Multiple Sclerosis
Conditions
Keywords
Multiple Sclerosis, Motion sensors, Smartwatch, Steps, Walking, Validation
Brief summary
The study is designed to validate the accuracy of steps detected by a commercially available smartwatch in persons with multiple sclerosis. Specifically, the investigators examine whether a smartwatch can detect steps accurately during slow, comfortable and fast overground walking. The total steps counted by the smartwatch will be compared to those counted by an accelerometer commonly used in clinical studies and the actually walked steps.
Detailed description
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. It is one of the most common neurological diseases in young adulthood. The main symptoms of MS are gait and mobility impairments, which also determine the severity of the disease. Currently, subjective clinical functional tests are commonly used to evaluate therapy outcomes. Due to advancing mechanization, body-worn accelerometers have been established as a potential instrument for the objective detection of mobility in clinical research. The accuracy of these devices for determining the mobility is therefore essential. However, current studies, especially in people with altered gait, show large deviations in step detection accuracy. In the present study we want to investigate: i) whether a commercially available smartwatch (Polar M600) counts steps in persons with multiple sclerosis (pwMS) accurately and ii) whether it counts steps as accurately as an accelerometer commonly used in clinical research (ActiGraph wGT3X-BT). In addition, the accuracy of the step detection by the algorithms of the manufacturer of the two devices (Polar M600 and ActiGraph wGT3X-BT) will be compared with an own-developed algorithm. For this purpose, 63 pwMS with low to severe functional restriction (EDSS: 0 - 6.5) will participate in this validation study. The validation protocol consists of three walking tests with different walking velocities. During these three conditions the participants will wear the Polar M600 on the wrist and the ActiGraph wGT3X-BT with a belt over the hip. In the first walking test, the subjects will complete 250 steps with comfortable walking velocity (CWV). After a sufficient break, the participants will be randomly assigned to either a fast walking velocity condition (FWV: CWV + 20%) followed by a sufficient period of rest and a slow walking velocity condition (SWV: CWV - 20%) or vice versa. Each of the walking tests with modified walking velocity also consists of 250 steps. To analyze the accuracy of step detection, the measured steps of the devices will be compared with the actually walked 250 steps.
Interventions
BEHAVIORALComfortable walking velocity (CWV)
Walking for 250 Steps with self-selected comfortable walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT)
BEHAVIORALSlow walking velocity (SWV: CWV - 20%)
Walking for 250 Steps with slow walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT). Slow walking consists of walking with 20% slower than the self-selected comfortable walking velocity by following a researcher who controls the walking velocity with a measuring wheel.
BEHAVIORALFast walking velocity (FWV: CWV + 20%)
Walking for 250 Steps with fast walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT). Fast walking consists of walking with 20% faster than the self-selected comfortable walking velocity by following a researcher who controls the walking velocity with a measuring wheel.
Sponsors
Neurological Rehabilitation Center Quellenhof
ZTM Bad Kissingen
University of Erlangen-Nürnberg
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
OTHER
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Multiple Sclerosis with Expanded Disability Status Scale between 0 - 6.5 * Ability to walk 250 steps with or without an assistive device
Exclusion criteria
* Clinically relevant cardiovascular or orthopaedic disease * Severe polyneuropathy * Cognitive impairment
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Step detection during comfortable walking | Following the comfortable walking velocity protocol, an average of 2 minutes | Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during comfortable walking for 250 steps. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Step detection during slow walking | Following the slow walking velocity protocol, an average of 2 minutes | Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during slow walking for 250 steps. |
| Step detection during fast walking | Following the fast walking velocity protocol, an average of 2 minutes | Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during fast walking for 250 steps. |
Countries
Germany
Outcome results
None listed