Accelerometer Measurements Research Articles

Timing of physical activity, genetic predisposition, and incident depression: An accelerometer-based prospective cohort study.

There is a lack of prospective cohort studies exploring the associations between the timing of physical activity and incident depression. This study aimed to explore the associations and to investigate whether genetic predisposition of depression may modify the associations. The study using data from UK Biobank, included 76,218 participants. The data of total physical activity (TPA) and moderate-to-vigorous physical activity (MVPA) were collected by accelerometer measurements over 7 consecutive days. Cox proportional hazard models were performed to calculate the hazard ratio (HR) and 95 % confidence interval (CI). In total, compared to the midday-afternoon group, participants in the early morning group of TPA had a lower risk of depression (HR: 0.76, 95 % CI: 0.65-0.89). Compared to the inactive group, a lower risk of incident depression was found among the participants with MVPA in the morning (HR: 0.80, 95 % CI: 0.67-0.96) and middy-afternoon (HR: 0.82, 95 % CI: 0.70-0.96). The joint effect analysis of the timing of TPA and genetic predisposition for incident depression showed that compared to the participants with a high genetic predisposition and in the middy-afternoon group of TPA, early morning group had a reduced risk of depression regardless of genetic predisposition. However, in subgroup analyses for genetic predisposition, only participants with a high genetic predisposition to depression benefited from TPA in the early morning. TPA in the early morning and MVPA in the morning and middy-afternoon were significantly associated with a lower depression risk, especially for participants with a higher genetic predisposition of depression.

Unknown input uncertainty calculation using virtual input shaping and interval analysis

A triaxial accelerometer has been developed to measure and determine the uncertainty associated with unknown vibrations disturbing a small force metrology experiment. However, methodological shortcomings remain regarding the calculation of uncertainty for dynamic measurements. Therefore, this paper proposes an alternative framework to estimate the uncertainty of specific dynamic quantities of interest with a nonlinear and uncertain measuring system. The novelty of the proposed methodology lies in the use of an accurate and equivalent representation of the physical system based on a linear model, combined with an additive virtual input describing all the unknown unmodeled dynamics. Measurement models are defined considering measurement biases, and uncertainty is calculated using interval analysis tools. Such tools allow determining the feasible values of the quantities of interest to be estimated. The innovative aspects of the proposed approach are fully illustrated in simulation on the triaxial accelerometer, comparing linear and nonlinear measurement models in passive mode.

Retrospective observational study shows accelerometers can monitor effects of canine pruritus treatment.

To evaluate the use of collar-mounted accelerometers to objectively monitor treatment outcomes in canine pruritus. Observational data from 1,803 dogs from 2019 through 2023 were retrospectively analyzed to evaluate the efficacy of collar-mounted accelerometers to assess treatment efficacy for pruritic canine skin diseases. Accelerometer measurements were joined to electronic health records to establish symptoms, diagnoses, and interventions. A directed acyclic graph was used to identify relevant variables to control for, and linear regression was used to model the pruritic behaviors before and after intervention. Significant reductions in pruritic behaviors, particularly scratching and licking, were observed following interventions. Antibody and immunosuppressant treatments exhibited the most pronounced effects on scratching behavior, with a reduction in scratching of up to 40.9% and 23.4%, retrospectively, in the 30 days following intervention relative to the 14 days prior. Collar-mounted accelerometers used to measure pruritic behaviors can detect the effects of interventions for canine pruritus. Pruritus is a common symptom of canine skin diseases, such as atopic dermatitis or allergic dermatitis, which can be difficult to diagnose and manage. This study highlights the use of collar-mounted accelerometers to objectively monitor treatment outcomes for canine pruritus, providing valuable insights into treatment effectiveness that could allow veterinarians and pet owners to optimize management strategies to alleviate the burden of this challenging condition.

