol use disorder (AUD). Previous studies have relied on self-report measures of PA, which are prone to measurement error. In the context of a randomized controlled trial of PA for AUD, we examined: (1) associations between device-measured and self-reported PA, (2) associations between PA measurements and alcohol use, and (3) the feasibility of obtaining device-measured PA data in this population. One-hundred and forty individuals with clinician-diagnosed AUD participated in a 12-week intervention comparing usual care (phone counselling) to yoga-based exercise and aerobic exercise. Device-measured PA (Actigraph GT3x), self-reported PA (International Physical Activity Questionnaire) and alcohol consumption (Timeline Follow Back Method) were assessed before and after the trial. Effects of the interventions on PA levels were assessed using linear mixed models. In total, 42% (n=59) of participants returned usable device-measured PA data (mean age= 56±10 years, 73% male). Device-measured and self-reported vigorous-intensity PA were correlated (β= −0.02, 95%CI= −0.03, −0.00). No associations were found for moderate-intensity PA. Compared to usual care, time spent in device-measured light-intensity PA increased in the aerobic exercise group (∆= 357, 95%CI= 709, 5.24). Increases in device-measured light-intensity PA were associated with fewer standard drinks (∆= −0.24, 95%CI= −0.03, −0.44), and fewer heavy drinking days (∆= −0.06, 95%CI=-0.01, −0.10). Increases in light-intensity/habitual PA were associated with less alcohol consumption in adults with AUD. Self-reported PA data should be interpreted with caution. Incentives are needed to obtain device-measured PA data in AUD populations. • First study to examine device-measured physical activity (PA) levels in AUD. • It is feasible to collect these data in AUD populations. • Incentives, including wrist-worn devices, may improve compliance. • Increases in light-intensity PA were associated with less alcohol consumption. [ABSTRACT FROM AUTHOR]

Due to unavoidable compliance in the drive trains of the individual links, all industrial robots exhibit some elasticity in their respective joints. This elasticity causes a discrepancy between the measured motor position and the actual link position of the robot. For highly dynamic movements of the robot, or in the case of heavy payloads, this can lead to significant deviations between the desired and actual end-effector pose of the robot. One approach to mitigate the resulting task performance degradation is using suitable state estimation strategies for elastic-joint robots. While critical for task performance, the link positions are typically not separately measured for industrial robots. Instead, standard robot control systems rely on the measured motor positions. To this end, this work studies the state estimation problem of elastic-joint industrial robots and compares the performance of different observers. The comparison is performed on an industrial robot with six degrees of freedom (6-DOF) using a laser tracker measurement of the end-effector movement as a ground truth. Four observer concepts are state-of-the-art strategies from the literature, which are briefly summarized first. Subsequently, two novel estimation strategies are proposed. The first exploits encoder and angular velocity measurements, and the second is an estimator that combines encoder, acceleration, and angular velocity measurements. To the best of the authors' knowledge, this is the first work that compares the performance of real-time observers for elastic-joints industrial robots with 6-DOF in an experimental setup. The properties of all observers are discussed in terms of estimation accuracy, sensor configuration, computational complexity, and required knowledge of model parameters. The experiments show that the novel estimation strategies improve the position estimation accuracy of the end-effector by up to 72 %. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Keel bone damage, which presents as fractures and/or deviations of the keel, has been detected in laying hens housed in all types of systems. Factors leading to keel bone damage in hens housed with limited vertical space, such as those housed in furnished systems, are not well understood, and are the topic of this study. Ten focal hens from each of 12 furnished cages (4 rooms of 3 cages) were fitted with keel mounted tri-axial accelerometers. Their behavior was video recorded continuously over two 3-wk trials: the first when the hens were between 52 and 60 wk of age, and the second approximately 20 wk later. The integrity of each hen's keel was evaluated at the start and end of each 3-wk trial using digital computed tomography. We identified predominant behaviors associated with acceleration events sustained at the keel (collisions, aggressive interactions and grooming) by pairing accelerometer outputs with video data. For each recorded acceleration event we calculated the acceleration magnitudes as the maximum summed acceleration recorded during the event, and by calculating the area under the acceleration curve. A principle components analysis, which was used as a data reduction technique, resulted in the identification of 4 components that were used in a subsequent regression analysis. A key finding is that the number of collisions a hen has with structures in her environment, and the number of aggressive interactions that a hen is involved, each affect the likelihood that she will develop 1 or more fractures within a 3-wk time span. This relationship between hen behavior and keel fracture formation was independent of the magnitude of acceleration involved in the event. Observed behavior did not have an impact on the formation of keel bone deviations, further supporting reports that the mechanisms underlying the 2 types of keel bone damage are different. [ABSTRACT FROM AUTHOR]

This study investigated how different shapes of umbrella handles and grip types influence muscle activation and postural variability under windy conditions. Seventeen adult participants were enrolled in this study, and different handle shapes (cylindrical, ellipsoidal, and triangular prism-shaped), grip types (four- and five-finger grip), and wind strengths were tested. Activation of the forearm and upper arm muscles was recorded using surface electromyography. Postural variability and ratings of (1) perceived difficulty of use and (2) perceived grip-posture variability were measured. The results indicated that activation of the finger flexor muscle increased under windy conditions, whereas postural variability was not affected. Weak wind (3.2–7.5 m/s) conditions caused greater perceived postural variability and activation of the wrist extensor muscle. The ellipsoidal handle shape had lower endpoint postural variability when held with a five-finger grip and also had lower perceived postural variability and difficulty compared to that with the cylindrical shape. Our findings can be used to select appropriate umbrella handle designs based on grip type and wind conditions. [ABSTRACT FROM AUTHOR]

—SiC is widely used in power electronics and high-temperature devices due to its comprehensive physicochemical properties, including high thermal stability, mechanical strength, etc. In recent years, the advantages of SiC for MEMS have gradually attracted the attention of researchers. However, the development of bulk SiC technology in the field of MEMS sensors has not been reviewed, especially in the fabrication and performance of MEMS bulk SiC sensors. The purpose of this review is to summarize the development status of bulk SiC materials, processes and sensors. The existing pressure sensors, accelerometers and other sensors based on SiC are reviewed. And the possible technological innovations for bulk SiC MEMS sensors are further proposed. [ABSTRACT FROM AUTHOR]

