Anatomical Consideration of the Motor Point Location of the Tibialis Anterior Muscle for effective Neuromuscular Electrical Stimulation

  • Narita Hirokazu
    Departments of Development and Aging, Division of Health Sciences, Hirosaki University Graduate School of Health Sciences Departments of Anatomical Science, Hirosaki University Graduate School of Medicine
  • Chiba Shoji
    Departments of Pathologic Analysis, Division of Medical Life Sciences, Hirosaki University Graduate School of Health Sciences
  • Yoshida Hideki
    Departments of Health Promotion, Division of Health Sciences, Hirosaki University Graduate School of Health Sciences
  • Mizohata Hideaki
    Department of Rehabilitation, National Hospital Organization Fukui National Hospital
  • Tonosaki Yoshikazu
    Departments of Anatomical Science, Hirosaki University Graduate School of Medicine
  • Ichinohe Noritaka
    Departments of Ultrastructural Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry

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[Purpose] We attempted to locate the motor points (MPs) of the tibialis anterior muscle (TA) for more effective neuromuscular electrical stimulation (NMES). [Subjects] We dissected 16 legs from 12 cadavers. [Methods] Branches of the deep peroneal nerve were traced to their entry into TA (MPs). We defined the FH-LM line connecting the fibular head to the lateral malleolus and the pFH-LM perpendicular to the FH-LM lines that ran through each MP. The distance from the fibular head to MPs projected on the FH-LM line was measured. On the pFH-LM line, the width of TA and the distance from the lateral edge of TA to each MP were measured. The location of each MP was expressed as a percentage of total length of the FH-LM line and of TA width, respectively. [Results] The median number of MPs was 8 per cadaver. About 68% of all MPs were located within the proximal one-third of the FH-LM line. The average location of the thickest motor branch MP was 4.2 cm (13.9 %) on the FH-LM line and 0.9 cm (33.5 %) medial from the lateral edge of TA. [Conclusion] This data should enable more effective NMES.<br>

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