logo
ResearchBunny Logo
Strength gains by motor imagery with different ratios of physical to mental practice

Health and Fitness

Strength gains by motor imagery with different ratios of physical to mental practice

M. Reiser, D. Büsch, et al.

Explore the groundbreaking study on motor imagery in strength training conducted by Mathias Reiser, Dirk Büsch, and Jöm Munzert. Discover how incorporating imagined contractions can yield significant strength gains while potentially reducing the need for high-intensity workouts.

00:00
00:00
~3 min • Beginner • English
Abstract
Publisher
Frontiers in Psychology
Published On
Aug 19, 2011
Authors
Mathias Reiser, Dirk Büsch, Jöm Munzert
DOI
https://doi.org/10.3389/fpsyg.2011.00194
Tags
motor imagery
strength training
maximum voluntary contraction
isometric contraction
exercise intervention

Related Publications

Explore these studies to deepen your understanding of the subject.

Leveraging the effector independent nature of motor imagery when it is paired with physical practice
Psychology

Leveraging the effector independent nature of motor imagery when it is paired with physical practice

S. N. Kraeutner, J. L. Mcarthur, et al.

Different motivation, different achievements: the relationship of motivation and dedication to academic pursuits with final grades among Jewish and Arab undergraduates studying together
Education

Different motivation, different achievements: the relationship of motivation and dedication to academic pursuits with final grades among Jewish and Arab undergraduates studying together

E. Gill, O. Guterman, et al.

Not with the bot! The relevance of trust to explain the acceptance of chatbots by insurance customers
Business

Not with the bot! The relevance of trust to explain the acceptance of chatbots by insurance customers

J. D. Andrés-sánchez and J. Gené-albesa

Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods
Biology

Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods

T. Yuan, N. Yan, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny