Dataset Information

Smartphone Accelerometry: A Smart and Reliable Measurement of Real-Life Physical Activity in Multiple Sclerosis and Healthy Individuals.

ABSTRACT: Background: Mobility impairment is common in persons with multiple sclerosis (pwMS) and can be assessed with clinical tests and surveys that have restricted ecological validity. Commercial research-based accelerometers are considered to be more valuable as they measure real-life mobility. Smartphone accelerometry might be an easily accessible alternative. Objective: To explore smartphone accelerometry in comparison to clinical tests, surveys, and a wrist-worn ActiGraph in pwMS and controls. Methods: Sixty-seven pwMS and 70 matched controls underwent mobility tests and surveys. Real-life data were collected with a smartphone and an ActiGraph over 7 days. We explored different smartphone metrics in a technical validation course and computed afterward correlation between ActiGraph (steps per minute), smartphone accelerometry (variance of vector magnitude), clinical tests, and surveys. We also determined the ability to separate between patients and controls as well as between different disability groups. Results: Based on the technical validation, we found the variance of the vector magnitude as a reliable estimate to discriminate wear time and no wear-time of the smartphone. Due to a further association with different activity levels, it was selected for real-life analyses. In the cross-sectional study, ActiGraph correlated moderately (r = 0.43, p < 0.05) with the smartphone but less with clinical tests (rho between |0.211| and |0.337|). Smartphone data showed stronger correlations with age (rho = -0.487) and clinical tests (rho between |0.565| and |0.605|). ActiGraph only differed between pwMS and controls (p < 0.001) but not between disability groups. At the same time, the smartphone showed differences between pwMS and controls, between RRMS and PP-/SPMS, and between participants with/without ambulatory impairment (all p < 0.001). Conclusions: Smartphone accelerometry provides better estimates of mobility and disability than a wrist-worn standard accelerometer in a free-living context for both controls and pwMS. Given the fact that no additional device is needed, smartphone accelerometry might be a convenient outcome of real-life ambulation in healthy individuals and chronic diseases such as MS.

SUBMITTER: Zhai Y

PROVIDER: S-EPMC7456810 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Smartphone Accelerometry: A Smart and Reliable Measurement of Real-Life Physical Activity in Multiple Sclerosis and Healthy Individuals.

Zhai Yuyang Y Nasseri Navina N Pöttgen Jana J Gezhelbash Eghbal E Heesen Christoph C Stellmann Jan-Patrick JP

Frontiers in neurology 20200814

<b>Background:</b> Mobility impairment is common in persons with multiple sclerosis (pwMS) and can be assessed with clinical tests and surveys that have restricted ecological validity. Commercial research-based accelerometers are considered to be more valuable as they measure real-life mobility. Smartphone accelerometry might be an easily accessible alternative. <b>Objective:</b> To explore smartphone accelerometry in comparison to clinical tests, surveys, and a wrist-worn ActiGraph in pwMS and ...[more]

PMID: 32922346

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Project description:OBJECTIVE:This study aimed to determine the intra-rater and inter-rater reliability and validity of a hybrid device, combining virtual reality goggles, a magnetometer and an inclinometer application for smartphones, to measure craniocervical range. SUMMARY OF BACKGROUND DATA:Accurate evaluation of craniocervical range of motion is important for early detection of certain diseased conditions and monitoring the progress of interventions. The universal goniometer is widely used for the measurement but it requires experienced practitioners. Whether a combination of virtual reality goggles and smartphone applications can provide the same or better performance compared with the goniometer is still unknown. METHODS:Forty-one healthy adults from the department of physical medicine and rehabilitation were recruited for craniocervical range examination (flexion, extension, side-bending to the right or left and rotating to the right or left) by using the hybrid device and universal goniometer. Using the hybrid device, repeated measurements were performed twice by a primary rater and once by a second rater. The primary rater also conducted a measurement using the universal goniometer in the same cohort. The intra-rater and inter-rater reliability (intra-class correlation coefficient (ICC)) were calculated using the two-way random effect model, whereas the validity was examined by the Pearson correlation coefficient and Bland-and-Altman plot. The interval between the first and second sessions of the measurement for intra-rater reliability was set at 30 min. RESULTS:Excellent intra-rater (ICC ? 0.925) and inter-rater (ICC ? 0.880) reliability was noted for the hybrid device. The minimal detectable changes from intra-observer and inter-observer comparisons ranged between 4.12° and 7.42° in all six directions. The Bland-and-Altman plot revealed small mean differences (?1.68°) between the hybrid device and universal goniometer. Both instruments had highly correlated measurements of craniocervical motion (r values ? 0.918). CONCLUSION:For healthy participants, excellent intra-rater and inter-rater reliability was noted for the hybrid device, and the measurements were consistent with the universal goniometer measurements. Future studies are needed to examine whether the device can perform similarly for patients with neck disorders.

Dataset Information

Smartphone Accelerometry: A Smart and Reliable Measurement of Real-Life Physical Activity in Multiple Sclerosis and Healthy Individuals.

Publications

Smartphone Accelerometry: A Smart and Reliable Measurement of Real-Life Physical Activity in Multiple Sclerosis and Healthy Individuals.

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