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In the present study, the activity of isolated motor units (MUs) in the rat soleus (SOL) muscle was evoked by stimulation of thin filaments of ventral roots using constant and irregular frequency stimulation patterns. The MUs force, action potentials, and mechanomyograms (MMG) were recorded. MMG profiles were recorded with a laser distance sensor (LDS), categorized and compared with profiles obtained in a similar experiment performed on the medial gastrocnemius (MG) muscle. The profiles and amplitudes of the MMG signal vary greatly depending on the type of stimulated MU, contraction, and LDS localization. Compared to previously obtained results for MG, where three general types of MMG signal were distinguished, in the case of SOL the signal polyphasic signal profile was observed for weak contraction. The steady‑state MMG‑contraction force relationship could be successfully approximated with a third‑order polynomial model. Nevertheless, the model parameters were not constant and changed with stimulation type. The observed phenomena were also analyzed with a 3D model utilizing the Finite Element Method. In vivo and simulation results suggested that MMG was an effect of superposition of several movements types evoked by contraction (muscle belly rotation, transverse shearing due to non-axial localization of MUs, local surface deformation). The proposed model set to explain the most likely origins of differences in the MMG profile between MG and SOL muscles. These observations were used to create a novel method of transcutaneous MMG measurement, based on 9‑degree of freedom inertial sensors. The technique was applied to the classification of 6 hand gestures based on the MMG signal.
Mechanomyogram (MMG) detects the muscle surface oscillations due to the mechanical activity of the motor units (MU). Even during static contractions MMG presents macro components (due to the gross dimensional changes of the muscle-tendon unit from rest to activity) and micro components (the summation of the dimensional changes of the fi bres of each recruited motor unit). The single MU mechanical contribution to MMG (MUMC) was defi ned by Gordon and Holbourn a the ‘‘mechanical counterpart” of the MU action potential. During voluntary contraction MUMC and MU twitch (MUT) can be extracted from MMG and force ripple signal by means of the EMG driven spike triggered averaging technique. In small hand muscles during 5% of the maximal voluntary isometric contraction (MVC) the values of MUMCs and MUTs were around 11 mm/s2 and 7 mN, respectively. Already at these low effort levels the summation in MMG of single MUMCs of the recruited MUs is not linear. This may be due to the long duration of the MUMCs and to the changes in the muscle transverse and longitudinal compliance to mechanical stress determined by the overall MUs activity. On this basis the meaning of the MMG and force ripple oscillations (when larger of the peak to peak noise of the signals during rest and of the MUCMs and MUTs reported for single MUs) with respect to the MUs driving program has to be deeply investigated. This could be done by a cross analysis with the EMG which may partly disclose the central nervous system MUs activation strategy.
Aim of the work was to verify if the sinusoidal modulation of the stimulation rate of individual rat MUs may provide reliable sinusoidal responses of the recorded force with an acceptable harmonic distortion (HD). After MU classification, the isolated axons of the spinal ventral roots were electrically stimulated with rates sinusoidally changing, from a minimum to a maximum value, with different frequencies of modulation for slow (0.4–1.0–2.0–4.0 Hz) and fast (1.0–2.0–4.0–7.0 Hz) MUs. From the twitching raw signal an interpolated force curve was obtained for each frequency to generate, from the sample by sample difference with the theoretical sine, the specific error signal. At each input frequency, HD was calculated as the percentage ratio between the total power of the error signal and the total power of the theoretical sine. Nine MUs, characterized as S (n=3), FR (n=3) and FF (n=3), were studied. The range of HD for S, FR, FF units was 0.9–5.1%, 0.3–3.5%, 0.3–4.1%, respectively. These HD values indicate that the sinusoidal responses of muscle functional unit were reliable and further suggest the possibility to use this method for single MU transfer function identification.
INTRODUCTION: The relationship between the output force and motor command depends on the intrinsic RESULTS: The mathematical decomposition of unfused tetanic contractions of FF and FR MUs into twitch-shape responses to consecutive stimuli was conducted. The decomposition indicated substantial changes predominantly in force and additionally in time parameters of successive twitch‑like components, responsible for a sag profile in tetanic curve. Namely, initially the force increased and the highest force was observed in a response to the 2nd–3rd stimulus for FF units, while after the 3rd–7th stimulus for FR MUs and later decreased leading to the sag. In the second series of experiments, a repeatability of the sag in tetanic contractions of the same MU in a muscle with preserved blood circulation and under ischemic conditions was tested. Sag restitution was present in muscles with the circulation preserved but it was prevented by occlusion of blood vessels, indicating that sag depends on an availability of an energy source which can be restituted under aerobic conditions. CONCLUSIONS: The study indicated that sag profile of unfused tetanic contractions is predominantly an effect of early increase in amplitudes of several initial responses followed by a decrease in their amplitudes and that these changes are stronger and longer in time scale in FR than in FF MUs. The results concerning repeatability of the phenomenon suggest that most probable source of energy for initial force increase is phosphocreatine.
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