Exploring Agreement in Voice Acoustic Parameters: A Repeated Measures Case Study Across Varied Recording Instruments, Speech Samples, and Daily Timeframes

Aims: The aim was to assess the agreement between microphone-derived and neck accelerometer-derived voice acoustic parameters and their associations with recording moments and speech types. Methods: Using simultaneous recordings, a 7-week study on a single individual was conducted to reduce intersubject variability. Agreement was assessed using Bland–Altman plots, and associations were examined with generalized estimating equations. Results: Bland–Altman plots showed no significant bias between microphone (MIC) and accelerometer (ACC) measurements for alpha ratio, CPP, PPE, SPL SD, fundamental frequency (fo) mean, and SD. Speech type and measurement timing were significantly associated with alpha ratio, while the instrument was not. Microphone measurements resulted in slightly lower CPP compared to the accelerometer, while reading samples yielded higher CPP compared to vowel productions. PPE, SPL SD, and fo mean showed significant associations with speech type, based on univariate analysis. Microphone measurements yielded a statistically smaller fo SD compared to the accelerometer, while reading productions had a larger fo SD than vowel productions. Conclusions: Fundamental frequency, alpha ratio, PPE, and SPL SD values were robust, regardless of the instrument used, suggesting the potential use of accelerometers in less-controlled environments. These findings are crucial for enhancing confidence in voice metrics and exploring efficient clinical assessment protocols.

Dynamic displacement measurement of a wind turbine tower using accelerometers: tilt error compensation and validation

Abstract. For vibration-based structural health monitoring (SHM) of wind turbine support structures, accelerometers are often used. Besides the structural acceleration, the measured quantity also contains the acceleration component due to gravity, which is known as tilt error. This tilt error must be quantified and taken into account; otherwise it can lead to incorrect evaluations, especially in the fatigue estimation or the dynamic displacement estimation using accelerometers. The standard solution is to explicitly measure the tilt angle, which requires an additional sensor for each measurement point and is not applicable for already recorded measurements without tilt information. Therefore, a novel tilt error compensation method is presented by using the static bending line. As a result the influence of the tilt error can be estimated in advance, and no additional sensors for tilt measurement are needed. The compensation method is applied to accelerometer measurements of an onshore wind turbine tower and validated with contactless absolute distance measurements from a terrestrial laser scanning (TLS) system. The position and frequency-dependent tilt error of the investigated tower has a significant influence on the quasi-static motion below 0.2 Hz with a minimum amplitude error of 9 %, whereas the normalised bending mode shapes around 0.3 Hz are only slightly affected.

Optimal dose and pattern of physical activity to prevent diagnosed depression: prospective cohort study.

Little is known about the dose and pattern of moderate-to-vigorous physical activity (MVPA) to prevent depression. We aimed to assess the prospective association of dose and pattern of accelerometer-derived MVPA with the risk of diagnosed depression. We included 74,715 adults aged 40-69 years from the UK Biobank cohort who were free of severe disease at baseline and participated in accelerometer measurements (mean age 55.2 years [SD 7.8]; 58% women). MVPA at baseline was derived through 1-week wrist-worn accelerometry. Diagnosed depression was defined by hospitalization with ICD-10 codes F32.0-F32.A. Restricted cubic splines and Cox regression determined the prospective association of dose and pattern of MVPA with the risk of incident depression. Over a median 7.9-year follow-up, there were 3,089 (4.1%) incident cases of depression. Higher doses of MVPA were curvilinearly associated with lower depression risk, with the largest minute-per-minute added benefits occurring between 5 (HR 0.99 [95% CI 0.96-0.99]) and 280 (HR 0.67 [95% CI 0.60-0.74]) minutes per week (reference: 0 MVPA minutes). Regardless of pattern, higher doses of MVPA were associated with lower depression risk in a curvilinear manner, with the greatest incremental benefit per minute occurring during the first 4-5 h per week. Optimal benefits occurred around 15 h/week.

