Objective: In this study, we evaluated the role of residual supraspinal and afferent signaling and their convergence on the sublesional spinal network in subject diagnosed with complete paralysis (AIS-A). Methods: A combination of electrophysiologic techniques with positional changes and subject-driven reinforcement maneuvers was implemented in this study. Electrical stimulation was applied transcutaneously at the T9-L2 vertebra levels and the spinal cord motor evoked potentials (SEMP) were recorded from leg muscles. To test the influence of positional changes, the subject was placed in (i) supine, (ii) upright with partial body weight bearing and (iii) vertically suspended without body weight bearing positions. Results: Increase in amplitude of SEMP was observed during transition from supine to upright position, supporting the role of sensory input in lumbosacral network excitability. Additionally, amplitudes of SEMP were facilitated during reinforcement maneuvers, indicating a supralesional influence on sub-lesional network. After initial assessment, subject underwent rehabilitation therapy with following electrophysiological testing that reviled facilitation of SEMP. Conclusion: These results demonstrate that combination of electrophysiological techniques with positional and reinforcement maneuvers can add to the diagnostics of discomplete SCI. These findings also support an idea that integration of supraspinal and afferent information on sub-lesional circuitry plays a critical role in facilitation of spinal sensorimotor network in discomplete SCI.

The modern transformation of all spheres of life is associated with rapid technological and digital development. The educational sphere, focusing on external demands, systematically introduces technological and digital solutions into the processes of pedagogical systems functioning, focusing on the expansion of the educational space, on increasing the availability of educational services. In order to create a comfortable and effective digital environment in universities, it is important to take into account not only the level of development of digital competencies of students and teachers, but also their basic needs and requirements in this area. We set a goal to identify the most successful digital solutions used at this stage in university education from the students’ perspective and to consider the factors inhibiting these processes. To solve the problems, we used methods of theoretical analysis and empirical processing of research data. The main method was a survey of students using the questionnaires “Digital learning environment and online learning format” and “Quality of digital educational resources and organizational aspects of e-learning” developed by the authors. More than a thousand students from Russian universities took part in the survey. The results of the survey showed what means of communication in online learning are considered by students to be the most effective, what means of increasing productivity and what means of organization and support in online learning are most useful to them. The platforms and learning systems were considered in detail to understand the important characteristics of these services for students. The analysis highlighted the main areas in the digital transformation of the educational environment, which should be targeted for their development and improvement.

The quality of modern measuring instruments has a strong influence on the speed of diagnosing diseases of the human musculoskeletal system. The research is focused on automatization of the method of gait analysis. The study involved six healthy subjects. The subjects walk straight. Each subject made several gait types: casual walking and imitation of a non-standard gait, including shuffling, lameness, clubfoot, walking from the heel, rolling from heel to toe, walking with hands in pockets, and catwalk. Each type of gait was recorded three times. For video fixation, the Vicon Nexus system was used. A total of 27 reflective markers were placed on the special anatomical regions. The goniometry methods were used. The walk data were divided by steps and by step phases. Kinematic parameters for estimation were formulated and calculated. An approach for data clusterization is presented. For this purpose, angle data were interpolated and the interpolation coefficients were used for clustering the data. The data were processed and four cluster groups were found. Typical angulograms for cluster groups were presented. For each group, average angles were calculated. A statistically significant difference was found between received cluster groups.