The Japanese Journal of Rehabilitation Medicine
Online ISSN : 1881-8560
Print ISSN : 1881-3526
ISSN-L : 1881-3526
46 巻, 10 号
選択された号の論文の9件中1~9を表示しています
第46回日本リハビリテーション医学会学術集会
招待講演
第46回日本リハビリテーション医学会学術集会
教育講演
総説
  • —定性的解析と定量的解析およびその限界—
    興津 太郎
    2009 年 46 巻 10 号 p. 649-658
    発行日: 2009/10/18
    公開日: 2009/10/30
    ジャーナル フリー
    Needle electromyography is used to investigate motor unit abnormalities, consisting of the anterior horn cell, the axon, the nerve end-plate, and the associated muscle fibers. The characteristics of the firing and recruitment patterns of motor units during voluntary contraction are identified as an interference pattern that is used clinically for the diagnosis of neuropathy and myopathy. Quantitative analysis of this interference pattern, using such factors as zero-crossing, spike count, number of turns (NT), the peak-to-peak amplitude, mean amplitude (MA), and automatic amplitude of the interference pattern envelope, is used to identify interference patterns resulting from specific pathologies. It is difficult, however, to improve the sensitivity and specificity of the analysis for the diagnosis of neuropathy and myopathy by separately analyzing the number or amplitude of the spikes involved in the interference pattern. Therefore, turn amplitude analysis has been developed, which combines the number and amplitude of the spikes. For the NT:MA ratio and peak ratio analysis (PRA), the turns are examined during a constant voluntary contraction. In contrast, for the cloud analysis, the distribution of NT and MA at various muscle strengths is plotted. Expert Quantitative Interference Pattern Analysis (EQUIP), which applies the expertise of an electromyographer, provides practical sensitivity and specificity for the clinical diagnosis of neuropathic and myopathic diseases. Understanding these various quantitative interference pattern analysis modalities will not only improve the ability of physiatrists to interpret electromyographic findings, but will also expand their knowledge of motor unit diseases.
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