Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data
One of the core problems for people with multiple sclerosis (pwMS) is the impairment of their ability to walk, which can be severely restrictive in everyday life. Therefore, monitoring of ambulatory function is of great importance to be able to effectively counteract disease progression. An extensiv...
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2021
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oai:doaj.org-article:c362a19c192142458ec7294a2d0101eb2021-11-25T16:58:40ZAutomated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data10.3390/brainsci111115072076-3425https://doaj.org/article/c362a19c192142458ec7294a2d0101eb2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3425/11/11/1507https://doaj.org/toc/2076-3425One of the core problems for people with multiple sclerosis (pwMS) is the impairment of their ability to walk, which can be severely restrictive in everyday life. Therefore, monitoring of ambulatory function is of great importance to be able to effectively counteract disease progression. An extensive gait analysis, such as the Dresden protocol for multidimensional walking assessment, covers several facets of walking impairment including a 2-min walk test, in which the distance taken by the patient in two minutes is measured by an odometer. Using this approach, it is questionable how precise the measuring methods are at recording the distance traveled. In this project, we investigate whether the current measurement can be replaced by a digital measurement method based on accelerometers (six Opal sensors from the Mobility Lab system) that are attached to the patient’s body. We developed two algorithms using these data and compared the validity of these approaches using the results from 2-min walk tests from 562 pwMS that were collected with a gold-standard odometer. In 48.4% of pwMS, we detected an average relative measurement error of less than 5%, while results from 25.8% of the pwMS showed a relative measurement error of up to 10%. The algorithm had difficulties correctly calculating the walking distances in another 25.8% of pwMS; these results showed a measurement error of more than 20%. A main reason for this moderate performance was the variety of pathologically altered gait patterns in pwMS that may complicate the step detection. Overall, both algorithms achieved favorable levels of agreement (r = 0.884 and r = 0.980) with the odometer. Finally, we present suggestions for improvement of the measurement system to be implemented in the future.Katrin TrentzschBenjamin MelzerHeidi Stölzer-HutschRocco HaasePaul BartschtPaul MeyerTjalf ZiemssenMDPI AGarticlemultiple sclerosisgait analysismobilitydigital tools and applicationsNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENBrain Sciences, Vol 11, Iss 1507, p 1507 (2021) |
| institution |
DOAJ |
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DOAJ |
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EN |
| topic |
multiple sclerosis gait analysis mobility digital tools and applications Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 |
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multiple sclerosis gait analysis mobility digital tools and applications Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Katrin Trentzsch Benjamin Melzer Heidi Stölzer-Hutsch Rocco Haase Paul Bartscht Paul Meyer Tjalf Ziemssen Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data |
| description |
One of the core problems for people with multiple sclerosis (pwMS) is the impairment of their ability to walk, which can be severely restrictive in everyday life. Therefore, monitoring of ambulatory function is of great importance to be able to effectively counteract disease progression. An extensive gait analysis, such as the Dresden protocol for multidimensional walking assessment, covers several facets of walking impairment including a 2-min walk test, in which the distance taken by the patient in two minutes is measured by an odometer. Using this approach, it is questionable how precise the measuring methods are at recording the distance traveled. In this project, we investigate whether the current measurement can be replaced by a digital measurement method based on accelerometers (six Opal sensors from the Mobility Lab system) that are attached to the patient’s body. We developed two algorithms using these data and compared the validity of these approaches using the results from 2-min walk tests from 562 pwMS that were collected with a gold-standard odometer. In 48.4% of pwMS, we detected an average relative measurement error of less than 5%, while results from 25.8% of the pwMS showed a relative measurement error of up to 10%. The algorithm had difficulties correctly calculating the walking distances in another 25.8% of pwMS; these results showed a measurement error of more than 20%. A main reason for this moderate performance was the variety of pathologically altered gait patterns in pwMS that may complicate the step detection. Overall, both algorithms achieved favorable levels of agreement (r = 0.884 and r = 0.980) with the odometer. Finally, we present suggestions for improvement of the measurement system to be implemented in the future. |
| format |
article |
| author |
Katrin Trentzsch Benjamin Melzer Heidi Stölzer-Hutsch Rocco Haase Paul Bartscht Paul Meyer Tjalf Ziemssen |
| author_facet |
Katrin Trentzsch Benjamin Melzer Heidi Stölzer-Hutsch Rocco Haase Paul Bartscht Paul Meyer Tjalf Ziemssen |
| author_sort |
Katrin Trentzsch |
| title |
Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data |
| title_short |
Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data |
| title_full |
Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data |
| title_fullStr |
Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data |
| title_full_unstemmed |
Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data |
| title_sort |
automated analysis of the two-minute walk test in clinical practice using accelerometer data |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/c362a19c192142458ec7294a2d0101eb |
| work_keys_str_mv |
AT katrintrentzsch automatedanalysisofthetwominutewalktestinclinicalpracticeusingaccelerometerdata AT benjaminmelzer automatedanalysisofthetwominutewalktestinclinicalpracticeusingaccelerometerdata AT heidistolzerhutsch automatedanalysisofthetwominutewalktestinclinicalpracticeusingaccelerometerdata AT roccohaase automatedanalysisofthetwominutewalktestinclinicalpracticeusingaccelerometerdata AT paulbartscht automatedanalysisofthetwominutewalktestinclinicalpracticeusingaccelerometerdata AT paulmeyer automatedanalysisofthetwominutewalktestinclinicalpracticeusingaccelerometerdata AT tjalfziemssen automatedanalysisofthetwominutewalktestinclinicalpracticeusingaccelerometerdata |
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