La principale cause de blessure au rugby à XV est l'impact. Les impacts sont enregistrés et classés selon quatre classes d'intensités grâce aux centrales inertielles embarquées avec l'unité GPS portée par les joueurs. Ainsi près de 800 impacts par match sont recensés pour seulement 23 joueurs. Ces impacts sont d'intensités variables suivant les joueurs et les actions au cours du jeu. Notre étude menée sur les données collectées pendant 2 ans de championnat Elite propose de recenser les effets de facteurs environnementaux fluctuant en cours de saison ainsi qu'une discussion sur la distribution des impacts par postes. L'étude est basée sur le traitement des rapports de match de 35 joueurs professionnels et 12 joueurs espoirs lors des saisons 2018 et 2019. Chaque joueur portait un GPS attitré de type S5 (Innovations Catapult, Scoresby, VIC, Australia). Les données ont été analysées sur R (v 3.6.1). Les résultats de cette étude démontrent qu'il existe une variation significative du nombre et de l'intensité des impacts entre les groupes de postes alors que l'endroit où se joue le match, le résultat du match, la compétition jouée ou la chronologie des matchs n'ont pas d'influence significative. Il apparaît que les arrières sont impliqués dans moins d'impacts que les avants, mais que l'intensité des impacts est supérieure. L'évolution du rugby moderne entraîne une aggravation des lésions liées aux impacts. Cette étude a permis de quantifier les différences entre les 4 postes avant et les 5 postes arrière en termes d'intensité et de probabilité. Les joueurs affectés à différents postes ont des morphologies et capacités physiques et techniques différentes qui peuvent expliquer nos observations et pourront être retenues comme critères objectifs de suivi de l'entraînement voire de sélection. Des études complémentaires sont nécessaires pour intégrer les caractéristiques cognitives des joueurs et prendre en compte l'influence des stratégies collectives. The main cause of injury in rugby union is impact. The impacts are recorded and classified according to four intensity brackets thanks to the on-board inertial units within the GPS unit worn by the players. Thus, nearly 800 impacts per match are recorded for only 23 players. These impacts are of variable intensity depending on the players and their actions during the game. Our study carried out on the data, collected during 2 years of the Elite French championship, proposes to identify the effects of environmental factors fluctuating throughout the season as well as a discussion on the distribution of impacts by position. The study is based on the processing of the match reports for 35 professional players and 12 Academy players during the 2018 and 2019 seasons. Each player wore an assigned S5 type GPS (Innovations Catapult, Scoresby, VIC, Australia). The data was analyzed on R (v 3.6.1). The results of this study show that there is a significant variation in the number and intensity of the impacts between positional groups. Additional factors which do not have a significant influence on this include whether the game is home or away, the result of the match, the different competitions played or the chronology of the matches throughtout the season. However, it appears that the backs are involved in less impact than the forwards, but the intensity of their impacts is greater. The evolution of modern rugby is leading to an increase in impact injuries. This study made it possible to quantify the differences between the 4 distinct positions within the forwards and the 5 distinct positions within the backs in terms of both the intensity and probability of their impacts. The players selected in these very specific positions all have individual morphologies and different physical and technical capacities, which may explain our observations and may be retained as objective criteria for monitoring training or even selection. Further studies are needed to integrate the cognitive characteristics of players, but also to take into account the influence of team technical strategies. [ABSTRACT FROM AUTHOR]

Background: One in two people with multiple sclerosis (PwMS) will fall in a three-month period. Predicting which patients will fall remains a challenge for clinicians. Standardized functional assessments provide insight into balance deficits and fall risk but their use has been limited to supervised visits.Research Question: The study aim was to characterize unsupervised 30-second chair stand test (30CST) performance using accelerometer-derived metrics and assess its ability to classify fall status in PwMS compared to supervised 30CST.Methods: Thirty-seven PwMS (21 fallers) performed instrumented supervised and unsupervised 30CSTs with a single wearable sensor on the thigh. In unsupervised conditions, participants performed bi-hourly 30CSTs and rated their balance confidence and fatigue over 48-hours. ROC analysis was used to classify fall status for 30CST performance.Results: Non-fallers (p = 0.02) but not fallers (p = 0.23) differed in their average unsupervised 30CST performance (repetitions) compared to their supervised performance. The unsupervised maximum number of 30CST repetitions performed optimized ROC classification AUC (0.79), accuracy (78.4%) and specificity (90.0%) for fall status with an optimal cutoff of 17 repetitions.Significance: Brief durations of instrumented unsupervised monitoring as an adjunct to routine clinical assessments could improve the ability for predicting fall risk and fluctuations in functional mobility in PwMS. [ABSTRACT FROM AUTHOR]

Peripheral artery disease (PAD) and lower levels of physical activity are both associated with higher mortality. Yet, their joint prognostic impact has not been systematically examined, especially in Hispanics/Latinos, and with objective measures. We aimed to examine the joint associations of PAD and physical activity with mortality in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We studied 7,620 Hispanic/Latino adults aged 45–74 years at baseline (2008–2011) who underwent assessment of PAD with ankle-brachial index (ABI) and physical activity with hip-worn accelerometry. We calculated four physical activity measures: sedentary time, light activity, moderate/vigorous activity, and total activity counts. We quantified the relationship between ABI and mortality overall, and by tertiles of activity measures in restricted cubic splines, using multivariable Cox models accounting for sampling weights. We also assessed cross-categories of ABI and activity measures with mortality. During a median follow up of 7.1 years, 314 participants died. We observed a U-shaped association of ABI with mortality overall (e.g., hazard ratio 1.80 [95%CI 1.20–2.80] at ABI 0.7 vs 1.2). This U-shaped association was generally consistent after stratifying by activity measures, but an elevated mortality risk for higher ABI was not evident in the most active tertile based on sedentary time, time in light activity, and total activity counts. In the cross-category analysis of ABI and physical activity, the highest mortality risk was consistently seen in abnormal ABI (≤0.9 or >1.4) plus the least active tertile (e.g., HR 5.61 [3.31–9.51] for light activity), compared to referent ABI (0.9–1.4) plus the other more active two tertiles, with no interactions between ABI and activity measure. Abnormal ABI and lower accelerometry-based physical activity were independently and jointly associated with mortality in Hispanics, suggesting the importance of simultaneously evaluating leg vascular condition and physical activity. [Display omitted] • Peripheral artery disease (PAD) and physical activity were associated with mortality. • Mortality risk increased greatly when PAD and low physical activity coexisted. • No interactions between PAD and physical activity were observed. • Simultaneously evaluating leg vasculature and physical activity improved prognosis. [ABSTRACT FROM AUTHOR]

