We explored possible effects of negative covariation among finger forces in multifinger accurate force production tasks on the classical Fitts’s speed-accuracy trade-off. Healthy subjects performed cyclic force changes between pairs of targets “as quickly and accurately as possible.” Tasks with two force amplitudes and six ratios of force amplitude to target size were performed by each of the four fingers of the right hand and four finger combinations. There was a close to linear relation between movement time and the log-transformed ratio of target amplitude to target size across all finger combinations. There was a close to linear relation between standard deviation of force amplitude and movement time. There were no differences between the performance of either of the two “radial” fingers (index and middle) and the multifinger tasks. The “ulnar” fingers (little and ring) showed higher indices of variability and longer movement times as compared with both “radial” fingers and multifinger combinations. We conclude that potential effects of the negative covariation and also of the task-sharing across a set of fingers are counterbalanced by an increase in individual finger force variability in multifinger tasks as compared with single-finger tasks. The results speak in favor of a feed-forward model of multifinger synergies. They corroborate a hypothesis that multifinger synergies are created not to improve overall accuracy, but to allow the system larger flexibility, for example to deal with unexpected perturbations and concomitant tasks.
Stacey L. Gorniak, Marcos Duarte, and Mark L. Latash
Samantha L. Winter and John H. Challis
For a physiologically realistic joint range of motion and therefore range of muscle fiber lengths, only part of the whole muscle force-length curve can be used in vivo; that is, only a section of the force-length curve is expressed. Previous work has determined that the expressed section of the force-length curve for individual muscles can vary between subjects; however, the degree of intersubject variability is different for different muscles. This study determined the expressed section of both the rectus femoris and gastrocnemius—muscles with very different ratios of tendon slack length to muscle fiber optimum length—for 28 nonspecifically trained subjects to test the hypothesis that the value of this ratio affects the amount of variability in the expressed section. The force-length curves of the two muscles were reconstructed from moment-angle data using the method of Herzog & ter Keurs (1988). There was no relationship between the expressed sections of the force-length curve for the two muscles. Less variability was found in the expressed section of the gastrocnemius compared with the rectus femoris, supporting the hypothesis. The lack of relationship between the expressed sections of the two muscles has implications for motor control and for training muscle for rehabilitation.
This study investigated the possible role of the corticospinal system during force generation and force relaxation. Nine young and healthy subjects were instructed to produce a total force with four fingers within a hand following a preset force generation and relaxation ramp template closely. Excitability of corticospinal (CS) projections was assessed by single- and paired-pulse TMS. Errors introduced by a finger force were partially compensated by other finger forces during force generation, but were amplified during force relaxation. The CS excitability was greater during force generation than maintenance or relaxation. No difference in intracortical inhibition or facilitation was found. Nonnormalized finger extensor EMG responses remained unchanged. The findings suggest that force relaxation is not just a withdrawal from activation, and multifinger interactions are likely controlled beyond the primary motor cortex.
Abderrehmane Rahmani, Georges Dalleau, Fabrice Viale, Christophe A. Hautier, and Jean-René Lacour
This study determined the validity and reliability of the kinematic device developed by Bosco et al. (1995) by comparing its peak force, peak velocity, and peak power measurements to data obtained simultaneously with a force platform placed under the subject’s feet. Fifteen international downhill skiers performed maximal half-squats on a guided barbell with masses of 60–180 kg. The coefficient of correlation (r) between the two peak forces (r = 0.85–0.95, p < .001), the two peak velocities (r = 0.74–0.91, p < .001), and the two peak powers (r = 0.85–0.95, p < .001) indicated that the kinematic device measurements were valid. The trial-to-trial reliability of half-squat exercises measured by the kinematic device gave an intraclass coefficient of correlation (CR) of: 0.70-0.90 for peak force, 0.62-0.90 for peak velocity, and 0.57-0.91 for peak power. There were no statistical differences between the two trials. The standard error of the means (SEM%) was less than 5% for peak force, less than 4% for peak velocity, and less than 7% for power. The high CR and low SEM% indicate that the kinematic device is reliable. The movement recorded by the kinematic device accurately described the action measured by the force platform.
