Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton
Abstract Background The clinical evaluation of the upper limb of severely impaired stroke patient is challenging. Sensor-based assessments may allow for an objective evaluation of this patient population. This study investigated the validity of a device-assisted approach in comparison to the clinica...
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doaj-a3670a729d5b4fa2b0d6aa95e4f7c9a22021-06-06T11:23:57ZengBMCJournal of NeuroEngineering and Rehabilitation1743-00032021-06-0118111110.1186/s12984-021-00875-7Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeletonFlorian Grimm0Jelena Kraugmann1Georgios Naros2Alireza Gharabaghi3Department of Neurosurgery and Neurotechnology, Institute for Neuromodulation and Neurotechnology, University Hospital and University of TübingenDepartment of Neurosurgery and Neurotechnology, Institute for Neuromodulation and Neurotechnology, University Hospital and University of TübingenDepartment of Neurosurgery and Neurotechnology, Institute for Neuromodulation and Neurotechnology, University Hospital and University of TübingenDepartment of Neurosurgery and Neurotechnology, Institute for Neuromodulation and Neurotechnology, University Hospital and University of TübingenAbstract Background The clinical evaluation of the upper limb of severely impaired stroke patient is challenging. Sensor-based assessments may allow for an objective evaluation of this patient population. This study investigated the validity of a device-assisted approach in comparison to the clinical outcome that it is supposed to reflect. Methods In nineteen severely impaired chronic stroke patients, we applied a gravity-compensating, multi-joint arm exoskeleton (Armeo Spring) and compared this sensor-based assessment with the clinical outcome measure Upper Extremity Fugl-Meyer Assessment (UE-FMA) scale. Specifically, we assessed separately and subsequently the range of motion in joint space for four single joints (i.e., wrist, elbow and shoulder flexion/extension (FE), and shoulder internal/external rotation (IER)), and the closing and opening of the hand with a pressure sensor placed in the handle. Results Within the kinematic parameters, a strong correlation was observed between wrist and elbow FE (r > 0.7, p < 0.003; Bonferroni corrected). The UE-FMA was significantly predicted by a multiple regression model (F (5, 13) = 12.22, p < 0.0005, adj. R 2 = 0.83). Both shoulder IER and grip pressure added significantly (p < 0.05) to the prediction with the standardized coefficients β of 0.55 and 0.38, respectively. Conclusions By applying an exoskeleton-based self-contained evaluation of single-joint movements, a clinically valid assessment of the upper limb range of motion in severely impaired stroke patients is feasible. Shoulder IER contributed most relevantly to the prediction of the clinical status. These findings need to be confirmed in a large, independent patient cohort.https://doi.org/10.1186/s12984-021-00875-7Human–machine interfaceExoskeletonSensorimotor interactionVirtual realityHand-arm modelMovement analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Florian Grimm Jelena Kraugmann Georgios Naros Alireza Gharabaghi |
spellingShingle |
Florian Grimm Jelena Kraugmann Georgios Naros Alireza Gharabaghi Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton Journal of NeuroEngineering and Rehabilitation Human–machine interface Exoskeleton Sensorimotor interaction Virtual reality Hand-arm model Movement analysis |
author_facet |
Florian Grimm Jelena Kraugmann Georgios Naros Alireza Gharabaghi |
author_sort |
Florian Grimm |
title |
Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_short |
Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_full |
Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_fullStr |
Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_full_unstemmed |
Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_sort |
clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
publisher |
BMC |
series |
Journal of NeuroEngineering and Rehabilitation |
issn |
1743-0003 |
publishDate |
2021-06-01 |
description |
Abstract Background The clinical evaluation of the upper limb of severely impaired stroke patient is challenging. Sensor-based assessments may allow for an objective evaluation of this patient population. This study investigated the validity of a device-assisted approach in comparison to the clinical outcome that it is supposed to reflect. Methods In nineteen severely impaired chronic stroke patients, we applied a gravity-compensating, multi-joint arm exoskeleton (Armeo Spring) and compared this sensor-based assessment with the clinical outcome measure Upper Extremity Fugl-Meyer Assessment (UE-FMA) scale. Specifically, we assessed separately and subsequently the range of motion in joint space for four single joints (i.e., wrist, elbow and shoulder flexion/extension (FE), and shoulder internal/external rotation (IER)), and the closing and opening of the hand with a pressure sensor placed in the handle. Results Within the kinematic parameters, a strong correlation was observed between wrist and elbow FE (r > 0.7, p < 0.003; Bonferroni corrected). The UE-FMA was significantly predicted by a multiple regression model (F (5, 13) = 12.22, p < 0.0005, adj. R 2 = 0.83). Both shoulder IER and grip pressure added significantly (p < 0.05) to the prediction with the standardized coefficients β of 0.55 and 0.38, respectively. Conclusions By applying an exoskeleton-based self-contained evaluation of single-joint movements, a clinically valid assessment of the upper limb range of motion in severely impaired stroke patients is feasible. Shoulder IER contributed most relevantly to the prediction of the clinical status. These findings need to be confirmed in a large, independent patient cohort. |
topic |
Human–machine interface Exoskeleton Sensorimotor interaction Virtual reality Hand-arm model Movement analysis |
url |
https://doi.org/10.1186/s12984-021-00875-7 |
work_keys_str_mv |
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