PHYSICAL ACTIVITY AND SERUM BIOMARKERS IN OLDER WOMEN WITH CARDIOVASCULAR DISEASE EXPERIENCING FATIGUE

Abstract Fatigue is a common symptom of cardiovascular disease (CVD) and can be an early indicator of frailty. Physical activity (PA) can improve fatigue and frailty-related serum biomarkers: brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor-A (VEGF A), and insulin-like growth factor-1 (IGF-1). However, variation in PA and serum biomarkers among patients with CVD who are experiencing fatigue is understudied. We aimed to investigate (a) differences in PA and serum biomarkers in women with CVD experiencing fatigue and (b) the influence of PA on fatigue. We used cross-sectional, baseline data from older women (≥ 65 years, N=253) with CVD participating in the MindMoves trial (NCT04556305). PA included ActiGraph accelerometer measures of sedentary behavior, light PA, moderate-to-vigorous PA, and daily step count, and cardiorespiratory fitness. Serum biomarkers included BDNF, VEGF-A, and IGF-1. Fatigue was assessed using two items from the Center for Epidemiologic Studies-Depression Scale. Two-sample t-tests examined differences in PA and biomarkers across subgroups with and without fatigue. Logistic regression was used to examine associations between significant PA variables and fatigue. Fatigue was prevalent in 17% of participants. There were significantly fewer daily minutes of MVPA (p=0.0005) and lower daily step count (p=0.0142) in those experiencing fatigue. No significant differences were observed in serum biomarkers. After adjusting for sociodemographic characteristics, no PA variable was associated with fatigue. Women with CVD who experience fatigue had lower engagement in PA. Future research is needed to investigate fitness measures (e.g., strength) and other biomarkers to understand underlying physiological processes influencing PA in fatigue.

АЛГОРИТМ ФІЛЬТРАЦІЇ ВИМІРЮВАНЬ АКСЕЛЕРОМЕТРИЧНИХ ДАТЧИКІВ У БЕЗПЛАТФОРМЕНИХ ІНЕРЦІАЛЬНИХ СИСТЕМАХ НАВІГАЦІЇ БЕЗПІЛОТНИХ ЛІТАЛЬНИХ АПАРАТІВ

In unmanned aerial vehicles of low mass, platformless inertial navigation systems are widely used. They are implemented on the basis of accelerometers and gyroscopes, which are made according to the technology of microelectromechanical systems. The low accuracy of microelectromechanical systems determines the use of additional stages of navigation measurement processing in navigation systems. To increase the accuracy of navigation determinations, stochastic filtering algorithms are used, namely the Kalman filter and its various modifications. Existing filtering algorithms are characterized by high computational complexity due to the abstract form of presentation, which does not reflect the details of implementation. That is why the task of synthesizing filtering algorithms that will meet the requirements of guaranteed convergence of the filtering process and minimal computational complexity regarding its implementation is relevant. This requirement is extremely important for navigation systems of small unmanned aerial vehicles, as their on-board equipment must be cheap and low-energy. The work is devoted to the synthesis and research of the algorithm of polynomial filtering of measurements of accelerometric sensors in platformless inertial navigation systems of unmanned aerial vehicles. The synthesis of the algorithm is performed according to the method based on the presentation of smoothing filters as dynamic systems described by discrete transfer functions, which are determined by the application of the third form of invariance conditions. A distinctive feature of the synthesized algorithm is the consideration in the filtering process of not only current, but also previous measurement results, which are weighted by their own smoothing coefficients. The conditions for the convergence of the filtering process are defined for the synthesized algorithm. Due to the scalar form of the algorithm implementation, low computational complexity is inherent. The effectiveness of the algorithm was confirmed by the results of computer simulation based on the results of real measurements of the ADXL345 accelerometer, which is part of the Arduino UNO R3.

Associations of adiposity and device-measured physical activity with cancer incidence: UK Biobank prospective cohort study.

High adiposity and low physical activity are associated with cancer risk. Whether different amounts and intensities of physical activity can mitigate this association is unclear. We aimed to examine the independent and combined associations of adiposity and device-measured physical activity levels of different intensities with cancer incidence and mortality. This prospective cohort study included data from 70,747 UK Biobank participants (mean age 61.6 ± 7.9 years, 56.4% women) with wrist-worn accelerometer measurements of physical activity and without chronic diseases or mobility limitations. Physical activity exposures included min per week of light (LPA), moderate-to-vigorous (MVPA), and vigorous (VPA) intensity physical activity, along with total weekly volume. Body mass index (BMI) was calculated from anthropometric measurements. Participants were categorized into 9 groups based on joint tertiles of physical activity and BMI categories (normal weight, overweight, and obesity). Secondary analyses included adiposity using bio-impedance and waist circumference measurements. The outcome was incidence and death from cancer retrieved from national registries. Associations between adiposity, physical activity, and cancer hazard were calculated as subdistribution hazard ratios. A secondary analysis focused on cancer types strongly associated with physical activity. We observed 2625 events (2572 non-fatal and 53 fatal) during a median follow-up of 6.1 years. Compared with the referent (normal weight and high physical activity), overweight and obesity were associated with a 6% to 36% higher cancer hazard across physical activity intensities. However, high MVPA and VPA (approximately 500 min and 32 min per week in the top tertiles, respectively) attenuated the hazard associated with overweight and obesity. Being normal weight was not associated with a higher cancer hazard regardless of physical activity level. The results were similar, although more pronounced, when modeling cancer types strongly associated with physical activity as the outcome. High MVPA and VPA levels may attenuate the association of overweight and obesity with cancer hazard, but maintaining a normal weight seems comparatively more important than physical activity to reduce the hazard. Maintaining a healthy body weight and engaging in physical activity is needed to minimize risk of some cancer types.

