On Modeling Center of Foot Pressure Distortion Through a Medium
Notice bibliographique
Résumé
The center of foot pressure (COP) is a commonly used output measure of the postural control system as it is indicative of the systems stability. A dense piece of foam, i.e., a sponge, can be used to emulate random environmental conditions that distort the ground reaction forces received and interpreted by the cutaneous sensors in the feet; thus introducing uncertainty into the control system. In this paper, the density and size of the sponge was selected such that a subject's weight did not cause full compression. In general, the COP is measured from the bottom of the sponge. As the sponge is used to distort ground reaction forces, it is reasonable then to assume that the COP signal would also be distorted. The use of other sensory information to identify state of balance, and compute necessary balance adjustments, is therefore required. In addition to a sponge, many different types of specialized footwear and inserts are used for people with peripheral neuropathy, such as diabetics. However, it is difficult to design diabetic footwear without a better understanding of the mechanical and physiological effects that different surfaces typical of outdoor terrains, such as a sponge, which cannot be predicted without the sense of the foot, have on balance. Therefore, the goal of this study was to investigate the change of the COP signal from the top and bottom of the sponge. Portable force sensing mats from Vista Medical were used to obtain the COP from the top and bottom of the sponge. The COP measured on the bottom of the sponge is not the same as the COP measured on the top, particularly in the medial-lateral direction. Several linear and nonlinear models were used to identify the unknown plant; i.e., the sponge. Overall, the nonlinear neural network method had superior performance when compared with the linear models. Thus, the results indicate that the signals from the top and bottom of the sponge are in fact different, and furthermore, they are nonlinearly related. A nonlinear mathematical model is proposed which describes COP distortion through a medium such as a sponge. Although the values for the model parameters determined were for a particular sponge, this study suggests that a neural network plant identification model may be applied to any medium other than the sponge; the information can then be used to determine how the balance control model is affected given the sensory information received.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».