等长运动
蹲下
大腿
物理医学与康复
医学
解剖
物理疗法
作者
Lachlan P. James,Charlie J. Davids,Tomas Rodriguez-Anderson,Haresh Suppiah,Benjamin F. Mentiplay
标识
DOI:10.1519/jsc.0000000000005198
摘要
ABSTRACT: James, LP, Davids, CJ, Rodriguez-Anderson, T, Suppiah, HT, and Mentiplay, BF. A comparison of force-time and muscle activation characteristics between the isometric squat and isometric mid-thigh pull. J Strength Cond Res 39(11): e1265-e1271, 2025-This investigation sought to establish the commonality of force-time curve characteristics between the isometric mid-thigh pull (IMTP) and isometric squat. In addition, the magnitude and timing of muscle activation (electromyography [EMG]) were examined at corresponding points on the force-time curve. Fifteen individuals (male: n = 12; age, 25.6 ± 4.7 years; body mass: 84.3 ± 9.2 kg; female: n = 3; age; 23.5 ± 4.9 years, body mass; 63.8 ± 12.4 kg) performed trials of the IMTP and the isometric squat while simultaneous measures of muscle activation were collected from the vastus medialis [VM], vastus lateralis [VL], biceps femoris [BF], and latissimus dorsi [LD]. A shared variance ( r2 ) of 74% was found for net peak force between tests. A shared variance of 27-48% was demonstrated for early stage measures of force up to 200 ms from onset. Large (VM, VL) to very large (BF, LD) significant relationships for mean EMG were revealed between conditions. Large to very large significant relationships for each EMG epoch were present between conditions for VM and LD. Larger and significantly greater mean muscle activation of the BF occurred in the IMTP. Peak force from the IMTP and isometric squat represent a common aspect of maximal strength. However, given the limited commonality between tests for early force-time characteristics, performance in 1 condition should not be considered representative of performance in the other condition across these measures. Practitioners interested in greater hamstring contribution to lower body maximal strength may prefer the IMTP.
科研通智能强力驱动
Strongly Powered by AbleSci AI