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BackgroundElectromyographic signals can be used in biomedical engineering and/or rehabilitation field, as potential sources of control for prosthetics and orthotics. In such applications, digital processing techniques are necessary to follow efficient and effectively the changes in the physiological characteristics produced by a muscular contraction. In this paper, two methods based on information theory are proposed to evaluate the processing techniques.MethodsThese methods determine the amount of information that a processing technique is able to extract from EMG signals. The processing techniques evaluated with these methods were: absolute mean value (AMV), RMS values, variance values (VAR) and difference absolute mean value (DAMV). EMG signals from the middle deltoid during abduction and adduction movement of the arm in the scapular plane was registered, for static and dynamic contractions. The optimal window length (segmentation), abduction and adduction movements and inter-electrode distance were also analyzed.ResultsUsing the optimal segmentation (200 ms and 300 ms in static and dynamic contractions, respectively) the best processing techniques were: RMS, AMV and VAR in static contractions, and only the RMS in dynamic contractions. Using the RMS of EMG signal, variations in the amount of information between the abduction and adduction movements were observed.ConclusionsAlthough the evaluation methods proposed here were applied to standard processing techniques, these methods can also be considered as alternatives tools to evaluate new processing techniques in different areas of electrophysiology.

Up to date, tissue regeneration of large bone defects is a clinical challenge under exhaustive study. Nowadays, the most common clinical solutions concerning bone regeneration involve systems based on human or bovine tissues, which suffer from drawbacks like antigenicity, complex processing, low osteoinductivity, rapid resorption and minimal acceleration of tissue regeneration. This work thus addresses the development of nanofibrous synthetic scaffolds of polycaprolactone (PCL)-a long-term degradation polyester-compounded with hydroxyapatite (HA) and variable concentrations of ZnO as alternative solutions for accelerated bone tissue regeneration in applications requiring mid-and long-term resorption. In vitro cell response of human fetal osteoblasts as well as antibacterial activity against Staphylococcus aureus of PCL:HA:ZnO and PCL:ZnO scaffolds were here evaluated. Furthermore, the effect of ZnO nanostructures at different concentrations on in vitro degradation of PCL electrospun scaffolds was analyzed. The results proved that higher concentrations ZnO may induce early mineralization, as indicated by high alkaline phosphatase activity levels, cell proliferation assays and positive Alizarin-RedS stained calcium deposits. Moreover, all PCL:ZnO scaffolds particularly showed antibacterial activity against S. aureus which may be attributed to release of Zn 2+ ions. Additionally, results here obtained showed a variable PCL degradation rate as a function of ZnO concentration. Therefore, this work suggests that our PCL:ZnO scaffolds may be promising and competitive short-, mid-and long-term resorption systems against current clinical solutions for bone tissue regeneration.