Background Context: Physical inactivity has been described as both a cause and a consequence of low back pain (LBP) largely based on self-reported measures of daily activity. A better understanding of the connections between routine physical activity and LBP may improve LBP interventions.Purpose: In this study, we aim to objectively characterize the free-living physical activity of people with low back pain in comparison to healthy controls using accelerometers, and we aim to derive a set of LBP-specific physical activity minutes thresholds that may be used as targets for future physical activity interventions.Study Design: Cross-sectional.Patient Sample: A total of 22 low back pain patients and 155 controls.Outcome Measures: Accelerometry derived physical activity measures.Methods: Twenty-two people with LBP were compared to 155 age and gender-matched healthy controls. All subjects wore an ActiGraph accelerometer on the right hip for 7 consecutive days. Accelerometry-based physical activity features (count-per-minute CPM) were derived using Freedson's intervals and physical performance intervals. A random forest machine learning classifier was trained to classify LBP status using a leave-one-out cross-validation procedure. An interpretation algorithm, the SHapley Additive exPlanations (SHAP) algorithm was subsequently applied to assess the feature importance and to establish LBP-specific physical activity thresholds.Results: The LBP group reported mild to moderate disability (average ODI=18.5). The random forest classifier identified a set of 8 features (digital biomarkers) that achieved 88.1% accuracy for distinguishing LBP from controls. All of the top distinguishing features were related to differences in the sedentary and light activity ranges (<800 CPM), whereas moderate to vigorous physical activity was not discriminative. In addition, we identified and ranked physical activity thresholds that are associated with LBP prediction that can be used in future studies of physical activity interventions for LBP.Conclusions: We describe a set of physical activity features from accelerometry data associated with LBP. All of the discriminating features were derived from the sedentary and light activity range. We also identified specific activity intensity minutes thresholds that distinguished LBP subjects from healthy controls. Future examination on the digital markers and thresholds identified through this work can be used to improve physical activity interventions for LBP treatment and prevention by allowing the development of LBP-specific physical activity guidelines. [ABSTRACT FROM AUTHOR]

• A novel method using an accelerometer is used to evaluate the impairment of excitation-contraction (E-C) coupling in critical illness myopathy (CIM). • Significant prolongation of E-C coupling time is detected by our technique in the early stage of CIM. • We propose our technique as a supplementary testing procedure for early diagnosis of CIM. This study aimed to develop a simple and reliable technique to assess excitation-contraction (E-C) coupling for early diagnosis of critical illness myopathy (CIM). We prospectively performed clinical and electrophysiological examinations on patients admitted to intensive care unit (ICU). In addition to full neurological examinations and routine nerve conduction study, motor related potential (MRP) was recorded using an accelerometer attached to the base of hallux after tibial nerve stimulation, and E-C coupling time (ECCT) was measured from the latency difference between soleus compound muscle action potential (CMAP) and MRP. Of 41 patients evaluated, 25 met the criteria for ICU-acquired weakness, 23 of whom had CIM. The time to the first electrophysiological examination (time to first test) correlated negatively with CMAP and with MRP. Conversely, a positive correlation was observed between the time to first test and ECCT. E-C coupling impairment occurred in most of our patients with CIM by the third day of ICU admission, and prolonged ECCT could be the earliest detectable abnormality. The ECCT measurement is an easy and reliable technique to detect reduced muscle membrane excitability in the early stage of CIM. The ECCT measured by our method using an accelerometer may be a parameter that predicts the development of CIM. [ABSTRACT FROM AUTHOR]

Background: The Styrd Power Meter is gaining special interest for on-field gait analyses due to its low-cost and general availability. However, the reliability and validity of the Stryd during walking on positive slopes using different backpack loads have never been investigated.Research Question: Is the Stryd Power Meter reliable and valid for quantifying gait mechanics during walking on positive inclines and during level walking incorporating load carriage?Methods: Seventeen participants from a police force rescue team performed 8 submaximal walking trials for 5-min at 3.6 km·h-1 during different positive slope (1%, 10% and 20%) and backpack load (0%, 10%, 20%, 30% and 40% of body mass) conditions. Two Stryd devices were utilized for reliability analyses. Validity of cadence and ground contact time (GCT) were analyzed against a gold standard device (Optojump).Results: The Stryd demonstrated acceptable reliability [mean bias: < 2.5%; effect size (ES): < 0.25; standard error of the mean: < 1.7%; r: > 0.76] for power, cadence, and GCT. Validity measures (mean bias: <0.8%; ES: <0.07; r: >0.96; Lin's Concordance Coefficient: 0.96; Mean Absolute Percent Error: <1%) for cadence were also found to be acceptable. The Stryd overestimated (P < 0.001; ES: >5.1) GCT in all the walking conditions. A significant systematic positive bias (P < 0.022; r = 0.56-0.76) was found in 7 conditions.Significance: The Stryd Power Meter appears to produce reliable measurements for power output, cadence and GCT. The Stryd produced valid measurements for cadence during walking on positive slopes and during level walking with a loaded backpack. However, the Stryd is not valid for measuring GCT during these walking conditions. This study adds novel data regarding the reliability and validity of this device and might be of particular interest for scientists, practitioners, and first responders seeking reliable devices to quantify gait mechanics during walking. [ABSTRACT FROM AUTHOR]

Background: Although movement variability and long-range correlations (LRCs) have been assessed in relation to neuropathology and aging during walking, to date only a few studies have investigated these aspects in subjects of different skill levels during prolonged overground running.Research Question: What effect does skill level and run duration have on different stride parameters, measures of variability and long-range correlations?Methods: Using a between-subject repeated measures design, we assessed stride mechanics, variability and LRCs in recreational and elite runners over the course of a continuous exhaustive run. All subjects ran at a fixed, pre-determined running speed relative to their maximal performance. Stride parameters were continually recorded using a single foot-mounted inertial measurement unit. It was hypothesized that a significant reduction in the strength of the LRCs would occur over the course of the run and that the observed changes would be more pronounced in the group of recreational runners.Results: Runners maintained a consistent stride length (SL), stride time (ST) and contact time (CT) during the run, while peak impact acceleration increased. Across groups, long-range correlations significantly decreased over the course of the run, while the magnitude of the variability remained constant. LRCs did not differ significantly between groups.Significance: This is the first study to simultaneously investigate the effects of prolonged running and skill level on a range of stride parameters as well as stride-to-stride variability. Generally, long-range correlations were shown to be sensitive to run duration, while the magnitude of the variability did not differ between earlier and later stages of the run. The lack of a group effect on LRCs supports the idea that the mechanisms responsible for the emergence of temporal patterns in the stride pattern are not influenced by skill level. [ABSTRACT FROM AUTHOR]

