1. The contribution to muscle force regulation provided by reflex pathways was studied in the elbow flexor muscles of seven normal human subjects, with the use of voluntary fatigue to induce a deficit in the force-generating capability of these muscles. To estimate the changes in the mechanical state of the muscle and the compensatory actions taken by reflex pathways to minimize the impact of fatigue, stochastic and 'step' angular perturbations were applied to the joint, and the resulting joint stiffness and electromyographic (EMG) responses were compared before and after fatigue. 2. The magnitude of contractile fatigue, induced by repeatedly lifting a weight via a pulley system, was quantified by comparing the slope of the isometric torque-EMG relationship before and after fatigue. The exercise routine was quite effective in producing severe and long-lasting fatigue, with average percentage changes in the isometric torque-EMG slope of 210-306% for biceps and 129-205% for brachioradialis, depending on the point in time examined. 3. The torque response to a rapid step stretch of the elbow joint was quite similar before and after fatigue for the time interval before reflex action (<20 ms after stretch onset), suggesting that intrinsic muscle stiffness for a given mean torque level was not changed by fatigue. The steady-state torque level attained after completion of the stretch was always decreased after fatigue, indicating a decrease in the reflex component of joint stiffness, but this decrease was small compared with the change in the isometric torque- EMG relationship and was accompanied by a significantly larger incremental EMG response after fatigue. This increase in incremental EMG after fatigue was found to be of reflex origin, with activation-related reflex gain changes apparently playing a significant role only at low contraction levels. 4. Torque and angle responses recorded during stochastic perturbations were used to identify elbow joint compliance impulse responses. A second-order mechanical model was fit to each impulse response, and the parameters representing joint inertia, elastic stiffness, and viscous stiffness were used to summarize changes in joint mechanical properties as the mean contraction level was varied. For a perturbation with a relatively wide bandwidth (0-25 Hz), fatigue had little or no effect on the form of the compliance impulse response, apparently because the stimulus disabled reflex force generation in elbow flexor muscles, whereas a perturbation with a more restricted bandwidth (0-10 Hz) demonstrated consistent decreases in joint stiffness after fatigue. Most (>90%) of this decrease in stiffness was attributable to a decrease in the elastic component, with only small and variable changes in viscous stiffness observed. As with step responses, the decreases in stiffness were small compared with isometric torque-EMG changes, and EMG responses elicited by stochastic perturbations of either bandwidth were significantly increased after fatigue, both in absolute magnitude and in the gain of the input-output relationship between the perturbation angle and the resulting EMG, especially for the heavily fatigued biceps muscle. 5. The mechanical and EMG responses obtained from both step and stochastic perturbations were consistent with the actions of a force-regulating feedback mechanism. Force feedback loop gains were estimated for the low bandwidth stochastic perturbation by the use of two different techniques, each of which gave broadly similar results. Average loop gains across all seven subjects of 1.27-4.61 were computed, depending on the method used and the assumptions made. Loop gain estimates from step perturbations were somewhat larger, averaging 8.31, but still within the same range. 6. These large loop gain values indicate that force regulation significantly reduces the sensitivity of the overall neuromuscular system to fatigue (by 56-89%) and imply that force regulation may be an important component of the overall reflex control of muscle contraction during nonfatiguing conditions as well.
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