Abstract
Intrinsic hand muscles are densely located in the hand, and the myoelectric observation from the surface is sometimes unreliable because of some outside influences that may interfere with the signals. In the present study, we evaluated the activation of multiple interosseous hand muscles through the surface electromyographic signals during isometric finger-oriented tasks using univariate and multivariate logistic regression models. Ten healthy subjects participated in our experiment, and isometrically exercised each finger one by one in flexed form. The result of a univariate analysis with the power and amplitude domain predictor variables of the surface electromyographic signals showed a significant consistency between the activated finger and the inserted finger of the dorsal interosseous muscles to the proximal phalanx (P < 0.001). Meanwhile, the results of a multivariate analysis showed a higher correlation of the regression model of the fourth dorsal interosseous muscle during the action of the ring finger using frequency-domain variables (the Nagelkerke R2 = 0.716 when the median frequency was used), compared to the model without the frequency-domain variables (the Nagelkerke R2 = 0.583). We concluded that logistic regression models using surface electromyographic signals have a particular possibility to produce reliable results of an activation analysis of intrinsic hand muscles. Furthermore, the use of frequency- and amplitude-domain variables was shown to assist in improving data reliability.