Notice bibliographique
Résumé
For researchers, surface electromyography (EMG) seems a seductive technology because it provides a non-invasive means to acquire in-vivo data about physiological processes that cause muscles to produce movement. It captures muscle activity during any movement of a body by measuring seizure potentials released by the muscles when they are activated. Consequently, measured potentials are typically used to fractionate a body’s response process as well as get timing of neural control and coordination among muscle groups. Such analyses permit assessments of technical skills which, in turn, provide foundational information for biofeedback training and development of new pedagogical methods. Consequently, in high-skill activities such as those of the performing arts, EMG would appear to have significant relevance in terms of skill optimization and learning. On the surface, it is apparent that arts performance shares many characteristics, including health risks, with an area where EMG research has already had a significant disciplinary impact – sports (Chesky, et al., 2002; Lehmann & Davidson, 2002; Wilson, 1986). Pedagogy and training in both sports and performance arts aim to develop physical skills efficiently while avoiding injury for participants. While EMG applications in human sports movements have been an acknowledged aid in improving sport performance for decades (e.g. the Journal of Electromyography and Kinesiology has a 21-year history in this regard), applications in arts performances are still rare. Further, a review of the literature shows that, EMG applications in the arts tend to fall into only three broad categories: skill analysis descriptions and establishment of norms, training method evaluations, biofeedback in both pedagogy and injury remediation (Kjelland, 2000). This book chapter details selected examples where EMG technology is used in applications pertinent to arts performance. Since almost all EMG studies rely upon initial skill analysis and description in order to establish norms, research in the performance arts is often a multi-stage process. Exemplars for purposes of discussion will be drawn from instrumental and vocal performance, as well as ballet. The goals of the selected research focus on: 1) describing the activity of selected muscles, 2) identifying innate abilities or talents, 3) quantifying the efficiency and effectiveness of pedagogical methods, 4) diagnosing technical difficulties, or 5) determining loading intensity during performance and evaluating factors related to pain and injury. Given the small body of existing EMG studies in the arts, the examples below are mainly chosen to elaborate the potential and relevance of EMG research in the performing arts as well as to encourage more research in the area.
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) | 0,001 | 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) | 0,000 | 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 ».