Dynamic patterns of muscular recruitment obtained by high-density EMG from diabetic subjects with different neuropathy degrees classified by a fuzzy-linguistic model

Author(s)

Eneida Yuri Suda

• Document type: Doctoral Thesis
• Press: São Paulo.
• Institution: Universidade de São Paulo (USP). Faculdade de Medicina (FM/SBD)
• Defense date: 2017-07-12

Examining board members

Isabel de Camargo Neves Sacco; Luciano Luporini Menegaldo; Maria Elisa Pimentel Piemonte

• Advisor: Isabel de Camargo Neves Sacco

Abstract

Introduction: The general proposal of this study is to get a better understanding on how motor control is affected in diabetic polyneuropathy (DPN) individuals. Fluctuations of the force and sEMG signal during isometric voluntary contractions have been studied as a simplified model of the physiological mechanism that underlies the control of movement. The analysis of the muscular recruitment patterns from lower limbs, obtained by high-density sEMG, together with the corresponding force signal outputs from knee and ankle joints, in the light of complexity analysis, adds to the knowledge of the disease effects in motor control. Additionally, examining the complexity of force and muscle activity of DPN individuals, along with the development of DPN from subclinical to the more severe stages, will help us understanding how the alterations will develop with the DPN progression. The hypotheses of this study are that: DPN alters the motor complexity, expressed as an increased amount of variability and a decreased structure of variability in sEMG and force outputs, and these alterations are aggravated by the severity of the disease. Methods: We assessed 10 control subjects and 38 diabetic subjects, classified as absent, mild, moderate, or severe DPN, by a fuzzy-system based on clinical variables. Multichannel sEMG (64-electrode matrix) of tibialis anterior, gastrocnemius medialis, vastus lateralis and biceps femoris muscles were acquired during isometric contractions at 10%, 20%, and 30% of the maximum voluntary contraction, and force levels were recorded during dorsiflexion, plantarflexion, knee extension and knee flexion. Standard deviation and sample entropy of force signals were calculated and root mean square and sample entropy were calculated from sEMG signals. Differences among groups of force and sEMG variables were verified using a multivariate analysis of variance (alpha=0.05). Results: Overall, during dorsiflexion contractions, moderate and severe subjects had higher force standard deviation and moderate subjects had lower force sample entropy. During plantarflexion, moderate subjects had higher force standard deviation and all diabetic subjects had lower entropy. During knee extension moderate DPN subjects demonstrated high force standard deviation and low force sample entropy. Tibialis anterior presented higher root mean square in absent group and lower entropy in mild subjects. For gastrocnemius medialis, entropy was higher in severe and lower in moderate subjects. Severely affected participants showed low sample entropy in vastus lateralis at all force levels. Conclusions: DPN affects the complexity of the neuromuscular system during low-level isometric contractions, reducing the system\'s capacity to adapt to challenging mechanical demands. The observed patterns of neuromuscular complexity were not associated with disease severity, with the majority of alterations recorded in moderate subject (AU)

• FAPESP's process: 13/06123-7 - Dynamic muscles recruitment patterns during gait using high-density EMG of diabetic patients in different severity degrees classified by a fuzzy system
• Grantee: Eneida Yuri Suda
• Support Opportunities: Scholarships in Brazil - Doctorate