GRACE and GRACE-FO require the reduction of non-gravitational accelerations, through an onboard accelerometer, to accurately estimate variations in the Earth's gravitational field. Accuracy in the accelerometer measurements is vital to this mass change recovery and significant errors will reduce the quality of the recovered science data. This paper describes our current characterization of error sources in the GRACE-FO accelerometers and the error mitigation strategies used in the generation of the JPL/CSR GRACE-FO Version 04 accelerometer data for public release. Our current error characterization model describes flicker noise on readings of one accelerometer plate pair on GRACE-D, impulse response limitations on both accelerometers, nonphysical once per revolution variations in the roll angular acceleration measurements on both accelerometers, significant correlated errors on all axes on GRACE-D, nominal thermal bias dependencies on both accelerometers, and expected nominal inter-measurement aliasing (cross-talk - expected as heritage from GRACE). Attitude reconstruction strategies incorporating star camera, inertial measurement unit, and magnetorquer measurements visibly improve angular acceleration recovery independent of the accelerometer. Error mitigation strategies for the linear acceleration measurements, associated with the calibrated accelerometer product provided in the version 04 release, dramatically improve estimates of the Earth's gravity field. While many of the error characterizations described here are not necessary for constructing the accelerometer transplant from GRACE-C to GRACE-D, as is currently done in the Version 04 release, the error characterizations described here lay the groundwork for future use of calibrated/corrected GRACE-D accelerometer data. [ABSTRACT FROM AUTHOR]

Background: Ambient light therapies are potentially effective in improving sleep disturbances and circadian rhythms. This study created a new lighting intervention model for elderly patients with dementia. It is hypothesized that exposure to bright ambient light in the morning is more effective than general lighting in improving sleep disturbances and circadian rhythms.Methods: A single-blind longitudinal-group experimental design was employed. The dementia participants came from the community and nursing homes. Those in the experimental group were exposed to ambient light at 2500 lux, and those in the comparison group were exposed to 114-307 lux. The corresponding sleep disturbances and circadian rhythms were determined using an accelerometer (XA-5). A longitudinal experimental design was adopted to observe the time to an effective response.Results: The covariates of benzodiazepine use and total activity during the day were analyzed using generalized estimating equations. The experimental group showed significant sleep efficiency improvement, with mean increases of 41.9% (P < 0.001) and 31.7% (P = 0.002), sleep time increases of 141 min (P = 0.001) and 135 min (P = 0.008), awakening time decreases of 116 min (P = 0.001) and 108 min (P = 0.002), and sleep onset advancements of 60-84 min/sleep offset delays of 57-79 min upon the fifth and ninth week, respectively. A 4-week bright ambient light intervention was the most effective.Conclusions: This study found that bright ambient light in the morning is beneficial for improving sleep disturbances and was driven by stabilizing circadian rhythms. [ABSTRACT FROM AUTHOR]

We have proposed a vibration sensor based on a Michelson interferometer. The sensor was developed in the form of a triaxial accelerometer, calibrated, and ultimately validated with reference calibrated devices during blast operations. The sensing function principle is based on the push–pull principle of the mass–spring system of a total of three interferometers. A housing was designed and fabricated using 3D printing to allow the sensor to be operated in the field. Sensor calibration was carried out in an accredited laboratory. The measured sensitivity values were approximately 60 dB re rad/g for the vertical axis and 48–51 dB re rad/g for the horizontal axes in the frequency range of 1 to 50 Hz. The sensitivity values of the presented sensor are comparable to or surpass those of the Michelson-based sensors described in the state-of-the-art. The resulting amplitude–frequency calibration models of the sensor were assembled for all three orthogonal measurement axes so that the particle velocity can be measured. Finally, comparative measurement to reference seismic stations was carried out during a multi-hole bench blast at the Kotouc Stramberk quarry to validate the calibration models. • Highly sensitive fiber optic sensor for the field of ground vibration measurement. • Three orthogonal components acceleration or particle velocity measurement. • Sensor encapsulated in 3D printed housing. • Tested in both the laboratory on calibration benches and in the field measurement. [ABSTRACT FROM AUTHOR]

• The study compares the performance of 13 artificial intelligence-based fall detection algorithms when applied to accelerometer signals captured at the waist of the test subject with a wearable device. • Unlike most related studies, which just use a single data repository to test their proposals, the analysis employs up to 11 different public laboratory-based datasets, as well as two databases with signals measured during real falls, and four repositories with mobility samples gathered during long-term monitoring campaigns. • The study considers not only the typical intra-dataset evaluation procedure followed by the literature but also cross-dataset evaluation (i.e. using data from a different repository for testing than that considered for training). • The performance metrics show that the behavior of all algorithms significantly degrades under cross-dataset evaluation conditions, both when tested with samples from another dataset generated in the laboratory and with real fall or long-term monitoring samples. • The results show that the algorithms tend to overfit the patterns of emulated falls (obtained from laboratory based datasets) used for training. Thus they are not able to extrapolate their learning correctly to conventional movements or new fall patterns, which reflects in a high percentage of undetected falls and a high hourly rate of false alarms. • The obtained results clearly question the evaluation procedures of fall detectors used so far in the literature, highlighting the importance of testing this type of detectors in realistic scenarios with signals from real falls and actual daily life movements. The evaluation of fall detection systems based on wearables is controversial as most studies in the literature benchmark their proposals against falls that are simulated by experimental subjects under unrealistic laboratory conditions. In order to systematically investigate the suitability of this procedure, this paper evaluates a wide set of artificial intelligence algorithms used for fall detection, when trained with a large number of datasets containing acceleration samples captured during the emulation of falls and ordinary movements and then tested with the signals of both actual falls and long-term traces collected from the constant monitoring of users during their daily routines. The results, based on a large number of repositories, show a remarkable degradation in all performance metrics (sensitivity, specificity and false alarm hourly rate) with respect to the typical case in which the detectors are tested with the same types of laboratory movements for which they were trained. [ABSTRACT FROM AUTHOR]