Kreg G. Gruben, Lynn M. Rogers, Matthew W. Schmidt, and Liming Tan
The force that healthy humans generated against a fixed pedal was measured and compared with that predicted by four models. The participants (n = 11) were seated on a stationary bicycle and performed brief pushing efforts against an instrumented pedal with the crank fixed. Pushes were performed to 10 force magnitude targets and at 12 crank angles. The increasing magnitude portion of the sagittal-plane force path for each push effort was fitted with a line to determine the direction of the muscle component of the foot force. Those directions varied systematically with the position of the pedal (crank angle) such that the force path lines intersected a common region superior and slightly anterior to the hip. The ability of four models to predict force path direction was tested. All four models captured the general variation of direction with pedal position. Two of the models provided the best performance. One was a musculoskeletal model consisting of nine muscles with parameters adjusted to provide the best possible ft. The other model was derived from (a) observations that the lines-of-action of the muscle component of foot force tended to intersect in a common region near the hip, and (b) the corresponding need for foot force to intersect the center-of-mass during walking. Thus, this model predicted force direction at each pedal position as that of a line intersecting the pedal pivot and a common point located near the hip (divergent point). The results suggest that the control strategy employed in this seated pushing task reflects the extensive experience of the leg in directing force appropriately to maintain upright posture and that relative muscle strengths have adapted to that pattern of typical activation.
Kreg G. Gruben, Lynn M. Rogers, and Matthew W. Schmidt
Control of the force exerted by the foot on the ground is critical to human locomotion. During running on a treadmill and pushing against a fixed pedal, humans increased foot force in a linear manner in sagittal plane force space. However, for pushes against a moving pedal, force output was linear for some participants but slightly curved for others. A primary difference between the static and dynamic pedaling studies was that the dynamic study required participants to push with varying peak effort levels, whereas a constant peak effort level was used for the fixed pedal pushes. The present study evaluated the possibility that force direction varied with level of effort. Seated humans pushed against a fixed pedal to a series of force magnitude targets. The force direction varied systematically with effort level consistent with the force path curvature observed for dynamic pedaling.
Rafael F. Escamilla, Naiquan Zheng, Toran D. MacLeod, Rodney Imamura, Shangcheng Wang, Kevin E. Wilk, Kyle Yamashiro, and Glenn S. Fleisig
pain syndrome (PFPS). 7 – 11 High patellofemoral joint force (and stress, which is force divided by contact area) may result in PFPS from numerous soft tissues, such as synovial plicae, infrapatellar fat pad, retinacula, joint capsule, and patellofemoral ligaments. 12 High patellofemoral joint force
Joseph J. Crisco, Nikolas J. Osvalds, and Michael J. Rainbow
and Statistical Analysis Peak force, peak moment, time of peak force, time of peak moment, time of 50% peak force, and time of 50% peak moment were computed and compared among bat models. A 1-way (bat model) analysis of variance with a Kruskal–Wallis test on ranks was used to examine the significance
Antonio Dello Iacono, Stephanie Valentin, Mark Sanderson, and Israel Halperin
Sport scientists and applied practitioners regularly monitor and prescribe training programs based on assessments of force production tests. Two examples of such tests are the isometric midthigh pull (IMTP) and the isometric squat tests. 1 , 2 Both require subjects to stand on a force plate and
Alejandro Pérez-Castilla, Belén Feriche, Slobodan Jaric, Paulino Padial, and Amador García-Ramos
The force platform is recognized as the ‘gold standard’ for testing vertical jumps. 1 – 3 The force platform estimates the velocity and power of the system center of mass from the directly recorded vertical ground reaction force data using the direct dynamic approach. Due to potential