Physical Activity, Sedentary Behaviour, and Cardiovascular Disease Risk Factors in Canadians Living With and Without Cardiovascular Disease.

Our aim in this study was to describe and compare the proportion of adult Canadians living with and without cardiovascular disease (CVD) and meeting the physical activity (PA) and sedentary behaviour (SB) recommendations of the Canadian 24-Hour Movement Guidelines using accelerometer and self-reported measures. Using adult (18-79 years of age) accelerometer data (Actical, worn during waking hours for 7 consecutive days) as well as chronic condition, sociodemographic, recreational screen time, and PA questions from 3 combined cycles of the Canadian Health Measures Survey, we compared the PA, SB, and CVD risk factors of adults living with and without CVD. A total of 7035 Canadian adults who reported living with (n= 363) and without (n= 6672) CVD were included. Few adults living with CVD were meeting the PA (29%) and SB (15%) recommendations. CVD status was not significantly associated with the likelihood of meeting the PA or screen time recommendations, but adults living with CVD had a lower likelihood of meeting the sedentary time recommendation when compared with adults without CVD (adjusted odds ratio= 0.49; 95% confidence interval, 0.30-0.82). Adults, primarily men, living with rather than without CVD engaged in less light- and moderate-intensity PA. The PA and SB of Canadian adults living with and without CVD are significantly different. Adults living with CVD had a lower likelihood of meeting the sedentary time recommendation, and adults living with CVD, primarily men, engaged in less light- and moderate-intensity PA. The identification of these movement behaviour targets may assist in allocating resources to sedentary individuals with the greatest need of PA.

Effectiveness and Durability of a Workplace Sedentary Behavior Intervention Based on the Total Worker Health® Approach.

We used the Total Worker Health® approach to develop a multi-component workplace sedentary behavior intervention and tested intervention effectiveness in a cluster randomized trial. Participants (n = 198; 75% female) were recruited from three call-centers (two intervention and one usual practice control). All worksites received pedal stand active workstations. The usual practice site received no additional support, while the intervention group completed a six-month program of activities including computer-based training, behavioral self-monitoring, health and safety discussions, and pedaling competitions. Data collection included a survey, a physical health assessment, and accelerometer measures of sedentary behavior, physical activity, and sitting/standing time. Primary analyses were generalized estimating equations comparing changes between intervention and usual practice conditions over time, along with analyses of changes in both groups combined over time. Six-month results revealed less prolonged sitting and reductions in musculoskeletal pain in both groups (all p < 0.05), while the intervention group showed additional improvements in moderate physical activity (p < 0.001) and use of pedal stands (p < 0.01). At 12-months, the additional physical activity and pedal stand use in the intervention group regressed to baseline levels, while reductions in prolonged sitting in both groups were durable (p < 0.01). This study adds to previous research showing the effectiveness of the Total Worker Health® approach for workplace health and safety. Results also show that, while providing employees with health and safety resources is beneficial, providing ongoing support for the adoption and use of resources is more effective.

Wearable accelerometer-derived measures of physical activity in heart failure: insights from the DETERMINE trials

