The Effects of Digital Anesthesia on Force Control Using a Precision Grip
Notice bibliographique
Résumé
A total of 20 right-handed subjects were asked to perform a grasp-lift-and-hold task using a precision grip. The grasped object was a one-degree-of-freedom manipuladum consisting of a vertically mounted linear motor capable of generating resistive forces to simulate a range of object weights. In the initial study, seven subjects (6 women, 1 man; ages 24-56 yr) were first asked to lift and hold the object stationary for 4 s. The object presented a metal tab with two different surface textures and offered one of four resistive forces (0.5, 1.0, 1.5, and 2.0 N). The lifts were performed both with and without visual feedback. Next, the subjects were asked to perform the same grasping sequence again after ring block anesthesia of the thumb and index finger with mepivacaine. The objective was to determine the degree to which an internal model obtained through prior familiarity might compensate for the loss of cutaneous sensation. In agreement with previous studies, it was found that all subjects applied significantly greater grip force after digital anesthesia, and the coordination between grip and load forces was disrupted. It appears from these data, that the internal model alone is insufficient to completely compensate for the loss of cutaneous sensation. Moreover, the results suggest that the internal model must have either continuous tonic excitation from cutaneous receptors or at least frequent intermittent reiteration to function optimally. A subsequent study performed with 10 additional subjects (9 women, 1 man; ages 24-49 yr) indicated that with unimpaired cutaneous feedback, the grasping and lifting forces were applied together with negligible forces and torques in other directions. In contrast, after digital anesthesia, significant additional linear and torsional forces appeared, particularly in the horizontal and frontal planes. These torques were thought to arise partially from the application of excessive grip force and partially from a misalignment of the two grasping fingers. These torques were further increased by an imbalance in the pressure exerted by the two opposing fingers. Vision of the grasping hand did not significantly correct the finger misalignment after digital anesthesia. Taken together, these results suggest that mechanoreceptors in the fingertips signal the source and direction of pressure applied to the skin. The nervous system uses this information to adjust the fingers and direct the pinch forces optimally for grasping and object manipulation.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».