Assessing the Influence of Elastic Recovery in a Stretch-Shortening Cycle Task: A Muscle Modelling Approach

Abstract

A Hill-based muscle model was used to assess the influences of series elastic recovery in stretch-shortening cycle (SSC) contractions at the human elbow. Elbow torque, EMG and joint kinematics were recorded as eight male subjects performed a vari ety of elbow flexion and extension tasks. A significant performance enhancement was observed in SSC vs non-SSC elbow flexions (20% greater angular impulse). The muscle model used activation-force, length-tension and force-velocity functions to estimate instantaneous elbow flexor and extensor moments. These moments were summed with a passive elbow moment to obtain estimates of net elbow moment and angular impulse. The estimated values were compared to actual measures of joint torque and angular impulse. The model accurately estimated the angular impulse generated by non-SSC contractions, but demonstrated substantial underestimation errors in SSC contractions. The majority of the SSC performance enhancement could not be attributed to either neural potentiation or to a better exploitation of contractile component mechanics. Since the model was designed to account for these influences but did not possess an ability to account for series elastic recovery, the performance enhancement which was not accounted for by the model was attributed to the recovery of strain energy stored in the SEC of the flexor muscles during the stretch phase. Past studies of SSC enhancement in voluntary movements have been unable to discern between the influences of elastic recovery, neural potentiation and other SSC phenomena. The methods employed in this study permitted the influence of elastic energy recovery to be partitioned from a net SSC performance enhancement. The results indicate that elastic recovery can play an important role in human movement, and that Hill-based muscle models offer a useful tool for studying physiological phenomena which can not be isolated experimentally.