Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic Exoskeleton
After a neurological injury, neurorehabilitation aims to restore sensorimotor function of patients. Technological assessments can provide high-quality data on a patient’s performance and support clinical decision making towards the most appropriate therapy. In this study, the ArmeoPower,...
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IEEE
2024-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/10734983/ |
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| author | Anna Sophie Knill Bettina Studer Peter Wolf Robert Riener Michela Goffredo Serena Maggioni |
| author_facet | Anna Sophie Knill Bettina Studer Peter Wolf Robert Riener Michela Goffredo Serena Maggioni |
| author_sort | Anna Sophie Knill |
| collection | DOAJ |
| description | After a neurological injury, neurorehabilitation aims to restore sensorimotor function of patients. Technological assessments can provide high-quality data on a patient’s performance and support clinical decision making towards the most appropriate therapy. In this study, the ArmeoPower, a robotic exoskeleton for the upper extremities, was used to assess 12 neurological patients and 31 non-disabled participants performing various standardized single joint and frontal plane game-like exercises. From the collected data, kinematic metrics (End-Point Error, Hand-Path Ratio, reaction time, stability, Number of Velocity Peaks, peak, and mean Velocity) and the game score, were calculated and analyzed according to three criteria: the reliability (a), the difference between patients and non-disabled participants (b), as well as the influence of robotic movement assistance (c). In total, 39 metrics were analyzed and the following five most promising assessment variables for different exercises could be identified based on the three above-mentioned criteria: smoothness (RainMug (wrist)), mean speed (RainMug (wrist)), reaction time (Goalkeeper), maximum speed (HighFlyer (elbow)) and accuracy (Connect the dots), with the former showing good validity (rho=0.82, p=0.02) when comparing to the patient’s severity level. The results demonstrate feasibility to extract and analyze various kinematic metrics from the ArmeoPower, which can provide quantitative information about human performance during training and therapy. The generated data increases the understanding of the patient’s movement and can be used in the future in clinical research for better performance evaluation and providing more feedback options, leading towards a more personalized and patient-centric therapy. |
| format | Article |
| id | doaj-art-484b082bd0f0475a8530a819d7fb224b |
| institution | Kabale University |
| issn | 1534-4320 1558-0210 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
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| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj-art-484b082bd0f0475a8530a819d7fb224b2024-11-12T00:00:08ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1534-43201558-02102024-01-01323942395210.1109/TNSRE.2024.348617310734983Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic ExoskeletonAnna Sophie Knill0https://orcid.org/0009-0002-8365-1740Bettina Studer1Peter Wolf2https://orcid.org/0000-0003-3616-9038Robert Riener3https://orcid.org/0000-0002-1726-2950Michela Goffredo4Serena Maggioni5Sensory-Motor Systems Laboratory, ETH Zurich, Zurich, SwitzerlandHocoma, Volketswil, SwitzerlandSensory-Motor Systems Laboratory, ETH Zurich, Zurich, SwitzerlandSensory-Motor Systems Laboratory, ETH Zurich, Zurich, SwitzerlandIRCCS San Raffaele Roma, Rome, ItalyHocoma, Volketswil, SwitzerlandAfter a neurological injury, neurorehabilitation aims to restore sensorimotor function of patients. Technological assessments can provide high-quality data on a patient’s performance and support clinical decision making towards the most appropriate therapy. In this study, the ArmeoPower, a robotic exoskeleton for the upper extremities, was used to assess 12 neurological patients and 31 non-disabled participants performing various standardized single joint and frontal plane game-like exercises. From the collected data, kinematic metrics (End-Point Error, Hand-Path Ratio, reaction time, stability, Number of Velocity Peaks, peak, and mean Velocity) and the game score, were calculated and analyzed according to three criteria: the reliability (a), the difference between patients and non-disabled participants (b), as well as the influence of robotic movement assistance (c). In total, 39 metrics were analyzed and the following five most promising assessment variables for different exercises could be identified based on the three above-mentioned criteria: smoothness (RainMug (wrist)), mean speed (RainMug (wrist)), reaction time (Goalkeeper), maximum speed (HighFlyer (elbow)) and accuracy (Connect the dots), with the former showing good validity (rho=0.82, p=0.02) when comparing to the patient’s severity level. The results demonstrate feasibility to extract and analyze various kinematic metrics from the ArmeoPower, which can provide quantitative information about human performance during training and therapy. The generated data increases the understanding of the patient’s movement and can be used in the future in clinical research for better performance evaluation and providing more feedback options, leading towards a more personalized and patient-centric therapy.https://ieeexplore.ieee.org/document/10734983/Assessmentexoskeletonkinematic metricsneurorehabilitationroboticsupper extremity |
| spellingShingle | Anna Sophie Knill Bettina Studer Peter Wolf Robert Riener Michela Goffredo Serena Maggioni Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic Exoskeleton IEEE Transactions on Neural Systems and Rehabilitation Engineering Assessment exoskeleton kinematic metrics neurorehabilitation robotics upper extremity |
| title | Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic Exoskeleton |
| title_full | Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic Exoskeleton |
| title_fullStr | Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic Exoskeleton |
| title_full_unstemmed | Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic Exoskeleton |
| title_short | Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic Exoskeleton |
| title_sort | kinematic assessment of upper limb movements using the armeopower robotic exoskeleton |
| topic | Assessment exoskeleton kinematic metrics neurorehabilitation robotics upper extremity |
| url | https://ieeexplore.ieee.org/document/10734983/ |
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