Is the freezing index a valid outcome to assess freezing of gait during turning in Parkinson’s disease?
IntroductionFreezing of gait (FOG) is a disabling symptom for people with Parkinson’s disease (PwPD). Turning on the spot for one minute in alternating directions (360 turn) while performing a cognitive dual-task (DT) is a fast and sensitive way to provoke FOG. The FOG-index is a widely used wearabl...
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Frontiers Media S.A.
2025-01-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2024.1508800/full |
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author | Maaike Goris Pieter Ginis Clint Hansen Christian Schlenstedt Christian Schlenstedt Jeffrey M. Hausdorff Jeffrey M. Hausdorff Jeffrey M. Hausdorff Nicholas D’Cruz Wim Vandenberghe Wim Vandenberghe Walter Maetzler Alice Nieuwboer Moran Gilat |
author_facet | Maaike Goris Pieter Ginis Clint Hansen Christian Schlenstedt Christian Schlenstedt Jeffrey M. Hausdorff Jeffrey M. Hausdorff Jeffrey M. Hausdorff Nicholas D’Cruz Wim Vandenberghe Wim Vandenberghe Walter Maetzler Alice Nieuwboer Moran Gilat |
author_sort | Maaike Goris |
collection | DOAJ |
description | IntroductionFreezing of gait (FOG) is a disabling symptom for people with Parkinson’s disease (PwPD). Turning on the spot for one minute in alternating directions (360 turn) while performing a cognitive dual-task (DT) is a fast and sensitive way to provoke FOG. The FOG-index is a widely used wearable sensor-based algorithm to quantify FOG severity during turning. Despite that, the FOG-index’s classification performance and criterion validity is not tested against the gold standard (i.e., video-rated time spent freezing). Therefore, this study aimed to evaluate the FOG-index’s classification performance and criterion validity to assess FOG severity during 360 turn. Additionally, we investigated the FOG-index’s optimal cutoff values to differentiate between PwPD with and without FOG.Methods164 PwPD self-reported the presence of FOG on the New Freezing of Gait Questionnaire (NFOGQ) and performed the DT 360 turn in the ON medication state while being videoed and wearing five wearable sensors. Two independent clinical experts rated FOG on video. ROC-AUC values assessed the FOG-index’s classification accuracy against self-reported FOG and expert ratings. Spearman-rho was used to evaluate the correlation between expert and FOG-index ratings of FOG severity.ResultsTwenty-eight patients self-reported FOG, while 104 were classified as a freezer by the experts. The FOG-index had limited classification agreement with the NFOGQ (AUC = 0.60, p = 0.115, sensitivity 46.4%, specificity 72.8%) and the experts (AUC = 0.65, p < 0.001, sensitivity 68.3%, specificity 61.7%). Only weak correlations were found between the algorithm outputs and expert ratings for FOG severity (rho = 0.13–0.38).ConclusionA surprisingly large discrepancy was found between self-reported and expert-rated FOG during the 360 turning task, indicating PwPD do not always notice FOG in daily life. The FOG-index achieved suboptimal classification performance and poor criterion validity to assess FOG severity. Regardless, 360 turning proved a sensitive task to elicit FOG. Further development of the FOG-index is warranted, and long-term follow-up studies are needed to assess the predictive value of the 360 turning task for classifying FOG conversion. |
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institution | Kabale University |
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spelling | doaj-art-c5dcbbca40794738a69c12527812e9a32025-01-08T05:10:26ZengFrontiers Media S.A.Frontiers in Neurology1664-22952025-01-011510.3389/fneur.2024.15088001508800Is the freezing index a valid outcome to assess freezing of gait during turning in Parkinson’s disease?Maaike Goris0Pieter Ginis1Clint Hansen2Christian Schlenstedt3Christian Schlenstedt4Jeffrey M. Hausdorff5Jeffrey M. Hausdorff6Jeffrey M. Hausdorff7Nicholas D’Cruz8Wim Vandenberghe9Wim Vandenberghe10Walter Maetzler11Alice Nieuwboer12Moran Gilat13Department of Rehabilitation Sciences, Neurorehabilitation Research Group (eNRGy), KU Leuven, Leuven, BelgiumDepartment of Rehabilitation Sciences, Neurorehabilitation Research Group (eNRGy), KU Leuven, Leuven, BelgiumDepartment of Neurology, University Hospital Schleswig-Holstein, Christian-Albrechts-University Kiel, Kiel, GermanyDepartment of Neurology, University Hospital Schleswig-Holstein, Christian-Albrechts-University Kiel, Kiel, GermanyInstitute of Interdisciplinary Exercise Science and Sports Medicine, Medical School Hamburg, Hamburg, GermanyDepartment of Physical Therapy, Faculty of Medical & Health Sciences