Dataset Information

Day-to-Day Variability and Year-to-Year Reproducibility of Accelerometer-Measured Free-Living Sit-to-Stand Transitions Volume and Intensity among Community-Dwelling Older Adults.

ABSTRACT: (1) Background: The purpose of this study was to evaluate the day-to-day variability and year-to-year reproducibility of an accelerometer-based algorithm for sit-to-stand (STS) transitions in a free-living environment among community-dwelling older adults. (2) Methods: Free-living thigh-worn accelerometry was recorded for three to seven days in 86 (women n = 55) community-dwelling older adults, on two occasions separated by one year, to evaluate the long-term consistency of free-living behavior. (3) Results: Year-to-year intraclass correlation coefficients (ICC) for the number of STS transitions were 0.79 (95% confidence interval, 0.70-0.86, p < 0.001), for mean angular velocity-0.81 (95% ci, 0.72-0.87, p < 0.001), and maximal angular velocity-0.73 (95% ci, 0.61-0.82, p < 0.001), respectively. Day-to-day ICCs were 0.63-0.72 for number of STS transitions (95% ci, 0.49-0.81, p < 0.001) and for mean angular velocity-0.75-0.80 (95% ci, 0.64-0.87, p < 0.001). Minimum detectable change (MDC) was 20.1 transitions/day for volume, 9.7°/s for mean intensity, and 31.7°/s for maximal intensity. (4) Conclusions: The volume and intensity of STS transitions monitored by a thigh-worn accelerometer and a sit-to-stand transitions algorithm are reproducible from day to day and year to year. The accelerometer can be used to reliably study STS transitions in free-living environments, which could add value to identifying individuals at increased risk for functional disability.

SUBMITTER: Lopponen A

PROVIDER: S-EPMC8471908 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The sit-to-stand test is commonly used by clinicians and researchers to analyze the functional capacity of older adults. The test consists to stand up and sit down from a chair and can be applied either in function of a predetermined number of repetitions to be completed or according to a specific time. The most common tool used by the evaluators is the chronometer, due to its low cost and ease of use. However, this tool may miss some important data throughout the test, such as the stand-up time and the total time of each repetition, as well as other kinematic and kinetic variables. Therefore, it is necessary to develop new cheap and affordable tools to capture these data with reliability. In this perspective, the development of mobile applications can be a valid and reliable alternative for the automatic calculation of different variables with sensors' data, including acceleration, velocity, force, power, and others. Thus, in this paper, we present a dataset related to the acquisition of the accelerometer data from a commodity smartphone for the measurement of different variables during the sit-to-stand test with institutionalized older adults. Forty participants (20 men and 20 women, 78.9 ± 8.6 years old, 71.7 ± 15.0 kg, 1.57 ± 0.1 m) from five community-dwelling centers (Centro de Dia e Apoio Domiciliário de Alcongosta, Lar Nossa Senhora de Fátima, Centro Comunitário das Minas da Panasqueira, Lar da Misericórdia, and Lar da Aldeia de Joanes) from Fundão, in Portugal, volunteered to participate in the data acquisition. A mobile phone was attached to the waist of the participants to capture the data during the sit-to-stand test. Then, seated in an armless chair with the arms crossed over the chest, the participants stood up and sat down in a chair six times. The stand-up action was ordered by an acoustic signal emitted by the mobile application. All data were acquired with the mobile application, and the outcome measures were the reaction time, total time, stand-up time and movement time. This paper describes the procedures to acquire the data. These data can be reused for testing machine learning or other methods for the evaluation of neuromuscular function in older adults during the sit-to-stand test.

Project description:PurposeThe aim was to use accelerometer data to describe day-to-day variability in physical activity in a single week, according to sociodemographic variables, in mid-aged Australian adults.MethodsData were from participants in the How Areas in Brisbane Influence HealTh and AcTivity (HABITAT) study who took part in a 2014 sub-study (N = 612; Mean age 60.6 [SD 6.9; range 48-73]). Participants wore a triaxial accelerometer (ActiGraph wGT3X-BT) on their non-dominant wrist for seven days, and data were expressed as acceleration in gravitational equivalent units (1 mg = 0.001 g). These were, used to estimate daily acceleration (during waking hours) and daily time spent in moderate-vigorous physical activity (MVPA, defined as ≥ 100mg). Coefficient of variation (calculated as [standard deviation/mean of acceleration and MVPA across the seven measurement days] * 100%) was used to describe day-to-day variability.ResultsAverage values for both acceleration (24.1-24.8 mg/day) and MVPA (75.9-79.7 mins/day) were consistent across days of the week, suggesting little day-to-day variability (at the group level). However, over seven days, average individual day-to-day variability in acceleration was 18.8% (SD 9.3%; range 3.4-87.7%) and in MVPA was 35.4% (SD 15.6%; range 7.3-124.6%), indicating considerable day-to-day variability in some participants. While blue collar workers had the highest average acceleration (28.6 mg/day) and MVPA (102.5 mins/day), their day-to-day variability was low (18.3% for acceleration and 31.9% for MVPA). In contrast, variability in acceleration was highest in men, those in professional occupations and those with high income; and variability in MVPA was higher in men than in women.ConclusionResults show group-level estimates of average acceleration and MVPA in a single week conceal considerable day-to-day variation in how mid-age Australians accumulate their acceleration and MVPA on a daily basis. Overall, there was no clear relationship between overall volume of activity and variability. Future studies with larger sample sizes and longitudinal data are needed to build on the findings from this study and increase the generalisability of these findings to other population groups.

Project description:Introduction: Inertial sensors generate objective and sensitive metrics of movement disability that may indicate fall risk in many clinical conditions including multiple sclerosis (MS). The Timed-Up-And-Go (TUG) task is used to assess patient mobility because it incorporates clinically-relevant submovements during standing. Most sensor-based TUG research has focused on the placement of sensors at the spine, hip or ankles; an examination of thigh activity in TUG in multiple sclerosis is wanting. Methods: We used validated sensors (x-IMU by x-io) to derive transparent metrics for the sit-to-stand (SI-ST) transition and the stand-to-sit (ST-SI) transition of TUG, and compared effect sizes for metrics from inertial sensors on the thighs to effect sizes for metrics from a sensor placed at the L3 level of the lumbar spine. Twenty-three healthy volunteers were compared to 17 ambulatory persons with MS (PwMS, HAI ? 2). Results: During the SI-ST transition, the metric with the largest effect size comparing healthy volunteers to PwMS was the Area Under the Curve of the thigh angular velocity in the pitch direction-representing both thigh and knee extension; the peak of the spine pitch angular velocity during SI-ST also had a large effect size, as did some temporal measures of duration of SI-ST, although less so. During the ST-SI transition the metric with the largest effect size in PwMS was the peak of the spine angular velocity curve in the roll direction. A regression was performed. Discussion: We propose for PwMS that the diminished peak angular velocity during SI-ST directly represents extensor weakness, while the increased roll during ST-SI represents diminished postural control. Conclusions: During the SI-ST transition of TUG, angular velocities can discriminate between healthy volunteers and ambulatory PwMS better than temporal features. Sensor placement on the thighs provides additional discrimination compared to sensor placement at the lumbar spine.

Dataset Information

Day-to-Day Variability and Year-to-Year Reproducibility of Accelerometer-Measured Free-Living Sit-to-Stand Transitions Volume and Intensity among Community-Dwelling Older Adults.

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