Purpose: To investigate the differences in neural control of back muscles activated during the eccentric vs. the concentric portions of a cyclic, submaximal, fatiguing trunk extension exercise via the analysis of amplitude and time-frequency parameters derived from surface electromyographic (SEMG) data. Methods: Using back dynamometers, 87 healthy volunteers performed three maximum voluntary isometric trunk extensions (MVC's), an isometric trunk extension at 80% MVC, and 25 cyclic, dynamic trunk extensions at 50% MVC. Dynamic testing was performed with the trunk angular displacement ranging from 0° to 40° and the trunk angular velocity set at 20°/s. SEMG data was recorded bilaterally from the iliocostalis lumborum at L1, the longissimus dorsi at L2, and the multifidus muscles at L5. The initial value and slope of the root mean square (RMS-SEMG) and the instantaneous median frequency (IMDF-SEMG) estimates derived from the SEMG recorded during each exercise cycle were used to investigate the differences in MU control marking the eccentric vs. the concentric portions of the exercise. Results: During the concentric portions of the exercise, the initial RMS-SEMG values were almost twice those observed during the eccentric portions of the exercise. The RMS-SEMG values generally increased during the concentric portions of the exercise while they mostly remained unchanged during the eccentric portions of the exercise with significant differences between contraction types. Neither the initial IMDF-SEMG values nor the time-course of the IMDF-SEMG values significantly differed between the eccentric and the concentric portions of the exercise. Conclusions: The comparison of the investigated SEMG parameters revealed distinct neural control strategies during the eccentric vs. the concentric portions of the cyclic exercise. We explain these differences by relying upon the principles of orderly recruitment and common drive governing motor unit behavior.
Keywords: concentric exercise; eccentric exercise; electromyography; muscle fatigue; time-frequency analysis.