IntroductionWearable accelerometers allow continuous assessment of physical activity during normal living conditions and may be useful in evaluating the effects of treatment for heart failure. We explored the relationships between accelerometer measures of physical activity and 6-minute walk distance and patient-reported measures of functional limitation in participants across the entire left ventricular ejection fraction spectrum in the DETERMINE trials. MethodsA subgroup of patients in the DETERMINE trials wore a waist-based accelerometer during 7-day periods at 3 points during the trial; between screening and randomization, and weeks 8 and 14. Patients completed the Kansas City Cardiomyopathy Questionnaire (KCCQ) and 6-minute walk distance (6MWD) at baseline and weeks 8 and 16. ResultsOf the 817 patients randomized, 319 (39%) had adequate baseline accelerometer data. Patients with lower levels of physical activity had lower (i.e. worse) KCCQ scores and 6MWD, higher NT-proBNP levels and BMI, worse kidney function, and more diabetes and atrial fibrillation. Baseline accelerometer values had weak correlations with KCCQ summary scores (Pearson r=0.06 to 0.21) and weak to moderate correlations with 6MWD (Pearson r=0.20 to 0.31). The change from baseline to 16 weeks in accelerometer-measured physical activity correlated weakly with the change in KCCQ summary scores (Pearson r=0 to 0.18) and 6MWD (r=0.01 to 0.10). ConclusionsIn the DETERMINE trials, accelerometer-based measures of physical activity correlated modestly with KCCQ summary scores and 6MWD. Accelerometer-based assessments of physical activity may provide additional information complementing that obtained from standard measures of functional limitation in patients with heart failure.

Longitudinal Changes in Adolescents’ Sedentary, Light, Moderate and Vigorous Physical Activity Levels

Background and purpose: In recent years, sedentary behaviour (SB) has become a significant risk factor for health, alongside the decline of physical activity (PA) in the population. This study explored adolescents’ PA and SB using a longitudinal design, from the age of 13 to 15, to elucidate any changes and when they potentially occur. Method: The data material from the accelerometer measurements was analysed using the program SPSS, version 28. Repeated measures ANOVA (and follow-up test with Bonferroni corrections) were used to assess changes in the four activity levels during the three years. Independent t-tests were used to examine gender differences in each year and at each activity level and to determine differences in activity level between participants with valid data for all three years and those with valid data only at 13 and/or 14 years of age. Results: Statistical analyses of the accelerometer measurements revealed a significant increase in time in the lowest activity level and a decrease in light, moderate and vigorous intensity PA levels during the three years. These changes were larger from 13 to 14, than from 14 to 15, years of age. However, no significant interaction was found between time and gender. Analyses also showed a significantly higher time spent in SB and lower time spent in moderate activity among girls compared to boys at 13, but not at the age of 14 and 15. Conclusions: The findings, which indicate a reduction in PA and increased sedentary time with increasing age, are discussed, which we argue are important to increase and solidify involvement in PA among adolescents. Emphasized here is the importance of communicating the diverse possibilities of movement and challenging understandings of what PA can be for youth.

Does growing up in a physical activity-friendly neighborhood increase the likelihood of remaining active during adolescence and early adulthood?

BackgroundThe SOPHYA-cohort-study investigated whether the objectively characterized and perceived residential neighborhood of Swiss youth predict accelerometer-measured physical activity and activity in specific domains (participation in a sports club and cycling) five years later.MethodsAt baseline in 2014, 1230 children and adolescents aged 6 to 16 years participated and wore accelerometers for 7 days. Of these children, 447 participated again in the follow-up study in 2019 and provided longitudinal accelerometer measurements. Sociodemographic factors and perceptions of the local neighbourhood were assessed by questionnaire. Specific objective environmental data (e.g. built environment or social environment) was modelled to the children’s address at baseline. Multivariate linear and logistic regression models were applied to identify short- and long-term characteristics that are associated with accelerometer-based physical activity, cycling and participation in organised sport.ResultsIf the neighborhood-score as perceived by the parents in 2014 was in the middle or lowest tertile, children were significantly less active cross-sectionally in 2014 (-41.1 (-78.0;-4.2) and -52.4 (-88.6;-16.2) counts per minute, cpm), and five years later (-52.4 (-88.6;-16.2) and 48.1 (-86.6;-9.7) cpm). In addition, they were also less likely to accumulate active minutes above the median at both measuring points compared to peers of the same age and sex. Using objective environmental data modeled around the children’s residential address, similar associations were found: In the tertile with the lowest proportion of green space children achieved less cpm in 2014, while a high main street density and a low socioeconomic environment, respectively, hindered physical activity tracking above the median longitudinally. Also for cycling and participation in a sport club, the associations with the perceived and objective environment were more pronounced in the longitudinal analyses.ConclusionThe results suggest that growing up in a physical activity friendly neighborhood increases the likelihood of remaining active during adolescence and early adulthood. Interventions should be implemented to ensure that children growing up in an unfavorable neighborhood do not fall behind at an early stage.

