Literature DB >> 24816334

Motor strategy patterns study of diabetic neuropathic individuals while walking. A wavelet approach.

I C N Sacco1, A N Hamamoto2, A N Onodera2, A A Gomes3, H A Weiderpass4, C G F Pachi5, J F Yamamoto6, V von Tscharner7.   

Abstract

The aim of this study was to investigate muscle׳s energy patterns and spectral properties of diabetic neuropathic individuals during gait cycle using wavelet approach. Twenty-one diabetic patients diagnosed with peripheral neuropathy, and 21 non-diabetic individuals were assessed during the whole gait cycle. Activation patterns of vastus lateralis, medial gastrocnemius and tibialis anterior were studied by means of bipolar surface EMG. The signal׳s energy and frequency were compared between groups using t-test. The energy was compared in each frequency band (7-542 Hz) using ANOVAs for repeated measures for each group and each muscle. The diabetic individuals displayed lower energies in lower frequency bands for all muscles and higher energies in higher frequency bands for the extensors׳ muscles. They also showed lower total energy of gastrocnemius and a higher total energy of vastus, considering the whole gait cycle. The overall results suggest a change in the neuromuscular strategy of the main extensor muscles of the lower limb of diabetic patients to compensate the ankle extensor deficit to propel the body forward and accomplish the walking task.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Diabetic polineuropathies; Electromyography; Gait; Neuromuscular strategy; Wavelet analysis

Mesh:

Year:  2014        PMID: 24816334     DOI: 10.1016/j.jbiomech.2014.04.007

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  7 in total

1.  Muscle Co-Contraction Detection in the Time-Frequency Domain.

Authors:  Francesco Di Nardo; Martina Morano; Annachiara Strazza; Sandro Fioretti
Journal:  Sensors (Basel)       Date:  2022-06-28       Impact factor: 3.847

2.  Association between spectral characteristics of paraspinal muscles and functional disability in patients with low back pain: a cohort study.

Authors:  Shin-Yi Chiou; Ermis Koutsos; Pantelis Georgiou; Paul H Strutton
Journal:  BMJ Open       Date:  2018-02-14       Impact factor: 2.692

3.  A wavelet based time frequency analysis of electromyograms to group steps of runners into clusters that contain similar muscle activation patterns.

Authors:  Vinzenz von Tscharner; Martin Ullrich; Maurice Mohr; Daniel Comaduran Marquez; Benno M Nigg
Journal:  PLoS One       Date:  2018-04-18       Impact factor: 3.240

4.  Characteristics of Lower Limb Muscle Activity in Elderly Persons After Ergometric Exercise.

Authors:  Kenichi Kaneko; Hitoshi Makabe; Kazuyuki Mito; Kazuyoshi Sakamoto; Yoshiya Kawanori; Kiyoshi Yonemoto
Journal:  Gerontol Geriatr Med       Date:  2020-12-10

5.  Comparison of Signal Processing Methods for Reducing Motion Artifacts in High-Density Electromyography During Human Locomotion.

Authors:  Bryan R Schlink; Andrew D Nordin; Daniel P Ferris
Journal:  IEEE Open J Eng Med Biol       Date:  2020-06-03

6.  Alterations in Spectral Attributes of Surface Electromyograms after Utilization of a Foot Drop Stimulator during Post-Stroke Gait.

Authors:  Rakesh Pilkar; Arvind Ramanujam; Karen J Nolan
Journal:  Front Neurol       Date:  2017-08-29       Impact factor: 4.003

7.  Wavelet analyses of electromyographic signals derived from lower extremity muscles while walking or running: A systematic review.

Authors:  Irene Koenig; Patric Eichelberger; Angela Blasimann; Antonia Hauswirth; Jean-Pierre Baeyens; Lorenz Radlinger
Journal:  PLoS One       Date:  2018-11-02       Impact factor: 3.240

  7 in total

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