Type B Uncertainty Analysis of Gravity-Based Determinations of Triaxial-Accelerometer Properties by Simulation of Measurement Errors

We simulated the effects of gimbal-alignment errors and rotational step-size errors on measurements of the sensitivity matrix and intrinsic properties of a triaxial accelerometer. We restricted the study to measurements carried out on a two-axis calibration system using a previously described measurement and analysis protocol. As well as imperfections in the calibration system, we simulated imperfect orthogonality of the accelerometer axes and non-identical sensitivity of the individual accelerometers in an otherwise perfect triaxial accelerometer, but we left characterization of other accelerometer imperfections such as non-linearity for future study. Within this framework, sensitivity-matrix errors are caused by imperfections in the construction and installation of the accelerometer calibration system, but not by the accelerometer imperfections included in the simulations. We use the results of this study to assign type B uncertainties to the components of the sensitivity matrix and related intrinsic properties due to imperfections in the measurement system. For calibrations using a reasonably well manufactured and installed multi-axis rotation stage such as that studied in this paper, we estimated upper bounds to the standard uncertainties of the order of 1 ×10−5 , 2 ×10−5 , 2 ×10−4 , and 5 ×10−5 for the intrinsic sensitivities, diagonal elements of the sensitivity matrix, off-diagonal elements of the sensitivity matrix, and zero-acceleration offsets, relative to a sensitivity-matrix element of 1, respectively, and 5 ×10−3 degrees for the intrinsic angles

Does Cup-Grip Type Affect Tremor among People with Essential Tremor?

Essential tremor (ET) is a movement disorder that may cause functional disability in daily activities, such as drinking from a cup or drawing. This study aims to characterize effects of varied cup-grip types and measured axes on the actual performance of people with ET and find correlations between cup-grip type and measured axes, and spiral drawing measures. Participants (20 with ET and 18 controls) held a cup of water in a steady position in three grip types and drew a spiral. The cup acceleration was measured by the cup triaxial accelerometer, analyzed in X, Y and Z axes (directions); deviation of the measured acceleration from the desired steady position acceleration was computed. Significant group differences were found for outcome measures in all grip types. Among participants with ET, significantly higher measured values were found in the cup’s horizontal plane (X and Y axes) compared to the vertical direction (Z axis) and for on-the-handle versus around-the-cup grips in the X and Y axes. Significant correlations were found between this grip’s measures and spiral-drawing actual performance measures, indicating the measurement axis and grip type may affect actual performance. These findings may support the future development of assistive devices for tremor suppression and personalized supportive therapy.

What Are Sheep Doing? Tri-Axial Accelerometer Sensor Data Identify the Diel Activity Pattern of Ewe Lambs on Pasture

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

The Effect of Cleat Position on Running Using Acceleration-Derived Data in the Context of Triathlons

Appropriate cycling cleat adjustment could improve triathlon performance in both cycling and running. Prior recommendations regarding cleat adjustment have comprised aligning the first metatarsal head above the pedal spindle or somewhat forward. However, contemporary research has questioned this approach in triathlons due to the need to run immediately after cycling. Subsequently, moving the pedal cleat posteriorly could be more appropriate. This study evaluated the effectiveness of a triaxial accelerometer to determine acceleration magnitudes of the trunk in outdoor cycling in two different bicycle cleat positions and the consequential impact on trunk acceleration during running. Seven recreational triathletes performed a 20 km cycle and a 5 km run using their own triathlon bicycle complete with aerodynamic bars and gearing. Interpretation of data was evaluated based on cadence changes whilst triathletes cycled in an aerodynamic position in two cleat positions immediately followed by a self-paced overground run. The evaluation of accelerometer-derived data within a characteristic overground setting suggests a significant increase in total trunk acceleration magnitude during cycling with a posterior cleat with significant increases to longitudinal acceleration (p = 0.04) despite a small effect (d = 0.2) to the ratings of perceived exertion (RPE). Cycling with a posterior cleat significantly reduced longitudinal trunk acceleration in running and overall acceleration magnitudes (p < 0.0001) with a large effect size (d = 0.9) and a significant reduction in RPE (p = 0.02). In addition, running after cycling in a posterior cleat was faster compared to running after cycling in a standard cleat location. Practically, the magnitude of trunk acceleration during cycling in a posterior cleat position as well as running after posterior cleat cycling differed from that when cycling in the fore-aft position followed by running. Therefore, the notion that running varies after cycling is not merely an individual athlete’s perception, but a valid observation that can be modified when cleat position is altered. Training specifically with a posterior cleat in cycling might improve running performance when trunk accelerations are analysed.

OS10.5.A BrainWear: Longitudinal, objective assessment of physical activity in 42 HGG patients