Diurnal patterns of accelerometer-measured physical activity and sleep and risk of all-cause mortality: a follow-up of the National Health and Nutrition Examination Surveys (NHANES)

BackgroundPhysical activity and sleep are established modifiable lifestyle factors, but the optimal time of the day of these behaviours for health is unknown. This study examined the independent and joint associations of diurnal patterns of physical activity and sleep with all-cause mortality.MethodsThis prospective cohort study included 6,673 participants who have attended the accelerometer assessment in the 2011–2014 National Health and Nutrition Examination Surveys (NHANES). Diurnal patterns of accelerometer-measured physical activity and sleep were identified using K-means clustering analysis. All-cause mortality was ascertained from the accelerometer measurement to December 31, 2019 (median follow-up 6.8 years). Survey-weighted Cox proportional hazard models were performed to estimate the independent and joint associations of diurnal patterns of physical activity and sleep with all-cause mortality.ResultsDiurnal patterns identified were: early-morning (32.4%), midday (42.5%), and late-afternoon (25.1%) for physical activity; and irregular sleep (37.4%), morning lark (33.6%), and night owl (29.0%) for sleep. After adjusting for volume of physical activity, sleep duration and other potential covariates, the early-morning physical activity pattern (hazard ratio 1.36, 95% confidence interval 1.13–1.64) and irregular sleep pattern (1.42, 1.01–1.99) were independently associated with higher risk of all-cause mortality, compared with midday physical activity and morning lark sleep patterns, respectively. In addition, participants with the combined pattern of early-morning physical activity and irregular sleep had higher risk of all-cause mortality compared to those with midday physical activity combined with a morning lark sleep pattern (1.92, 1.33–2.78). Several sociodemographic differences were observed in the strength of these associations.ConclusionsWearable activity-rest monitoring data showed that peak physical activity in the early morning and irregular sleep diurnal patterns are associated with increased mortality risk, and the combination of these patterns further exaggerated the risk. Public health program should acknowledge that the diurnal patterns of physical activity and sleep, in addition to their duration and frequency, may play a crucial role in lifestyle-based health promotion and management strategies.

Comparative Analysis of Machine Learning Techniques for Identifying Multiple Force Systems from Accelerometer Measurements.

The knowledge of the forces acting on a structure enables, among many other factors, assessments of whether the component's useful life is compromised by the current machine condition. In many cases, a direct measurement of those forces becomes unfeasible, and an inverse problem must be solved. Among the solutions developed, machine learning techniques have stood out as powerful predictive tools increasingly applied to engineering problem-solving. This study evaluates the ability of different machine learning models to identify parameters of multi-force systems from accelerometer measurements. The models were assessed according to their prediction potential based on correlation coefficient (R2), mean relative error (MRE), and processing time. A computational numerical model using the finite element method was generated and validated by vibration measurements performed using accelerometers in the laboratory. A robust database created by the response surface methodology in conjunction with Design of Experiment (DOE) was used for the evaluation of the ability of machine learning models to predict the position, frequency, magnitude, and number of forces acting on a structure. Among the six machine learning models evaluated, k-NN was able to predict with a 0.013% error, and Random Forests showed a maximum error of 0.2%. The innovation of this study lies in the application of the proposed method for identifying parameters of multi-force systems.

Influence of physical activity measurement on the association between Life’s Essential 8 and incident cardiovascular disease in older women

ObjectiveThe American Heart Association’s Life’s Essential 8 (LE8) metric includes self-reported physical activity as one of the metrics for assessing cardiovascular health. Self-reported physical activity is prone to misclassification, whereas accelerometer measures are less biased. We examined associations of LE8 and incident cardiovascular disease (CVD) using self-reported and accelerometer-measured physical activity. MethodsParticipants in the Women’s Health Initiative (WHI) Objective Physical Activity and Cardiovascular Health Study (n = 4,243; mean age = 79 ± 7 years) with no CVD history completed the WHI physical activity questionnaire and the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire prior to wearing a hip-worn accelerometer for up to seven days in 2012–2014. LE8 components (physical activity, diet, sleep, body mass index, smoking, blood pressure, non-HDL cholesterol, and glucose) were scored according to guidelines. Scores were created using five physical activity measures: WHI questionnaire (LE8WHI), CHAMPS (LE8CHAMPS), accelerometer-measured physical activity (LE8A), and sample quantiles of accelerometer-measured physical activity (LE8AQ) and daily steps (LE8STEPS). Hazard ratios (HR) for physician-adjudicated CVD were estimated using Cox regression. Results707 incident CVD events occurred over an average 7.5 years. Multivariable HRs (95 % CI) comparing women in the highest vs. lowest quartiles of LE8 scores were: LE8WHI = 0.53 (0.43–0.67), LE8CHAMPS = 0.47 (0.38–0.60), LE8A = 0.44 (0.36–0.56), LE8AQ = 0.44 (0.35–0.55), and LE8STEPS = 0.45 (0.35–0.57). ConclusionsThe LE8-incident CVD association varies by physical activity measurement, however all methods showed reduced risk. Device-measures of physical activity may be more accurate in the LE8, but when impractical to implement, also support use of self-reported measures.