A Fiber Bragg Grating low-frequency accelerometer with a single-notched hinge in series is proposed to improve the hinge structure's sensitivity and the cross-sensitivity of the accelerometer of low-frequency seismic waves. The sensitivity and the cross-sensitivity of the accelerometer are improved by connecting the single-notched hinge structure in series and experimentally verified. Based on the theoretical analysis, the resonance frequency and sensitivity formula of the accelerometer are derived. At the same time, the accelerometer is simulated by finite element analysis software to simulate and analyze the characteristics of the accelerometer in terms of resonance frequency, strain distribution, and amplitude-frequency response. The structural parameters of the accelerometer are optimized by numerical analysis software, and the effects of the structural parameters on the sensitivity and resonance frequency of the accelerometer are analyzed. The experimental results show that the resonance frequency of the accelerometer is 110 Hz, the flat region is 0.6–50 Hz, the linearity is as high as 98.9%, the sensitivity is 1040.41 pm/g, and the cross-sensitivity of the accelerometer in the flat interval is 4.94%. This indicates that the accelerometer shows good linearity and cross-sensitivity in the flat interval, which well meets the needs of seismic wave signal monitoring in low-frequency oil and gas exploration. [Display omitted] • Tandem single-notch hinge structure reduces detector cross-sensitivity. • The top of the mass block is provided with a rectangular thin plate to improve sensitivity. • The dual grating packaging method effectively improves the sensitivity of the detector. • Small size, low processing cost, can achieve large area detection. [ABSTRACT FROM AUTHOR]

Fiber optic accelerometers have a wide range of applications in low-frequency vibration measurement, such as in earthquake monitoring, disaster early warning, underground resource exploration, and anti-seismic monitoring projects for critical structures like dams and bridges. In response to the current issues of Fiber Bragg Gratings (FBG) accelerometers being insensitive to low-frequency vibration signals and challenging to apply in engineering, a dual straight-wing FBG accelerometer for low-frequency vibration measurement is proposed. Firstly, a sensor model is established and theoretically analyzed. Secondly, the impact of the sensor's main structural parameters on sensitivity and natural frequency is analyzed, and the sensor is simulated using ANSYS. Finally, a prototype of the sensor is developed, and a low-frequency vibration testing system is set up to test the sensor's performance. Experimental results show that the accelerometer has a natural frequency of 39.1 Hz, operates in the 5–22 Hz frequency band, and has a sensitivity of 171.7 p.m./g, a dynamic range of 69.82 dB, and a transverse interference resistance of less than 9.5%. This research provides a new reference for the development of similar sensors. • The sensor is constructed with a double straight airfoil cantilever beam. • Structural parameter optimization and finite element simulation are carried out for each structural parameter of the sensor. • Built a low-frequency vibration testing system. • The signal of the time series is transformed into a fast Fourier transform using the periodogram method. [ABSTRACT FROM AUTHOR]

To investigate the independent and joint associations between sedentary behaviors (SB) and physical activity (PA) with inhibitory control (IC) in adults. A total of 111 participants (median age = 30 years; 60% women), completed the Stroop Color-Words test to assess IC. They also wore accelerometers for seven days to measure SB, light PA, moderate-to-vigorous PA (MVPA), and daily steps. We previously set cutoff points for SB and PA measurements and tested them to determine their association with IC. All analyses were adjusted for potential confounding factors including age, gender, post-secondary education, income, body mass index, and accelerometer wear time. Low SB, high MVPA, and high daily steps were independently associated with a better IC compared to their respective counterparts. Adults with low levels of SB and light PA demonstrated better IC performance (β = −227.67, 95%CI = −434.14 to −21.20) compared to those with high SB and low light PA. Conversely, individuals with high SB and high light PA exhibited worse performance (β = 126.80, 95%CI = 2.11 to 251.50) than those in the high SB and low light PA group. Furthermore, the joint association of low SB with high MVPA (β = −491.12, 95%CI = −689.23 to −293.01) or low SB with high daily steps (β = −254.29, 95%CI = −416.41 to −92.16) demonstrated better IC performance compared to those with high SB and low MVPA or low daily steps. Our findings highlight independent and joint associations between low SB, high MVPA, and high daily steps with enhanced IC in adults. • < 9 h/day of sedentary behavior was associated with better inhibitory control. • ≥ 21 min/day of MVPA was related to enhanced inhibitory control. • A minimum of 5000 daily steps were linked to better inhibitory control in adults. • Low SB with high MVPA or daily steps has a positive impact on inhibitory control. • Our study emphasizes SB and PA synergy for improved inhibitory control. [ABSTRACT FROM AUTHOR]

We examined the association between mode of commuting to/from school (i.e., walking, multimodal, and motorized-vehicle) and movement behaviours in several space-time domains (i.e., total day, home, school, transport, and other locations). Walking to and/or from school was associated with higher MVPA in all space-time domains except home, where no associations were found. After subtracting commuting time to/from school from total day domain, the associations in favour of walking to/from school were maintained compared to those using other commuting modes, and in transport domain these associations dissipated. The study suggests the importance of promoting walking to/from school for increasing MVPA levels. • Walking to/from school was associated with the highest MVPA levels in total day, school, transport, and other locations. • Walking to/from school accumulated the least sedentary time in total day, school, transport, and other locations. • Walking to/from school constitutes a substantial part of total day and transport MVPA levels. • Activity synergy hypothesis seems confirmed since associations were maintained after subtracting commuting times. [ABSTRACT FROM AUTHOR]

• Temperature compensation in gravimeters and accelerometers. • Multi-sensor and Machine Learning approaches. • Laboratory platform for training data generation. • Applicability to other measuring systems, such as magnetometers and gyroscopes. Temperature is a major source of inaccuracy in high-sensitivity accelerometers and gravimeters. Active thermal control systems require power and may not be ideal in some contexts such as airborne or spaceborne applications. We propose a solution that relies on multiple thermometers placed within the accelerometer to measure temperature and thermal gradient variations. Machine Learning algorithms are used to relate the temperatures to their effect on the accelerometer readings. However, obtaining labeled data for training these algorithms can be difficult. Therefore, we also developed a training platform capable of replicating temperature variations in a laboratory setting. Our experiments revealed that thermal gradients had a significant effect on accelerometer readings, emphasizing the importance of multiple thermometers. The proposed method was experimentally tested and revealed a great potential to be extended to other sources of inaccuracy as well as to other types of measuring systems, such as magnetometers or gyroscopes. [ABSTRACT FROM AUTHOR]

