PubMed · 5381230
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B Swart, W Dingendorf, H D Kappe. 1969. [Basic principles of tomographic practice].. https://pubmed.ncbi.nlm.nih.gov/5381230/
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This study tested the hypothesis that eccentric exercise (ECC) would increase force fluctuation for several days following exercise; however, concentric exercise (CON) would not produce such an effect. Twelve men performed six sets of five reps of dumbbell exercise of the elbow flexors eccentrically with one arm and concentrically with the other, separated by 4-6 weeks, using a dumbbell set at 50% of maximal voluntary isometric contraction (MVC) measured at 90 degrees of elbow flexion. MVC, range of motion (ROM), upper arm circumference, plasma creatine kinase activity (CK), myoglobin concentration (Mb) and muscle soreness were assessed before, immediately after, 1 h and 1-5 days following both exercise bouts. Force fluctuations during 30, 50 and 80% MVC were quantified by coefficient of variation (CV) of the force data (sampling frequency: 100 Hz) for 4 s. Significantly (P < 0.01) larger changes in MVC, ROM, and upper arm circumference were evident following ECC compared to CON, and only ECC resulted in significant (P < 0.01) increases in CK and Mb, and development of muscle soreness. Significant (P < 0.01) differences existed between ECC and CON for changes in force fluctuations. CV increased significantly (P < 0.01) immediately and 1 h after ECC from baseline for 30, 50, and 80% MVC without a significant difference among the intensities, and no significant changes in CV were evident following CON. It was concluded that increases in force fluctuation were peculiar to ECC, but did not necessarily reflect muscle damage.
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Changes in the kinematic and electromyographic characteristics that occur while learning to move as fast as possible have been studied experimentally. Experimental investigation of what happens to the individual motor units (MUs) is more difficult. Access to each MU is impossible, and the recruitment and force developing properties of all individual MUs cannot be known. Thus, what is currently known about MU firing is based on experiments that have recorded relatively few MUs compared to what exists in the entire muscle. A recently developed muscle model (Raikova and Aladjov, 2002, J. Biomechanics, 35, 1123-1135) composed of MUs with different properties can be used for such investigation. The process of learning fast elbow flexion in the horizontal plane was simulated and the results were compared with experimentally measured data. Comparing the simulation results of the very first trial of a particular subject with those of the last trail (at the end of the learning process), it can be concluded that the speed of limb motion and muscle forces increase initially as a result of the more synchronous MUs activation and the increase of firing rate of active MUs. Further improvement necessitated an appreciable reduction in the motor task requirements (i.e. less muscle force and less MUs' activity) set in the computational algorithm by optimization criteria. This forced the next process-inclusion of additional MUs.