Impact of metro vibrations on people: critical aspects of designing vibration mitigation interventions

A methodology for assessing and mitigating the impact of metro infrastructure generated vibration and ground-borne noise on people is described. This methodology combines techniques for analyzing vibration measurements and predictive modeling to identify effective mitigation interventions. These interventions require working on existing railway track systems and involve interruption of service, unlike noise mitigation interventions that can be implemented without interfering with rail and road infrastructure. For this reason, it is important to identify the most effective mitigation techniques to minimize the impact on the population and simplify on-site implementation. The methodology was applied in Milan metro lines where the vibration level was estimated, and a vibration mitigation system was designed. The vibration phenomenon was quantified through accelerometric measurements taken in several buildings affected by the disturbance from vibration. The measured vibration levels were compared with reference level established by standards. The maximum difference obtained from this comparison was used as input data for the design of the mitigation intervention. The vibration mitigation interventions involve increasing the total mass and elasticity of the existing system. Their effectiveness was verified through numerical calculation using parametric software confirming the required amount of mitigation.

Optical interferometry implementation considerations for sinusoidal low frequency accelerometer measurements and calibrations

Vibration metrology utilizing sine excitation stimulus, based either on fringe counting or minimum point methods, employs Michelson interferometers for the calibration of accelerometers. The former method combines the optical reference and measurements arms from a static mirror and reflected by the accelerometer respectively which are then directed to a suitable photodiode for processing. The stroking motion due to the oscillation of the accelerometer will contribute to the misalignment of the two optical paths and there are three methods to compensate for this. The first requires the mounting of a mirror on the accelerometer itself and the effect of the added mass from the mirror can be accounted for and corrected. The second requires the mounting of three mirrors on the mounting surface of the accelerometer but this requires the alignment of the Michelson interferometer for each mirror. The third is to use two retro reflectors so that the returning measurement beams are always along the same path with the reference; however, this requires the alignment of the interferometer for each retro-reflector. This paper will discuss such considerations on the optical systems, their components and associated instrumentation and discuss the design of an alternative approach that can overcome certain limitations.

Finite element analysis for the measurement error of electrostatic accelerometer due to the electrode misalignment

Abstract The electrostatic accelerometer is the key payload of many space missions, such as satellite gravity measurements, space gravitational experiments, with a typical precision requirement from nano-g to femto-g. The measurement error model analysis is an important issue for the electrostatic accelerometer with numerous error sources. The traditional method by theoretical analysis is complicated to evaluate the complete measurement error models quantitatively especially when the machining and assembly errors of the sensor head are considered. Limited by the earth gravity and seismic noise which is much higher than the intrinsic noise, the complete error model of electrostatic accelerometers can also hardly be tested on ground. In this paper, the method by using finite element analysis of the sensor head is studied. The simulation model for an electrostatic accelerometer sensor head is built, and the multi-conductor capacitance matrix data is simulated. The accuracy of the capacitance simulation is evaluated in three ways including the convergence check of the capacitance with the mesh size, the symmetry verification, and the sensitivity comparison with the theoretical model. Finally, the accelerometer measurement model is analyzed based on the simulation data, using the case of rotating installation misalignment of the upper electrode as an example. The measurement model and error items of one horizontal axis and one rotating axis are quantitatively evaluated. The method proposed in this paper provide a new effective approach to the measurement model analysis of the electrostatic accelerometers in complex working scenarios both in orbit and on ground, which could be helpful to enhance the performance and the efficiency of application.