• Condition monitoring can be achieved in agricultural machines from vibration signal. • K Nearest Neighbors classifier achieves high accuracy when monitoring the machine. • Harmony Search algorithm increases accuracy and decreases training time. • Different vibration sensor locations do not show large differences in accuracy. • No specific information of the machine is needed in the design of the method. Monitoring the status of rotating components is important in modern machinery. The goal of this study is to evaluate the feasibility of using a k-Nearest Neighbors (kNN) classifier combined with a Harmony Search (HS) algorithm, to detect the operational status of rotating components within agricultural machines. Vibration data, the source data, were acquired from four accelerometers located along the chassis of a harvester. Five operational statuses of three rotating components of the harvester were studied: engine (low/maximum speed), thresher, and chopper (on/off and balanced/unbalanced). The methodology includes vibration signal acquisition, data preprocessing, smoothing, preselection of frequencies, Brute Force (BF) and Harmony Search frequency selection, and classification with kNN. The input frequencies for the classifier were chosen with either BF search or HS. The main results of the study were: i) the preselection of frequencies reduced the training time between 92.2% and 95.6%; ii) the smoothing stage improved accuracy; iii) HS reduced the training time between 82% and 90% in comparison with BF, reaching accuracies of nearly 100% in the five operational statuses with only 2 input frequencies; iv) similar levels of accuracy were obtained when using data from the accelerometers at different locations. The results suggested that it was feasible to predict the operational status of rotating components of agricultural machines using a kNN classifier with the combination of preselection, smoothing, and the HS algorithm. This feasibility was achieved both in terms of accuracy and computational burden, building upon previously proposed methods. [ABSTRACT FROM AUTHOR]

Self-supervised learning (SSL) has gained prominence in the field of accelerometer-based human activity recognition (HAR) due to its ability to learn from both labeled and unlabeled data. While labeled data acquisition is costly, it is relatively easy to accumulate unlabeled sensor data. However, few works utilize large-scale, unlabeled datasets for pre-training despite its positive impact on downstream HAR performance, shown in recent work. Cross-sensor upstream training has also received limited attention. We introduce a new auxiliary task, randomized cross-sensor masked reconstruction (RCSMR), for SSL. We pre-train a transformer encoder on the large-scale HUNT4 dataset with RCSMR. The resulting model exhibits better performance on two downstream datasets with the same sensor setup as HUNT4 (HARTH and HAR70+), achieving an average F1-score of 74.03%, surpassing two other auxiliary tasks (70.51% to 72.78%) and five supervised baselines (47.51% to 58.84%). Moreover, when applied to three datasets with sensor configurations distinct from HUNT4 (USC-HAD, PAMAP2, MobiAct), RCSMR outperforms nine state-of-the-art SSL methods, with an F1-score of 72.99% compared to F1-scores ranging from 51.46% to 69.88%. We further show that certain activities exhibit improved separability when utilizing latent representations learned through RCSMR, indicating reduced sensor position and orientation bias. Our method is applied in large-scale epidemiological studies, offering valuable insights into the impact of physical activity behavior on public health. [Display omitted] • New self-supervised cross-sensor learning auxiliary task (RCSMR) for HAR. • Large-scale dual-sensor pre-training, single-sensor downstream training. • RCSMR pre-trained Transformer outperforms supervised & SSL methods on 7 HAR datasets. • RCSMR has better activity separability in the latent space than other auxiliary tasks. • RCSMR is effective on limited amounts of labeled data and different model sizes. [ABSTRACT FROM AUTHOR]

Surgical implantation of acoustic transmitters is a widely used method to study the movement ecology and eco-physiology of sharks. Nevertheless, the impact of surgical implantation on the behaviour of the target species is seldom separated from the capture stress. Pyjama catsharks (Poroderma africanum) is a small benthic shark species endemic to South Africa. For this species, tonic immobility is insufficient to achieve adequate sedation for surgical implantation of internal transmitters and a combination of tonic immobility and anaesthetic is needed. Therefore, behavioural responses to surgical implantation of internal transmitters were quantified in pyjama catsharks using tri-axial accelerometers in a controlled captive environment for a 24-h period after capture and a 24-h period after surgery. A 2-state hidden Markov model was developed to investigate the sharks' activity patterns, as well as the related possible effects of the treatment type (capture vs surgery and surgery vs non surgery) and time of day. The results showed that the sharks which went through surgery (treatment group) spent significantly more time (58.7 % of their time) in a lower activity state, which we believe relates to higher stress levels, following surgery compared to following capture. Furthermore, sharks in the treatment group spent roughly 20 % more time in the lower activity state compared to the control group (without surgical implantation). These results could be related to the sedating effect of the anaesthetic, and/or suggest short-term behavioural stress response to the surgical implantation of transmitter, related to either biochemical stress or anatomical discomfort. Furthermore, the sharks changed their behavioural state more frequently in the three hours after the surgery and spent more time in a lower activity state. This emphasises the importance of allowing the sharks enough time to recover from the combination of anaesthesia and surgery before being released into the ocean. [ABSTRACT FROM AUTHOR]

