RÉSUMÉ
There have been several research studies on efficient methods for analysis and classification of electromyography (EMG) signals and adoption of wavelet functions, which is a promising approach for determining the spectral distribution of the signal. This study compares distinct time-frequency analysis methods for investigating the EMG activity of the thigh and calf muscles during gait among non-diabetic subjects and diabetic neuropathic patients. It also attempts to verify, by adaptive optimal kernel and discrete wavelet transform, whether there are EMG alterations related to diabetic neuropathy in the lower limb muscles during gait. The results show that diabetics might not keep up with the mechanical demands of walking by changing muscle fibre recruitment strategies, as seen in the control group. Moreover, principal components analysis indicates more alterations in diabetic motor strategies, and we identify that diabetic subjects need other strategies with different muscle energy production and frequencies to carry out their daily activities.
Sujet(s)
Neuropathies diabétiques/physiopathologie , Démarche/physiologie , Traitement du signal assisté par ordinateur , Phénomènes biomécaniques/physiologie , Électromyographie , Femelle , Humains , Mâle , Adulte d'âge moyen , Muscles squelettiques/physiologie , Analyse en composantes principalesRÉSUMÉ
Muscular fatigue was studied in relation to different types of exercises. Thirty rats were divided in three groups: control, aerobic (running) and anaerobic exercises (weight lifting). Computerized measures of fatigue were done, using a special software that has the ability to generate impulses in different intensities. A fatigue index was obtained in a way that the greater the fatigue, the smaller was this index. Relationship among the three groups was possible and we are able to observe that the weight lift group (anaerobic exercises) performed better when compared with the two other groups.