Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings
Background: Gait variability is an established marker of gait function that can be assessed using sensor-based approaches. In clinical settings, spatial constraints and patient condition impede the execution of longer distance walks for the recording of gait parameters. Turning paradigms are often u...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-01-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fnagi.2018.00435/full |
| _version_ | 1819016987024556032 |
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| author | Daniel Kroneberg Morad Elshehabi Morad Elshehabi Anne-Christiane Meyer Karen Otte Sarah Doss Friedemann Paul Friedemann Paul Friedemann Paul Susanne Nussbaum Daniela Berg Daniela Berg Andrea A. Kühn Andrea A. Kühn Andrea A. Kühn Andrea A. Kühn Walter Maetzler Walter Maetzler Tanja Schmitz-Hübsch Tanja Schmitz-Hübsch |
| author_facet | Daniel Kroneberg Morad Elshehabi Morad Elshehabi Anne-Christiane Meyer Karen Otte Sarah Doss Friedemann Paul Friedemann Paul Friedemann Paul Susanne Nussbaum Daniela Berg Daniela Berg Andrea A. Kühn Andrea A. Kühn Andrea A. Kühn Andrea A. Kühn Walter Maetzler Walter Maetzler Tanja Schmitz-Hübsch Tanja Schmitz-Hübsch |
| author_sort | Daniel Kroneberg |
| collection | DOAJ |
| description | Background: Gait variability is an established marker of gait function that can be assessed using sensor-based approaches. In clinical settings, spatial constraints and patient condition impede the execution of longer distance walks for the recording of gait parameters. Turning paradigms are often used to overcome these constraints and commercial gait analysis systems algorithmically exclude turns for gait parameters calculations. We investigated the effect of turns in sensor-based assessment of gait variability.Methods: Continuous recordings from 31 patients with movement disorders (ataxia, essential tremor and Parkinson’s disease) and 162 healthy elderly (HE) performing level walks including 180° turns were obtained using an inertial sensor system. Accuracy of the manufacturer’s algorithm of turn-detection was verified by plotting stride time series. Strides before and after turn events were extracted and compared to respective average of all strides. Coefficient of variation (CoV) of stride length and stride time was calculated for entire set of strides, segments between turns and as cumulative values. Their variance and congruency was used to estimate the number of strides required to reliably assess the magnitude of stride variability.Results: Non-detection of turns in 5.8% of HE lead to falsely increased CoV for these individuals. Even after exclusion of these, strides before/after turns tended to be spatially shorter and temporally longer in all groups, contributing to an increase of CoV at group level and widening of confidence margins with increasing numbers of strides. This could be attenuated by a more generous turn excision as an alternative approach. Correlation analyses revealed excellent consistency for CoVs after at most 20 strides in all groups. Respective stride counts were even lower in patients using a more generous turn excision.Conclusion: Including turns to increase continuous walking distance in spatially confined settings does not necessarily improve the validity and reliability of gait variability measures. Specifically with gait pathology, perturbations of stride characteristics before/after algorithmically excised turns were observed that may increase gait variability with this paradigm. We conclude that shorter distance walks of around 15 strides suffice for reliable and valid recordings of gait variability in the groups studied here. |
| first_indexed | 2024-12-21T02:56:21Z |
| format | Article |
| id | doaj.art-63451ad904f14dc4a5c07242164cae7b |
| institution | Directory Open Access Journal |
| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-12-21T02:56:21Z |
| publishDate | 2019-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-63451ad904f14dc4a5c07242164cae7b2022-12-21T19:18:19ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652019-01-011010.3389/fnagi.2018.00435389096Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined SettingsDaniel Kroneberg0Morad Elshehabi1Morad Elshehabi2Anne-Christiane Meyer3Karen Otte4Sarah Doss5Friedemann Paul6Friedemann Paul7Friedemann Paul8Susanne Nussbaum9Daniela Berg10Daniela Berg11Andrea A. Kühn12Andrea A. Kühn13Andrea A. Kühn14Andrea A. Kühn15Walter Maetzler16Walter Maetzler17Tanja Schmitz-Hübsch18Tanja Schmitz-Hübsch19Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, GermanyDepartment of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, GermanyDepartment of Neurodegenerative Diseases, Center for Neurology, Hertie Institute for Clinical Brain Research, Tübingen, GermanyCharité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, GermanyCharité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, GermanyCharité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, GermanyCharité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, GermanyCharité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, GermanyExperimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité – Universitätsmedizin Berlin, Berlin, GermanyDepartment of Neurodegenerative Diseases, Center for Neurology, Hertie Institute for Clinical Brain Research, Tübingen, GermanyDepartment of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, GermanyDepartment of Neurodegenerative Diseases, Center for Neurology, Hertie Institute for Clinical Brain Research, Tübingen, GermanyCharité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, GermanyCharité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, GermanyExperimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité – Universitätsmedizin Berlin, Berlin, GermanyBerlin School of Mind and Brain, Charité – Universitätsmedizin Berlin, Berlin, GermanyDepartment of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, GermanyDepartment of Neurodegenerative Diseases, Center for Neurology, Hertie Institute for Clinical Brain Research, Tübingen, GermanyCharité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, GermanyExperimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité – Universitätsmedizin Berlin, Berlin, GermanyBackground: Gait variability is an established marker of gait function that can be assessed using sensor-based approaches. In clinical settings, spatial constraints and patient condition impede the execution of longer distance walks for the recording of gait parameters. Turning paradigms are often used to overcome these constraints and commercial gait analysis systems algorithmically exclude turns for gait parameters calculations. We investigated the effect of turns in sensor-based assessment of gait variability.Methods: Continuous recordings from 31 patients with movement disorders (ataxia, essential tremor and Parkinson’s disease) and 162 healthy elderly (HE) performing level walks including 180° turns were obtained using an inertial sensor system. Accuracy of the manufacturer’s algorithm of turn-detection was verified by plotting stride time series. Strides before and after turn events were extracted and compared to respective average of all strides. Coefficient of variation (CoV) of stride length and stride time was calculated for entire set of strides, segments between turns and as cumulative values. Their variance and congruency was used to estimate the number of strides required to reliably assess the magnitude of stride variability.Results: Non-detection of turns in 5.8% of HE lead to falsely increased CoV for these individuals. Even after exclusion of these, strides before/after turns tended to be spatially shorter and temporally longer in all groups, contributing to an increase of CoV at group level and widening of confidence margins with increasing numbers of strides. This could be attenuated by a more generous turn excision as an alternative approach. Correlation analyses revealed excellent consistency for CoVs after at most 20 strides in all groups. Respective stride counts were even lower in patients using a more generous turn excision.Conclusion: Including turns to increase continuous walking distance in spatially confined settings does not necessarily improve the validity and reliability of gait variability measures. Specifically with gait pathology, perturbations of stride characteristics before/after algorithmically excised turns were observed that may increase gait variability with this paradigm. We conclude that shorter distance walks of around 15 strides suffice for reliable and valid recordings of gait variability in the groups studied here.https://www.frontiersin.org/article/10.3389/fnagi.2018.00435/fullgait variabilitygait analysisturn detectionhealthy elderlymovement disorders |
| spellingShingle | Daniel Kroneberg Morad Elshehabi Morad Elshehabi Anne-Christiane Meyer Karen Otte Sarah Doss Friedemann Paul Friedemann Paul Friedemann Paul Susanne Nussbaum Daniela Berg Daniela Berg Andrea A. Kühn Andrea A. Kühn Andrea A. Kühn Andrea A. Kühn Walter Maetzler Walter Maetzler Tanja Schmitz-Hübsch Tanja Schmitz-Hübsch Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings Frontiers in Aging Neuroscience gait variability gait analysis turn detection healthy elderly movement disorders |
| title | Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings |
| title_full | Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings |
| title_fullStr | Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings |
| title_full_unstemmed | Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings |
| title_short | Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings |
| title_sort | less is more estimation of the number of strides required to assess gait variability in spatially confined settings |
| topic | gait variability gait analysis turn detection healthy elderly movement disorders |
| url | https://www.frontiersin.org/article/10.3389/fnagi.2018.00435/full |
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