El Taller como construcción colectiva de aprendizaje

As previously outlined in this review single muscle fibers and single muscles (i.e. single joint movements), exhibit a F-V relationship that is hyperbolic (Perrine & Edgerton, 1978; Thorstensson et al., 1976a; Wilkie, 1950). Although, the nature of this relationship differs when the movement being performed involves multiple joints and muscles such as half-squats (Rahmani et al., 2001), leg press (Bobbert, 2012; Samozino et al., 2012), arm cranking (Driss et al., 1998; Jaafar et al., 2015), jumping (Bobbert & Van Ingen Schenau, 1990) and cycling (Bobbert et al., 2016). The shape of the relationship between external force and velocity obtained during these multi-joint exercises is usually described as linear or “almost linear” (Bobbert, 2012). It has been proposed that neural factors may account for the shift from a hyperbolic to linear appearance in voluntary movements of greater complexity (Yamauchi et al., 2007). A recent

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review by Jaric (2015) outlined that the F-V relationships of maximal multi-joint movements (including cycling) appear to be reliable, valid and accurate enough to detect differences in maximal force, maximal power and maximal velocity within and between sporting and clinical populations. However, in the case of maximal leg cycling, there is a lack of consensus regarding the most appropriate way to model and therefore characterise the shape of T-C and P-C relationships (see Table 2.1).

The earliest study by Dickinson in 1928 described the relationship between cadence and braking force as linear. Studies conducted some years later using an isokinetic cycle ergometer showed that the relationship between torque and cadence was linear (Sargeant et al., 1981). Thereafter, in the majority of studies, researchers have predicted T-C relationships using linear regressions, while P-C relationships were consequently characterised using symmetrical parabolas (i.e. second order polynomial/quadratic regressions) (Dorel et al., 2010; Dorel et al., 2005; Gardner et al., 2007; Hintzy et al., 1999; Martin et al., 1997; McCartney et al., 1985; Samozino et al., 2007) as depicted in Figure 2.5B. Maximal T-C and P-C relationships have also been described during the acceleration phase (i.e. downstroke) of a single all-out exercise (Seck et al., 1995). Further, one study applied the same method of prediction, to describe the P-C and T-C relationships for different phases of the pedalling movement, allowing cadence-specific power and torque to be calculated during the downstroke (i.e. 0-180° of a pedal cycle) and

upstroke (180-360° of a pedal cycle) (Dorel et al., 2010).

However, as presented in a paper by Vandewalle et al. (1987) the force-velocity relationship during cycle ergometry was suggested to exhibit an approximately linear relationship, as the force values obtained at heavy and light braking forces were downwardly inflected. In later studies, some researchers opted to employ higher order polynomials to predict T-C and P-C relationships using second and third order polynomials/cubic regressions respectively, refuting simple linear and symmetrical parabola shapes (Arsac et al., 1996; Hautier et al., 1996; Yeo et al., 2015). The earliest of these studies demonstrated that a higher order regression provided systematically higher r values compared with a linear function (0.96 ± 0.02 vs 0.91 ± 0.04) for T- C relationships (Arsac et al., 1996). Although different modelling procedures were not investigated for P-C relationships, as a consequence of second order polynomials employed for T-C relationships, these researchers used a third order polynomial to characterise P-C relationships, which resulted in individual r values between 0.95 and 0.99. In a more recent study by Yeo et al. (2015) T-C relationships were well fit with second order polynomials (r2 of 0.99 for both conditions), while third order polynomials provided a good fit for P-C relationships (r2 of 0.97 for both conditions). Other than the loose investigation of regression order comparison by Arsac and colleagues (1996), it appears that no direct comparison between the different modelling procedures typically employed in the literature has been conducted previously.

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Considering the results reported from F-V tests of other movements, the implementation of higher order polynomials may offer greater flexibility for modelling T-C and P-C relationships, providing a more comprehensive approach for characterising the shapes of these relationships (and the calculation of the limits of NMF). Recently, Bobbert (2012) showed that the force vs velocity relationship was not perfectly linear for maximal leg press, a multi-joint movement requiring a low level of external force control. As depicted in Figure 2.5B the dotted line on the F-V relationship indicates the reduction in total external force observed by Bobbert at high forces and high velocities. Considering that maximal leg cycling is a multi-joint movement requiring a high level of external force control, the possibility that T-C relationships may be better predicted using non-linear regressions while the P-C relationships may be better predicted using parabolas of asymmetrical shapes cannot be ruled out. Similarly, due to the complexity of dynamic, poly- articular movements such as maximal cycling, it seems very plausible that not every individual would exhibit exactly the same shaped T-C and P-C relationships.

According to previous studies, a variety of phenomena (discussed in section 2.3.1 above) could potentially cause the shape of T-C relationships to deviate from linearity and the shape of P-C relationships to deviate from a symmetrical parabola in maximal cycling. Previous findings suggest that torque and power production may be limited by neural inhibitions (Babault et al., 2002; Perrine & Edgerton, 1978; Westing et al., 1991; Yamauchi et al., 2007) and/or non-maximal skeletal muscle potentiation (Robbins, 2005) when producing maximal pedalling movements at low cadences. While pedalling at high cadences, torque and power production could be limited by activation-deactivation dynamics (van Soest & Casius, 2000), alterations in the motor control strategy (McDaniel et al., 2014).