Co-activations of agonist and antagonist muscles are believed to be present in voluntary limb movement. Recent studies indicate that such co-activations are either synergic or dyssynergic. The aims of this paper are to (1) develop a novel method that can extract both the intensity and frequency information from the recordings of the surface electromyograms (EMGs) of involved muscles, and (2) investigate if the involved muscles will be under synergic co-activation during voluntary forearm pronation for normal subjects and dyssynergic co-activation for patients with radial nerve palsy. We examined 11 healthy subjects and 4 patients with right-arm radial nerve palsy in this study. For the group of healthy subjects, each one of them was asked to perform 30 trials of voluntary forearm pronation and then 30 trials of passive pronation as control experiments. As to the second group of patients, each one was asked to perform only 15 trials of voluntary pronation due to the limitation and durability of their arms. The recordings of the surface EMGs included the short and long heads of the biceps brachii, the brachialis, the lateral head of the triceps brachii, brachioradialis, and pronator teres. Experimental results of the healthy group indicated that the surface EMGs of all muscles had no statistically significant changes in fractal dimensions (FDs) and spectral frequencies of the control experiments during passive pronation. Yet, during the voluntary pronation experiments, the surface EMGs of all muscle groups were temporally synchronized in frequencies with persistent intensities. Hence, all involved muscle groups were in synergic co-activation. Statistical results of the group mean values of FDs during rest vs. forearm pronation also revealed significant difference with p < 0.01 for healthy subjects. As to the group of patients, their EMGs could still have bursting activities, but the synchronized significant frequencies might be lacking or the intensities as indicated from their FDs would not be persistent. To further compare the FDs among the three different protocols, a mixed-model ANOVA and multiple comparison tests were performed. Finally, in order to illustrate the advantages of this novel method, we have compared it with the detrended fluctuation analysis (DFA). It is believed that this proposed method will have the potential to be a biomarker for evaluating dynamical disease in neuromuscular disorders.