A common practice in the construction of the garage floors of residential and office buildings is the construction of the concrete slab in two steps: one thick layer at the beginning of the work, a second thin layer at the end of it. This procedure saves time but also brings in the problem of a cold joint between the two layers which, eventually, may get loose or even split. However it is difficult to control the status of the concrete layers until they are completely split unless one make use of destructive tests such as the extraction of test samples. In this paper we demonstrate the use of vibrational data to assess and control the status of the joint between the two layers. To that end we have carried out two series of experiments. The first one is an experimental procedure in the laboratory with the goal to see if vibrational data are able to distinguish among different levels of fixation between the two layers. We use a concrete slab as the thick layer and a MDF board as the thin layer, bonded by means of gypsum plaster. Different amounts of the surface covered by the gypsum plaster give different levels of fixation between the layers. For each configuration we produced vibration with a standard tapping machine and measured it with the aid of a vibrometer. Our results are positive; with a simple test vibrational data can distinguish whether two layers are fixed by 25% or less, by 50% or by 100% of their surface. With the laboratory results we have designed a non-destructive test to be carried on in-situ measurements so as to ascertain the level of fixation of two layers of a concrete slab. The test is based on the installations described in Annex A of ISO 16251-1, so that it does not require large investments or facilities. It is able to cope with different kind of data and is independent of the characteristics of the slab thanks to the statistics tools applied to the data. The second one is the application of the test to data measured in an actual building with the aforementioned problem in its garage floor. We measured vibration induced by a different source, a car passing by, and in several locations, both with loose and well fixed layers. The vibration was recorded by the same vibrometer as above. Notwithstanding the differences in the data source, the test can be applied to the data and the results are compatible with the known status of the slab: we obtain a 77.0% of sensitivity and 54.5% of specificity, while only a 1.0% of false positives and none false negatives. The only drawback of the test is its high number of undecidable cases, which amounts to 24.1%. [Display omitted] • Measure vibration to check the condition of the joint between concrete layers. • Laboratory testing to detect the condition of the interlayer joint. • Comparison of laboratory and in-situ tests. • Test that distinguishes between more than 50% and less than 50% of surface bonded. • Very reliable non-destructive test. [ABSTRACT FROM AUTHOR]

Smartphone accelerometry has potential to provide clinicians with specialized gait analysis not available in most clinical settings. The Gait&Balance Application (G&B App) uses smartphone accelerometry to assess spatiotemporal gait parameters under two conditions: walking looking straight ahead and walking with horizontal head turns. This study investigated the validity of G&B App gait parameters compared with the GAITRite® pressure-sensitive walkway. Healthy young and older adults (age range 21–85 years) attended a single session where a smartphone was secured over the lumbosacral junction. Data were collected concurrently with the app and GAITRite® systems as participants completed the two walking conditions. Spatiotemporal gait parameters for 54 participants were determined from both systems and agreement evaluated with partial Pearson's correlation coefficients and limits of agreement. The results demonstrated moderate to excellent validity for G&B App measures of step time (r p 0.97, 95 % CI [0.96, 0.98]), walking speed (r p 0.83 [0.78, 0.87]), and step length (r p 0.74, [0.66, 0.80]) when walking looking straight ahead, and results were comparable with head turns. The validity of walking speed and step length measures was influenced by sex and height. G&B App measures of step length variability, step time variability, step length asymmetry, and step time asymmetry had poor validity. The G&B App has potential to provide valid measures of unilateral and bilateral step time, unilateral and bilateral step length, and walking speed, under two walking conditions in healthy young and older adults. Further research should validate this tool in clinical conditions and optimise the algorithm for demographic characteristics. [ABSTRACT FROM AUTHOR]

• This review focuses on the most useful methods and techniques for the study of movement and movement disorders. • Tools that can be used to study movement include kinematics, kinetics, and the underlying muscle activity with EMG. • The brain activity driving movement can be studied with EEG, MEG, and functional MRI. Clinical neurophysiology studies can contribute important information about the physiology of human movement and the pathophysiology and diagnosis of different movement disorders. Some techniques can be accomplished in a routine clinical neurophysiology laboratory and others require some special equipment. This review, initiating a series of articles on this topic, focuses on the methods and techniques. The methods reviewed include EMG, EEG, MEG, evoked potentials, coherence, accelerometry, posturography (balance), gait, and sleep studies. Functional MRI (fMRI) is also reviewed as a physiological method that can be used independently or together with other methods. A few applications to patients with movement disorders are discussed as examples, but the detailed applications will be the subject of other articles. [ABSTRACT FROM AUTHOR]

Background: Identifying clusters of physical activity (PA) from accelerometer data is important to identify levels of sedentary behaviour and physical activity associated with risks of serious health conditions and time spent engaging in healthy PA. Unsupervised machine learning models can capture PA in everyday free-living activity without the need for labelled data. However, there is scant research addressing the selection of features from accelerometer data. The aim of this systematic review is to summarise feature selection techniques applied in studies concerned with unsupervised machine learning of accelerometer-based device obtained physical activity, and to identify commonly used features identified through these techniques. Feature selection methods can reduce the complexity and computational burden of these models by removing less important features and assist in understanding the relative importance of feature sets and individual features in clustering.Method: We conducted a systematic search of Pubmed, Medline, Google Scholar, Scopus, Arxiv and Web of Science databases to identify studies published before January 2021 which used feature selection methods to derive PA clusters using unsupervised machine learning models.Results: A total of 13 studies were eligible for inclusion within the review. The most popular feature selection techniques were Principal Component Analysis (PCA) and correlation-based methods, with k-means frequently used in clustering accelerometer data. Cluster quality evaluation methods were diverse, including both external (e.g. cluster purity) or internal evaluation measures (silhouette score most frequently). Only four of the 13 studies had more than 25 participants and only four studies included two or more datasets.Conclusion: There is a need to assess multiple feature selection methods upon large cohort data consisting of multiple (3 or more) PA datasets. The cut-off criteria e.g. number of components, pairwise correlation value, explained variance ratio for PCA, etc. should be expressly stated along with any hyperparameters used in clustering. [ABSTRACT FROM AUTHOR]

Two behavioral change-based strategies for promoting adherence to physical activity (PA) suggested to have the greatest potential are the pedometer and Motivational Interviewing (MI). However, there are no comparisons between these two strategies identifying which one is more effective for improving PA adherence. This systematic review and meta-analysis aimed to determine which PA motivation strategy is more effective for promoting adherence to self-directed PA in female breast cancer survivors. Studies implementing self-directed PA which used a step tracker and/or MI for motivation in female breast cancer survivors were identified from the following databases at two timepoints, September 2019 and June 2020: CENTRAL, PubMed, CINAHL, PsycINFO, and Sportdiscuss. Sixteen randomized controlled trials (RCTs) were selected for data extraction, whereas ten RCTs were included in meta-analysis. Meta-analysis was performed on pooled data to estimate the standardized mean differences in PA duration and step count, and 95% confidence intervals. The number of participants meeting PA recommendations was also analyzed. Subgroup analysis was performed for three motivational strategies (pedometer combined with counselling, with print material or with motivational interviewing). Meta-analysis showed that pedometer combined with another intervention has a small effect on step count (p = 0.03) and a moderate effect on duration of moderate-vigorous physical activity (MVPA) (p = <0.0001) compared to controls. Additionally, motivational strategies increase the number of participants who meet a PA goal (p = 0.005). The findings of this review endorse the use of a step tracker combined with counselling, print material or MI based on behavioral change theory. This approach provided the most consistent positive effect on adherence to self-directed PA among breast cancer survivors. Future studies should evaluate differences between measures of adherence to self-directed PA, to identify the best motivation strategy for improving patient adherence and health outcomes. Systematic review registration: PROSPERO Registration number CRD42020148542. [ABSTRACT FROM AUTHOR]

