The mean power frequency (MNF) and the median power frequency (MDF) are frequency-domain and the root mean square (RMS) time-domain features that are frequently used for muscle fatigue assessment and muscle activation in surface EMG signals. The objective of this article is to determine if it is possible to use the LabVIEW biomedical toolkit so that the rehabilitation specialist can analyze graphically and numerically the different parameters such as: amplitude, frequency, muscle activity, etc., that are useful to evaluate the evolution of rehabilitation. This paper proposes the use of the biomedical toolkit in LabVIEW of National Instruments to extract and analyze the characteristics of the EMG signal, RMS, MNF and the spectrogram using the functions of the biomedical toolkit, Biosignal RMS and EMG Mean Power Frequency. For this purpose, two databases of electromyographic signals acquired with the Myo armband placed on the forearm were used. In the first database, the fist movement was chosen for this work. In the second database, participants held their elbows bent at 90 degrees, holding a weight of 6 kg for 120 seconds. In the graphs can be visualized the activation of the muscles, the RMS, MNF and the spectrogram of the electromyographic signal per sensor. It is possible select the time of the sliding window for the calculation of the RMS, (0.1 s, 0.5 s, 1 s, etc.), for the databases test, the signal was smoothed the longer the window time. The results obtained show that with the LabVIEW software it is possible to analyze that characteristics of the EMG signal, present them graphically, for example visual interpretation to evaluate the evolution of rehabilitation in physical and sports medicine.