Legs are the contact point of humans during walking. In fact, leg muscles react when we walk in different conditions (such as different speeds and paths). In this research, we analyze how walking path affects leg muscles’ reaction. In fact, we investigate how the complexity of muscle reaction is related to the complexity of path of movement. For this purpose, we employ fractal theory. In the experiment, subjects walk on different paths that have different fractal dimensions and then we calculate the fractal dimension of Electromyography (EMG) signals obtained from both legs. The result of our analysis showed that the complexity of EMG signal increases with the increment of complexity of path of movement. The conducted statistical analysis also supported the result of analysis. The method of analysis used in this research can be further applied to find the relation between complexity of path of movement and other physiological signals of humans such as respiration and Electroencephalography (EEG) signal.

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BACKGROUND: Walking is one of the important actions of the human body. For this purpose, the human brain communicates with leg muscles through the nervous system. Based on the walking path, leg muscles act differently. Therefore, there should be a relation between the activity of leg muscles and the path of movement. OBJECTIVE: In order to address this issue, we analyzed how leg muscle activity is related to the variations of the path of movement. METHOD: Since the electromyography (EMG) signal is a feature of muscle activity and the movement path has complex structures, we used entropy analysis in order to link their structures. The Shannon entropy of EMG signal and walking path are computed to relate their information content. RESULTS: Based on the obtained results, walking on a path with greater information content causes greater information content in the EMG signal which is supported by statistical analysis results. This allowed us to analyze the relation between muscle activity and walking path. CONCLUSION: The method of analysis employed in this research can be applied to investigate the relation between brain or heart reactions and walking path.

Our skin reacts to various stimuli that we receive. Since all parts of the human body are controlled by the brain, a relationship should exist among brain and skin activities. This study evaluates the relation among skin and brain activities. As such, we benefited from the information-based analysis. We collected GSR and EEG signals of eight participants in various olfactory stimulations. Accordingly, we ran Shannon entropy-based analysis to evaluate the correlation between the information contents of these two signals. The results showed that the alterations in the complexity of stimulus and the information of GSR and EEG signals are strongly correlated. We also verified the results of the analysis of Shannon entropy of signals by calculating their Hurst exponent to quantify their memory. According to the results, the alterations of the memory of EEG and GSR signals are similar to the alterations of the information of these signals.