Myoelectric control of active prostheses requires electrode systems that are easy to apply for daily repositioning of the electrodes by the user. In this study we propose the use of Smart Fabric and Interactive Textile (SFIT) systems as an alternative solution for recording high-density EMG signals for myoelectric control. A sleeve covering the upper and lower arm, which contains 100 electrodes arranged in four grids of 5 × 5 electrodes, was used to record EMG signals in 3 subjects during the execution of 9 tasks of the wrist and hand. The signals were analyzed by extracting wavelet coefficients which were classified with linear discriminant analysis. The average classification accuracy for the nine tasks was 89.1 ± 1.9 %. These results show that SFIT systems can be used as an effective way for muscle-machine interfacing.