BACKGROUND In patients with High Grade Glioma (HGG), QoL and physical function decline with progressive disease (PD). Objective assessment of physical functioning is challenging as patients spend most of their time away from the hospital. Wearable technology allows measurement of objective, continuous activity data in a non-obtrusive manner. BrainWear is a phase II feasibility study, collecting longitudinal physical activity (PA) data from patients with primary and secondary brain tumours. MATERIAL AND METHODS All agreed to wear an Axivity AX3 triaxial accelerometer and completed the EORTC QLQ C30 and BN20, the Montreal Cognitive Assessment (MoCA) and Multidimensional fatigue inventory (MFI) questionnaires. Accelerometers were changed at 14-day intervals, and PRO questionnaires completed at pre-specified study intervals. Age-sex matched controls were identified from the UK Biobank 7-day accelerometer study. Raw accelerometer data was processed using UK Biobank accelerometer software and inclusion of high-quality wear time selected as ≥72 hours of data in a 7-day data collection and data in each 1-hour period of a 24-hour cycle over multiple days. We analysed variation in activity by patient demographics and treatment days. The wilcoxin-signed rank test was used to compare participant activity between radiotherapy treatment days and non-treatment days, mixed effects models were used to evaluate longitudinal changes in activity and we used k-means clustering to characterise clusters of PA behaviours. RESULTS We have collected 3458 days of accelerometer data from 42 HGG patients with a median age of 59, 80% of which has been classified as high quality. Patients &gt;60 years spend more time doing moderate activity compared to those &lt;60 years (52 vs 33 minutes/day, p=0.012), and there are significant differences in mean vector magnitude (17.12 vs 16.85 mg, p=0.013) and walking (91 vs 72 minutes/day) between radiotherapy and non-radiotherapy days. In patients having a 6-week RT course, time spent in daily moderate activity falls 4-fold between week 1 and the second week after RT completion (70 minutes to 16 minutes/day). Comparing HGG patients to healthy controls shows a significant difference in time spent across all activities (p&lt;0.05). K-means clustering analysis shows three distinct clusters, with 87% of HGG patients falling into the very inactive or moderately active groups. CONCLUSION Digital remote health monitoring is feasible and acceptable with 80% of data classified as high-quality wear-time suggesting good patient adherence. Triaxial accelerometer data collection captures objective evidence of a significant reduction in moderate daily activity at the time of expected peak RT side-effects and patients walk almost 30% less on non-RT treatment days. HGG patients show significantly lower levels of activity compared to matched healthy controls.

Increased Rotatory Laxity after Anterolateral Ligament Lesion in Anterior Cruciate Ligament- (ACL-) Deficient Knees: A Cadaveric Study with Noninvasive Inertial Sensors

The anterolateral ligament (ALL) has been suggested as an important secondary knee restrain on the dynamic laxity in anterior cruciate ligament- (ACL-) deficient knees. Nevertheless, its kinematical contribution to the pivot-shift (PS) phenomenon has not been clearly and objectively defined, and noninvasive sensor technology could give a crucial contribution in this direction. The aim of the present study was to quantify in vitro the PS phenomenon in order to investigate the differences between an ACL-deficient knee and an ACL+ALL-deficient knee. Ten fresh-frozen paired human cadaveric knees ( n = 20 ) were included in this controlled laboratory study. Intact, ACL-deficient, and ACL+ALL-deficient knees were subjected to a manual PS test quantified by a noninvasive triaxial accelerometer (KiRA, OrthoKey). Kinematic data (i.e., posterior acceleration of the tibial lateral compartment) were recorded and compared among the three statuses. Pairwise Student’s t -test was used to compare the single groups ( p < 0.05 ). Intact knees, ACL-deficient knees, and ACL+ALL-deficient knees showed an acceleration of 5.3 ± 2.1 m/s2, 6.3 ± 2.3 m/s2, and 7.8 ± 2.1 m/s2, respectively. Combined sectioning of ACL and ALL resulted in a statistically significant acceleration increase compared to both the intact state ( p < 0.01 ) and the ACL-deficient state ( p < 0.01 ). The acceleration increase determined by isolated ACL resection compared to the intact state was not statistically significant ( p > 0.05 ). The ALL sectioning increased the rotatory laxity during the PS after ACL sectioning as measured through a user-friendly, noninvasive triaxial accelerometer.

A Novel Sleep Scoring Algorithm-Based Framework and Sleep Pattern Analysis Using Machine Learning Techniques

Maintaining the suited amount of sleep is considered the prime component for maintaining a proper and adequate health condition. Often it has been observed that people having sleep inconsistency tend to jeopardize the health and appeal to many physiological and psychological disorders. To overcome such difficulties, it is often required to keep a requisite note of the duration and quality of sleep that one is having. This work defines an algorithm that can be utilized in smart wearables or mobile phones to perceive the duration of sleep and also to classify a particular instance as slept or awake on the basis of data fetched from the triaxial accelerometer. A comparative analysis was performed based on the results obtained from some previously developed algorithms, rule-based models, and machine learning models, and it was observed that the algorithm developed in the work outperformed the previously developed algorithms. Moreover, the algorithm developed in the work will very much define the scoring of sleep of an individual for maintaining a proper health balance.

Relationship between disease activity level and physical activity in rheumatoid arthritis using a triaxial accelerometer and self-reported questionnaire

Objective This study evaluated the relationship between rheumatoid arthritis (RA) disease activity level and physical activity (PA) by using an accelerometer and self-reported questionnaire. Results The cross-sectional study was part of a cohort study designed to determine disease activity is associated with PA in RA patients. We classified patients with a Disease Activity Score 28-erythrocyte sedimentation rate (DAS28-ESR) of less than and higher than 3.2 into the low-disease-activity (LDA) group and moderate/high-disease-activity (MHDA) group, respectively. We measured the wear time, time of vigorous-intensity PA, moderate-intensity PA, light-intensity PA, and sedentary behavior per day using a triaxial accelerometer. 34 patients were included in the study. The accelerometer-measured moderate-to-vigorous PA (MVPA) was 17.2 min/day and 10.6 min/day in the LDA group and MHDA group (p < 0.05), respectively. There was no significant association between RA disease activity level and accelerometer-measured PA with adjustment for age and Functional Assessment of Chronic Illness Therapy-Fatigue score. There was no correlation between accelerometer-measured MVPA and self-reported MVPA in the MHDA group, but these factors were correlated in the LDA group (rs = 0.57, p < 0.05). In conclusion, no significant association was noted between RA disease activity level and accelerometer-measured PA.