PubMed · 13454497
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
M PISANI, G MONTILLI, C SERRA. 1957-05-25. [Electromyography in scleroderma].. https://pubmed.ncbi.nlm.nih.gov/13454497/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
Primary orthostatic tremor is characterized by 16-Hz motor activity that is coherent between muscles. It has been suggested that this tremor originates in the brain. This view is questioned by findings from a patient with complete paraplegia who experiences intermittent leg spasms at rest. The EMG activity within the spasms showed a 16-Hz component that was coherent between muscles unilaterally and bilaterally. This raises the possibility that the spinal cord could be the source of orthostatic tremor.
Because humans have limited ability to independently control the many joints of the hand, a wide variety of hand shapes can be characterized as a weighted combination of just two or three main patterns of covariation in joint rotations, or "postural synergies." The present study sought to align muscle synergies with these main postural synergies and to describe the form of membership of motor units in these postural/muscle synergies. Seventeen joint angles and the electromyographic (EMG) activities of several hand muscles (both intrinsic and extrinsic muscles) were recorded while human subjects held the hand statically in 52 specific shapes (i.e., shaping the hand around 26 commonly grasped objects or forming the 26 letter shapes of a manual alphabet). Principal-components analysis revealed several patterns of muscle synergy, some of which represented either coactivation of all hand muscles, or reciprocal patterns of activity (above and below average levels) in the intrinsic index finger and thumb muscles or (to a lesser extent) in the extrinsic four-tendoned extensor and flexor muscles. Single- and multiunit activity was generally a multimodal function of whole hand shape. This implies that motor-unit activation does not align with a single synergy; instead, motor units participate in multiple muscle synergies. Thus it appears that the organization of the global pattern of hand muscle activation is highly distributed. This organization mirrors the highly fractured somatotopy of cortical hand representations and may provide an ideal substrate for motor learning and recovery from injury.
OBJECTIVE: This is the first reported use of the continuous wavelet transform (CWT) of the surface EMG (sEMG) to extract the reflex response to muscle stretch. We used a modulus-based method to estimate instantaneous amplitude-envelopes from ridges of the CWT (referred in this work as sEMG intensity) to extract the dynamic reflex response from sEMG. We tested the method on tendon reflexes where excellent temporal resolution is required to identify the different latency components, and on the tonic stretch reflex (tonic SR) response to an ongoing perturbation that characteristically has a low signal to noise ratio. METHODS: Eight subjects without neurological impairment were subjected to a series of archilles tendon taps and a 2 min continuous perturbation of the ankle using a pseudo-sinusoidal stretch profile containing frequencies from 0.1 to 8.0 Hz. The tendon reflexes were assessed in the soleus muscle at 10% of MVC and the tonic SR in tibialis anterior while the muscle was relaxed, at 5 and 10% of maximal voluntary contraction. Root mean square (RMS) and wavelet ridge extraction was applied to the sEMG signal to extract sEMG amplitudes (RMS) and intensities for all reflexes. To obtain the tonic SR, these estimates and those from the sEMG-RMS were subsequently cross-correlated with the perturbation record to yield 2 sets of estimates of reflex gain and coherence for comparison. RESULTS: The sEMG intensities were highly correlated with the torques resulting from a ramped voluntary contraction. Following tendon taps, the method resolved the M1, M2, M3 response components at accurate latencies and with more complete reconstruction of the components than RMS-derived estimates. The wavelet ridge estimates extracted the tonic SR from resting and contracting muscles with significantly higher coherence than RMS estimates. Reflex gain, when estimated from sEMG intensity or sEMG-RMS, demonstrated similar relationships to the perturbation frequency and background contraction level. When the sEMG intensity reflex gain estimates from different subjects were pooled, they showed significantly lower variance about the mean than gain estimates derived from the rectified sEMG. CONCLUSIONS: Wavelet-ridge extraction provides a valid approach to reflex evaluation from sEMG that does not depend on the absolute amplitude of the potentials measured at the EMG electrodes. This may have substantial advantages in more directly comparing responses between subjects on an absolute frequency scale without the need for normalisation against maximal contraction levels.