Visual Inputs and Motor Outputs as Indivduals Walk Through Dynamically Changing Environments
Notice bibliographique
Résumé
Walking around in dynamically changing environments require the integration of three of our sensory systems: visual, vestibular, and kinesethic. Vision is the only modality of these three sensory systems that provides information at a distance for proactively controlling locomotion (Gibson, 1958). The visual system provides information about self-motion, about body position and body segments relative to one another and the environment, and environmental information at a distance (Patla, 1998). Gibson (1979) developed the idea that everyday behaviour is controlled by perception-action coupling between an action and some specific information picked up from the optic flow that is generated by that action. Such that visual perception guides the action \nrequired to navigate safely through an environment and the action in turn alters perception. The objective of my thesis was to determine how well perception and action are coupled when approaching and walking through moving doors with dynamically changing apertures. My first two studies were grouped together and here I found that as the level of threat increased, the parameters of control changed and not the controlling mechanism. The two dominant action control parameters observed were a change in approach velocity and a change in posture (i.e. shoulder rotation). These findings add to previous work done in this area using a similar set-up in virtual reality, \nwhere after much practice participants increased success rate by decreasing velocity prior to crossing the doors. In my third study I found that visual fixation patterns and action parameters were similar when the location of the \naperture was predictable and when it was not. Previous work from other researchers has shown that vision and a subsequent action are tightly coupled with a latency of about 1second. I have found that vision only tightly \ncouples action when a specific action is required and the threat of a collision increases. My findings also point in the same direction as previous work that has shown that individuals look where they are going. My last study \nwas designed to determine if we go where we are looking. Here I found that action does follow vision but is only loosely correlated. The most important and common finding from all the studies is that at 2 seconds prior to crossing the moving doors (any type of movement) vision seems to have the most profound effect on action. At this time variability in action is significantly lower than at prior times. I believe that my findings will help to understand how individuals use vision to modify actions in order to avoid colliding with other people or other moving objects within the environment. And this knowledge will help elderly individuals to be better able to cope with walking \nin cluttered environments and avoid contacting other objects.
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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 | 0,004 |
| 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 | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».