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Electromyography (EMG) and Nerve Conduction Studies

Electromyography (EMG) and Nerve Conduction Studies

Nerve conduction studies (NCS) and electromyography (EMG) are recognized electrophysiological techniques that play an important role in the diagnosis of neuromuscular diseases. Their early development is closely related to the discovery of electricity, this relationship has been clarified from the observation of the effect of applying electricity to animals and the discovery that nerves and muscles may be the source of electricity. The former paved the way for the practice of electrotherapy, and the latter provided a basis for electrodiagnosis. After years of extensive research, NCS and EMG have become pioneers in the field of clinical neurosubspecialty electrodiagnosis.

EMG and NCS are Painful Examinations

EMG and NCS are an unpleasant and sometimes painful examination. Pain reduces the patient's compliance and has a negative impact on the test results. Each factor induces positive emotional valence by acting as a distractor or affects pain perception through different sensory patterns. A numerical scale was used to evaluate pain. The pain levels of EMG and NCS for patients with different factors are ranked as follows:

Pyramid effect of pain degree of patients with EMG and NCS examinations and different factors. Fig.1 Pyramid effect of pain degree of patients with EMG and NCS examinations and different factors.

Application of EMG and NCS in Diseases

  • Coronavirus disease (COVID) -19 polyneuropathy
  • Three recent patients with sequelae of COVID-19 underwent NCS and EMG examinations. NCS showed partial or complete conduction blocks on several nerves, a slightly longer delay than the nerves, and rare or absent F waves, all these both indicate that SARS-COV-2 caused polyneuropathy. The short duration and low amplitude of the motor unit action potential with early full recruitment on interference pattern on EMG, typical for myopathy, suggest a direct action of COVID-19 on muscular fibers, especially in the lower limbs.

  • Fibromyalgia (FM)
  • The results collected from the largest group of FM patients indicate that features of polyneuropathy, muscle attenuation, and chronic inflammatory degradation polyneuropathy (CIDP) are common in FM. EMG/NCS has detected large fibrosis (LFN) in FM patients, which may be a clinically useful tool for detecting LFN in FM and help to better understand the cause of this disorder.

  • Rehabilitation science
  • The movement of the fingers is one of the main human movements by many scientists. The complexity analysis of EMG signals recorded by different actions through fractal analysis is very important for the research of rehabilitation science. Fractal theory can be applied to study the influence of other types of stimuli on the complexity of muscle response.

A sample of EMG signal in case of index finger flexion. Fig.2 A sample of EMG signal in case of index finger flexion. (Namazi, 2019)

  • Diabetic peripheral neuropathy (DPN)
  • DPN is the most common long-term complication of patients with type 2 diabetes (T2DM), but the least recognized and understood. NCS and EMG are important non-invasive diagnostic methods used in the detection of diabetic peripheral neuropathy.

    Early Development of EMG and NCS

    • In 1771, Galvani proved that electrical stimulation of animal muscle tissue produces contraction, so the concept of animal electricity was born.
    • In 1929, Adrian recorded the potential of a single motor unit by connecting concentric needle electrodes to amplifiers and speakers.
    • In 1938, Denny Brown described the fascicular potential and separated it from fibrillation.
    • In 1945, Larrabee measured the compound muscle action potentials of the health and injured nerves of war victims.
    • In 1957, Lambert and Eaton described a new electrophysiological feature of myasthenia syndrome associated with lung cancer.

    Creative Biolabs has advanced technology and a complete laboratory platform, which can provide you with professional analysis and strategies in the fields of neuroscience and biochemical technology. Please feel free to contact us if you are interested or have any questions.

    Reference

    1. Namazi, H. Fractal-based classification of electromyography (EMG) signal in response to basic movements of the fingers. Fractals. 2019, 27(03): 1950037.
    For Research Use Only. Not For Clinical Use.
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