Torna ai risultati
Scheda bibliografica · Consultazione e accesso
Artículo

A Novel Approach to Analyzing Wrestling Skills: Multidimensional Recurrence Quantification Analysis of Muscle Activity

Kazem Esfandiarian-Nasab et al · Shiraz University of Medical Sciences · 2026

Materiale supplementare disponibile
Lettura rapida. Controlla i dati essenziali della risorsa e accedi al contenuto con il pulsante principale. La scheda mostra solo le informazioni necessarie per identificare, citare e aprire l’opera.

Accesso alla risorsa

Apri il contenuto dall’opzione principale o scegli un’altra fonte disponibile.

DOAJ DOAJ Articles
Entrar por DOAJ
Accesso principale

Materiale supplementare disponibile

El enlace apunta a material asociado, anexos, tablas, datos o página complementaria. No se marca como libro/texto completo.
Apri materiale

Riepilogo

Descripción general del contenido del recurso.

Background: As athletes develop, their motor patterns evolve from variable to adaptive neuromuscular control strategies, enabling precise execution of complex movements. Traditional linear biomechanical analyses of wrestling techniques often focus on averaged data points, overlooking motor pattern variability and nonlinear dynamic characteristics. Understanding these nonlinear dynamics can enhance skill acquisition, injury prevention, and training optimization. This study is the first to apply multidimensional recurrence quantification analysis (MDRQA) of electromyography (EMG) signals to compare motor patterns in elite and sub-elite wrestlers during a shadow freestyle tie-up drill (SFTUD).Methods: This cross-sectional, descriptive-analytical observational study recorded EMG signals from the triceps, biceps, anterior deltoid, and latissimus dorsi of the dominant upper limb during a 15-second SFTUD. Determinism (%DET) and laminarity (%LAM) were used to assess repeatability and stability, while diagonal (EntL) and vertical (EntV) entropy measured complexity and adaptability.Results: Elite wrestlers exhibited significantly higher %DET and %LAM, indicating greater consistency in their motor patterns. Elevated EntL and EntV values further suggest enhanced complexity and adaptability in neuromuscular control, reflecting the chaotic dynamics associated with superior performance.Conclusion: These findings underscore the importance of nonlinear motor pattern dynamics in the development of wrestling skill. MDRQA can identify expertise-related movement patterns, enabling coaches and practitioners to design targeted training programs that optimize performance and reduce injury risk.

Come citare

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

al, K. E. N. E. (2026). A Novel Approach to Analyzing Wrestling Skills: Multidimensional Recurrence Quantification Analysis of Muscle Activity. https://doi.org/10.30476/jrsr.2025.105002.1539

MLA

al, Kazem Esfandiarian-Nasab et. "A Novel Approach to Analyzing Wrestling Skills: Multidimensional Recurrence Quantification Analysis of Muscle Activity." 2026. https://doi.org/10.30476/jrsr.2025.105002.1539.

Chicago

al, Kazem Esfandiarian-Nasab et. 2026. "A Novel Approach to Analyzing Wrestling Skills: Multidimensional Recurrence Quantification Analysis of Muscle Activity.". https://doi.org/10.30476/jrsr.2025.105002.1539.

Harvard

al, K. E. N. E. 2026, A Novel Approach to Analyzing Wrestling Skills: Multidimensional Recurrence Quantification Analysis of Muscle Activity, Shiraz University of Medical Sciences, available at: https://doi.org/10.30476/jrsr.2025.105002.1539 [Accessed 7 Aug. 2026].

Condividi e stampa

Salva la scheda, copia il link permanente o stampala in PDF.

Esporta riferimento

Esporta il record nei formati più comuni per usarlo con un gestore bibliografico.

Dettagli della risorsa

Informazioni bibliografiche utili per verificare che sia il materiale corretto.

Titolo
A Novel Approach to Analyzing Wrestling Skills: Multidimensional Recurrence Quantification Analysis of Muscle Activity
Autore / collaboratori
Kazem Esfandiarian-Nasab et al
Editore
Shiraz University of Medical Sciences
Anno di pubblicazione
2026
ISSN
2345-6167
ISSN
2345-6167
Lingua
Inglés

Soggetti

Esplora risorse correlate a partire da questi soggetti.

Copiato