In this study, a hybrid sol-gel method was used to fabricate Pb(Zr 0.52 Ti 0.48) 0.98 Nb 0.02 O 3 (PNZT) piezoelectric thick films. By preparing Pb(Zr 0.52 Ti 0.48) 0.98 Nb 0·02 O 3 sol-gel solutions and mixing them with PZT-5A piezoelectric powders, therefore, the thickness of single layer coating can be increased and reduce the risk of film cracks. The proposed PNZT films have the dielectric constant of 1750, dielectric loss of 0.063, remnant polarization of 58 μC/cm2, and d 33 of 133 p.m./V. Piezoelectric cantilever beam MEMS accelerometers were then designed, simulated and fabricated via photolithography methods on Si substrates. The sensitivity and natural frequency of the cantilever beam accelerometer are 16.8 mV/g and 200Hz, respectively. Finally, a cantilever beam accelerometer is successfully applied for the server hard-drive fault detection. [ABSTRACT FROM AUTHOR]

Background: Behavioral changes during adolescence are affected by biological and social aspects. However, environment aspects, which are beyond adolescents' control, also contribute to behavior adoption, and school may have a significant impact in these behaviors. This cross-sectional study aims to investigate how lifestyle behaviors are associated with the school shift attended by high school students.Methods: The sample comprised 635 high school students (51.2% girls, 16.33 ± 1.0 years old) from Southern Brazil. Physical activities of different intensities (light and moderate-to-vigorous), sedentary behaviors, and sleep (duration, efficiency, and timing) were measured using accelerometers. Engagement in sport and non-sport activities, screen time indicators, and diet were self-reported. Linear models were fitted to compare each lifestyle behavior between the two school shifts.Results: Students attending the afternoon shift slept (β = 01:29 95%CI 01:13; 01:46) and woke up later (β = 01.41 95%CI 01:27; 01:54), and had a longer sleep duration (β = 00:12 95%CI 0:02; 00:21) than those attending the morning shift. However, the sleep efficiency of those in the afternoon shift was lower than their peers in the morning shift (β = -1.89 95%CI -3.01; -0.77).Conclusions: School schedule was associated with sleep behaviors of adolescents, but not with other lifestyle behaviors. [ABSTRACT FROM AUTHOR]

Introduction: There is an ongoing digital revolution in the field of Parkinson's disease (PD) for the objective measurement of motor aspects, to be used in clinical trials and possibly support therapeutic choices. The focus of remote technologies is now also slowly shifting towards the broad but more "hidden" spectrum of non-motor symptoms (NMS).Methods: A narrative review of digital health technologies for measuring NMS in people with PD was conducted. These digital technologies were defined as assessment tools for NMS offered remotely in the form of a wearable, downloadable as a mobile app, or any other objective measurement of NMS in PD that did not require a hospital visit and could be performed remotely. Searches were performed using peer-reviewed literature indexed databases (MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane CENTRAL Register of Controlled Trials), as well as Google and Google Scholar.Results: Eighteen studies deploying digital health technology in PD were identified, for example for the measurement of sleep disorders, cognitive dysfunction and orthostatic hypotension. In addition, we describe promising developments in other conditions that could be translated for use in PD.Conclusion: Unlike motor symptoms, non-motor features of PD are difficult to measure directly using remote digital technologies. Nonetheless, it is currently possible to reliably measure several NMS and further digital technology developments are underway to offer further capture of often under-reported and under-recognised NMS. [ABSTRACT FROM AUTHOR]

• We focus on Continuous Authentication (CA) in IoT (particularly smart- phones) assisted by non-trusted servers. • We propose SmartCAMPP, a CA mechanism leveraging motion sensors which ensures users' privacy. • No previous CA work for smartphones has relied upon motion sensors considering privacy. • SmartCAMPP achieves 76.85% of accuracy while taking 5.12 ms of computation for authenticating a user. • As compared to non-privacy-preserving mechanisms, SmartCAMPP offers promising accuracy and affordable performance overhead. Continuous Authentication (CA) approaches are attracting attention due to the explosion of available sensors from IoT devices such as smartphones. However, a critical privacy concern arises when CA data is outsourced. Data from motion sensors may reveal users' private issues. Despite the need for CA in smartphones, no previous work has explored how to tackle this matter leveraging motion sensors in a privacy-preserving way. In this work, a mechanism dubbed SmartCAMPP is proposed to achieve CA based on gyroscope and accelerometer data. Format-preserving encryption techniques are applied to privately outsource them. Our results show the suitability of the proposed scheme, featuring 76.85 % of accuracy while taking 5.12 ms. of computation for authenticating each user. Interestingly, the use of cryptography does not lead to a significant impact as compared to a non-privacy-preserving mechanism. [ABSTRACT FROM AUTHOR]

We proposed a new primary calibration method of a laser Doppler vibrometer (LDV) using the optical modulated excitation of an electro-optical modulator and validated this approach by comparing mechanical modulated excitation with homodyne laser interferometer at the National Metrology Institute of Japan (NMIJ). The velocity sensitivity of the LDV was evaluated with the uncertainty budget at a high-frequency range up to 1 MHz, which is indicated as the upper limit of 50 kHz in ISO (International Organization for Standardization) 16063–41. As the results, we confirmed that velocity sensitivities between optical and mechanical modulated excitations are flat within their uncertainty from 100 Hz up to 1 MHz. Moreover, in order to evaluate the accurate phase shift of the accelerometer up to 20 kHz using optical modulated excitation, we also revealed the reliability of two time shifts between homodyne and heterodyne laser interferometers. • Evaluate frequency response of laser Doppler vibrometer up to MHz order using electro-optic modulator. • Present uncertainty budget of primary calibration of laser Doppler vibrometer. • Evaluate validity of time delay of laser interferometer using phase shift of accelerometer. • Present time delay of electro-optical modulator. • Present time delay dependence of cable on output impedance. [ABSTRACT FROM AUTHOR]