Reliability of pelvic floor muscle surface electromyography (sEMG) recordings during synchronous whole body vibration

Measurement of Simple Reaction Time of the Cyclist in the Laboratory and Natural Environment Condition

The most commonly used reaction time tests within the athlete community require appropriate testing conditions and equipment, most frequently laboratory ones, which are not suitable for testing athletes in their natural environment and do not fully represent athletes' natural capabilities and the influence of the surrounding environment. Therefore, this study's goal is to compare the simple reaction times (SRTs) of cyclists during tests in laboratory conditions and in natural cycling surroundings. The young cyclists (55 participants) took part in the study. The SRT was measured in a quiet laboratory room with the use of the special device. During riding and standing with a bike outdoors, the necessary signal was captured and transmitted by a folic tactile sensor (FTS) and an extra intermediary circuit (both invented by our team member) connected to a muscle activity measurement system (Noraxon DTS Desktop, Scottsdale, AZ, USA). The results showed that external conditions significantly affect the SRT, with it being the longest when riding and the shortest if measured in an isolated laboratory room, but without an effect of gender. Typically, men have a shorter reaction time, but our result supports other observations, where people with an active lifestyle show no sex differentiation in SRT. The proposed FTS with an intermediary circuit allowed us to measure SRT with the use of non-dedicated equipment and avoid buying a new one for a single specific use.

Intermuscular coupling network analysis of upper limbs based on R-vine copula transfer entropy

In the field of neuroscience, it is very important to evaluate the causal coupling characteristics between bioelectrical signals accurately and effectively. Transfer entropy is commonly used to analyze complex data, especially the causal relationship between data with non-linear, multidimensional characteristics. However, traditional transfer entropy needs to estimate the probability density function of the variable, which is computationally complex and unstable. In this paper, a new and effective method for entropy transfer is proposed, by means of applying R-vine copula function estimation. The effectiveness of R-vine copula transfer entropy is first verified on several simulations, and then applied to intermuscular coupling analysis to explore the characteristics of the intermuscular coupling network of muscles in non-fatigue and fatigue conditions. The experiment results show that as the muscle group enters the fatigue state, the community structure can be adjusted and the muscle nodes participating in the exercise are fully activated, enabling the two-way interaction between different communities. Finally, it comes to the conclusion that the proposed method can make accurate inferences about complex causal coupling. Moreover, the characteristics of the intermuscular coupling network in both non-fatigue and fatigue states can provide a new theoretical perspective for the diagnosis of neuromuscular fatigue and sports rehabilitation, which has good application value.