Abstract
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.
Highlights
Inertial sensors generate objective and sensitive metrics of movement disability that may indicate fall risk in many clinical conditions including multiple sclerosis (MS)
We found that the total time duration of the TUG task as measured by stopwatch was a consistent and discriminatory feature for these two cohorts; this is similar to a study of TUG in the elderly [Instrumental Activities of Daily Living (IADL) vs. no IADL] in which TUG duration was the most discriminatory feature [52], and to an Multiple Sclerosis (MS) vs. healthy comparison of the Timed 25 Foot Walk where overall velocity was the most discriminatory mobility feature [53]
In our cohorts we compared a wide variety of sensor-based microfeatures of TUG to two timing features of TUG as a whole; we found that many of the thigh-derived sensor micro-features are reproducible and have high reliability, and that a collection of thigh pitch angular velocity features based on the sit-to-stand transition differed between MS and healthy with higher effect sizes than total time duration of TUG; three of these features were statistically significantly different by the stringent Holm-Bonferroni method of multiple comparisons
Summary
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. Multiple Sclerosis (MS) is a progressive neurological disorder usually presenting in early adulthood whose manifestations include an unpredictable spectrum of motor, sensory and autonomic symptoms, usually accompanied by increasing levels of ambulatory dysfunction [1, 2]. MS is currently without a cure or a known cause, the last decade has seen a renaissance in disease modifying treatments and symptomatic therapies [3]. Assessment of intervention efficacy fundamentally depends on making accurate measurements of disease progression and disability. Traditional Measurements of Disability Progression in MS
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