Application to biomedical signals 211
tion linear discriminant analysis (LDA) and multilayer perceptron (MLP) were ap-
plied. The best performance was obtained for WP/PCA/LDA combination, yielding
a classification error of 6%. This result was an improvement in respect to procedures
based on time features of MUAPs, which for the same data gave an average error of
9%.
WT was also successfully applied for diagnosis and follow up of Parkinson dis-
ease [De Michele et al., 2003]. The sEMG for ballistic movement was recorded from
major pectoralis and posterior deltoid muscles. The Morlet complex wavelet was
used and cross-correlation was computed between continuous wavelet transforms
W
f
(a,τ) and W
g
(a,τ) of functions f (t) and g(t) describing signals from the ...