The surface electromyography (sEMG) records the electrical activity of muscle fibers during contraction: one of its uses is to assess changes taking place within muscles in the course of a fatiguing contraction to provide insights into our understanding of muscle fatigue in training protocols and rehabilitation medicine. Until recently, these myoelectric manifestations of muscle fatigue (MMF) have been assessed essentially by linear sEMG analyses. However, sEMG shows a complex behavior, due to many concurrent factors. Therefore, in the last years, complexity-based methods have been tentatively applied to the sEMG signal to better individuate the MMF onset during sustained contractions. In this review, after describing concisely the traditional linear methods employed to assess MMF we present the complexity methods used for sEMG analysis based on an extensive literature search. We show that some of these indices, like those derived from recurrence plots, from entropy or fractal analysis, can detect MMF efficiently. However, we also show that more work remains to be done to compare the complexity indices in terms of reliability and sensibility; to optimize the choice of embedding dimension, time delay and threshold distance in reconstructing the phase space; and to elucidate the relationship between complexity estimators and the physiologic phenomena underlying the onset of MMF in exercising muscles.

The influence of the chronotype on the sleep quality in male collegiate soccer players in response to acute high intensity interval training (HIIT) performed at two different times of day was evaluated. The sleep quality was poorer in the morning-type than in the evening-type players after the evening HIIT session, whereas no significant changes in the sleep quality of the two chronotypes after the morning HIIT session was observed. The results suggest that an athlete’s chronotype should be taken into account when scheduling training sessions and to promote faster recovery processes.

To evaluate the association between coagulation defects and cerebral venous thrombosis, a case-control study was conducted in 25 patients who had no autoimmune, neoplastic or infectious disease and 75 healthy individuals. There were no patients with deficiency of protein C or protein S. Four had resistance to activated protein C (APC) and one had APC resistance associated with antithrombin deficiency. APC resistance was investigated by DNA analysis, and diagnosed by the presence of a point mutation in the factor V gene, which predicts replacement of Arg⁵⁰⁶ with Gin at one of the two APC cleavage sites in activated factor V. The prevalence of APC resistance was 20% in patients and 2.7% in controls. This difference was statistically significant (p = 0.01) and the odds ratio was 9.1. A circumstantial factor predisposing to cerebral venous thrombosis (such as oral contraceptive intake, pregnancy, puerperium, trauma or prolonged immobilization) was reported in 72% of cases. In conclusion, APC resistance is the most frequent coagulation abnormality associated with cerebral venous thrombosis.