and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, IsraelCenter for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, IsraelRush Alzheimer’s Disease Center, Rush University Medical Center and Department of Orthopaedic Surgery, Rush Medical College, Chigaco, IL, United StatesDepartment of Rehabilitation Sciences, Neurorehabilitation Research Group (eNRGy), KU Leuven, Leuven, BelgiumDepartment of Neurosciences, Laboratory for Parkinson Research, KU Leuven, Leuven, BelgiumDepartment of Neurology, University Hospitals Leuven, Leuven, BelgiumDepartment of Neurology, University Hospital Schleswig-Holstein, Christian-Albrechts-University Kiel, Kiel, GermanyDepartment of Rehabilitation Sciences, Neurorehabilitation Research Group (eNRGy), KU Leuven, Leuven, BelgiumDepartment of Rehabilitation Sciences, Neurorehabilitation Research Group (eNRGy), KU Leuven, Leuven, BelgiumIntroductionFreezing of gait (FOG) is a disabling symptom for people with Parkinson’s disease (PwPD). Turning on the spot for one minute in alternating directions (360 turn) while performing a cognitive dual-task (DT) is a fast and sensitive way to provoke FOG. The FOG-index is a widely used wearable sensor-based algorithm to quantify FOG severity during turning. Despite that, the FOG-index’s classification performance and criterion validity is not tested against the gold standard (i.e., video-rated time spent freezing). Therefore, this study aimed to evaluate the FOG-index’s classification performance and criterion validity to assess FOG severity during 360 turn. Additionally, we investigated the FOG-index’s optimal cutoff values to differentiate between PwPD with and without FOG.Methods164 PwPD self-reported the presence of FOG on the New Freezing of Gait Questionnaire (NFOGQ) and performed the DT 360 turn in the ON medication state while being videoed and wearing five wearable sensors. Two independent clinical experts rated FOG on video. ROC-AUC values assessed the FOG-index’s classification accuracy against self-reported FOG and expert ratings. Spearman-rho was used to evaluate the correlation between expert and FOG-index ratings of FOG severity.ResultsTwenty-eight patients self-reported FOG, while 104 were classified as a freezer by the experts. The FOG-index had limited classification agreement with the NFOGQ (AUC = 0.60, p = 0.115, sensitivity 46.4%, specificity 72.8%) and the experts (AUC = 0.65, p < 0.001, sensitivity 68.3%, specificity 61.7%). Only weak correlations were found between the algorithm outputs and expert ratings for FOG severity (rho = 0.13–0.38).ConclusionA surprisingly large discrepancy was found between self-reported and expert-rated FOG during the 360 turning task, indicating PwPD do not always notice FOG in daily life. The FOG-index achieved suboptimal classification performance and poor criterion validity to assess FOG severity. Regardless, 360 turning proved a sensitive task to elicit FOG. Further development of the FOG-index is warranted, and long-term follow-up studies are needed to assess the predictive value of the 360 turning task for classifying FOG conversion.https://www.frontiersin.org/articles/10.3389/fneur.2024.1508800/fullParkinson’s diseasefreezing of gaitwearable sensorsaccelerometerturningclassification |
spellingShingle | Maaike Goris Pieter Ginis Clint Hansen Christian Schlenstedt Christian Schlenstedt Jeffrey M. Hausdorff Jeffrey M. Hausdorff Jeffrey M. Hausdorff Nicholas D’Cruz Wim Vandenberghe Wim Vandenberghe Walter Maetzler Alice Nieuwboer Moran Gilat Is the freezing index a valid outcome to assess freezing of gait during turning in Parkinson’s disease? Frontiers in Neurology Parkinson’s disease freezing of gait wearable sensors accelerometer turning classification |
title | Is the freezing index a valid outcome to assess freezing of gait during turning in Parkinson’s disease? |
title_full | Is the freezing index a valid outcome to assess freezing of gait during turning in Parkinson’s disease? |
title_fullStr | Is the freezing index a valid outcome to assess freezing of gait during turning in Parkinson’s disease? |
title_full_unstemmed | Is the freezing index a valid outcome to assess freezing of gait during turning in Parkinson’s disease? |
title_short | Is the freezing index a valid outcome to assess freezing of gait during turning in Parkinson’s disease? |
title_sort | is the freezing index a valid outcome to assess freezing of gait during turning in parkinson s disease |
topic | Parkinson’s disease freezing of gait wearable sensors accelerometer turning classification |
url | https://www.frontiersin.org/articles/10.3389/fneur.2024.1508800/full |
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