Bimanual Elbow Robotic Orthoses: Preliminary Investigations on an Impairment Force-Feedback Rehabilitation Method
Notice bibliographique
Résumé
Modern rehabilitation practices have begun integrating robots, recognizing their significant role in recovery. New and alternative stroke rehabilitation treatments are essential to enhance efficacy and mitigate associated health costs. Today's robotic interventions can play a significant role in advancing rehabilitation. In addition, robots have an inherent ability to perform tasks accurately and reliably and are typically well suited to measure and quantify performance. Most rehabilitation strategies predominantly target activation of the paretic arm. However, bimanual upper-limb rehabilitation research suggests potential in enhancing functional recovery. Moreover, studies suggest that limb coordination and synchronization can improve treatment efficacy. In this preliminary study, we aimed to investigate and validate our user-driven bimanual system in a reduced intensity rehab practice. A bimanual wearable robotic device (BWRD) with a Master-Slave configuration for the elbow joint was developed to carry out the investigation. The BWRD incorporates position and force sensors for which respective control loops are implemented, and offers varying modes of operation ranging from passive to active training. The proposed system enables the perception of the movements, as well as the forces applied by the hemiparetic arm, with the non-hemiparetic arm. Eight participants with chronic unilateral stroke were recruited to participate in a total of three 1-h sessions per participant, delivered in a week. Participants underwent pre- and post-training functional assessments along with proprioceptive measures. The post-assessment was performed at the end of the last training session. The protocol was designed to engage the user in an assortment of static and dynamic arm matching and opposing tasks. The training incorporates force-feedback movements, force-feedback positioning, and force matching tasks with same and opposite direction movements. We are able to suggest identification of impairment patterns in the position-force plot results. In addition, we performed a proprioception evaluation with the system. We set out to design innovative and user immersive training tasks that utilize the BWRD capabilities, and we demonstrate that the subjects were able to cooperate and accomplish the protocol. We found that the Fugl-Meyer and Wolf Motor Function Test (pre to post) measured improvements (15 and 19%, respectively). Recognizing the brevity of the training, we focus our report primarily on the proprioception testing (32% significant improvement, p prop = 0.033) and protocol distinctive features and results. This paper presents the electromechanical features and performance of the BWRD, the testing protocol, and the assessments utilized. Outcome measures and results are presented and demonstrate the successful application and operation of the system.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».