Visual cueing: Does it produce an acute improvement in turning in a Parkinsonian sample?
Notice bibliographique
Résumé
Anticipatory eye movement promotes cranio-caudal sequencing during walking turns, reducing the risk of falls. Individuals with Parkinson’s disease (PD) have difficulty producing anticipatory eye movements which may limit cranio-caudal rotation sequencing during turning. Visual cues have the potential to promote anticipatory eye movement and cranio-caudal sequencing by guiding the eyes into the turn. The purpose of this study was to examine if discrete external visual cues could train anticipatory eye movement and cranio-caudal rotations during walking turns. We hypothesized that visual cues would have limited effects on a sample of neurotypical young adults (NYA), but would improve anticipatory eye movement and cranio-caudal sequencing in a sample group with PD. \n 10 NYA (20-30 years) and 6 PD (45-75 years; Hoehn and Yahr 1-3) completed three blocks of walking trials with a 90-degree left turn. Trials were blocked by visual condition: non-cued baseline turns (5 trials), visually cued turns (10 trials), and non-cued retention turns (5 trials). A Delsys Trigno (Delsys, Boston, MA) captured horizontal saccades at 1024 Hz via electrooculography (EOG). Two Optotrak cameras (Northern Digital Inc., ON, Canada) captured head, trunk, pelvis and feet kinematics at 120 Hz. Timing of segment rotation with respect to ipsilateral foot contact (IFC1) prior to the turn was calculated using angular displacement and velocity about the vertical axis. \n As expected, NYA produced typical cranio-caudal rotation sequences during baseline walking turns. Eyes led (407 ms prior to IFC1), followed by the head (99 ms prior to IFC1), and trunk (151 ms after IFC 1). Onset time between adjacent segments was significantly different (p = 0.018 and p = 0.021 respectively). Effects of visual cuesin NYA were minimal with some coupling of the eyes and head occurring (210 ms and 237 ms prior to IFC1) due to requirements to follow visual targets on approach to the turn. Trunk segment rotation remained significantly later (p = 0.001; 149 ms after IFC1). In contrast, PD produced no anticipatory eye or segment movement in baseline trials. Head rotation began 57 ms after IFC1 followed by the eyes and trunk (97ms and 323 ms after IFC1) with no significant differences between segments. However, following visual cue training (during retention trials), PD produced cranio-caudal rotation with anticipatory eyes movement at 161 ms prior to IFC1, followed by the head 106 ms prior to IFC1 and trunk 289 ms after IFC1 with a significant difference between head and trunk segments (p=0.048). \n Results suggest discrete external visual cues during walking turns assist PD in producing cranio-caudal rotation sequencing in trials following visual cue training. Interestingly, when visual cues are present, greater coupling between the eyes and head occur with the head often leading eye movement. Therefore, appearance of visual targets and instructions to follow visual targets are critical to consider when evaluating their use for turning movements. These findings provide an interesting starting point for the use of visual cues to specifically promote cranio-caudal segment coordination during walking\nturns to reduce risk of falls.
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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 | 0,000 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».