Complexity-Based Analysis of the Correlation of Brain and Heart Activity in Younger and Older Subjects

The analysis of extraocular muscles’ activation is crucial for understanding eye movement patterns, providing insights into oculomotor control, and contributing to advancements in fields such as vision research, neurology, and biomedical engineering. Ten subjects went through the experiments, including normal watching, blinking, upward and downward movements of eyes, and eye movements to the left and right while their electromyogram (EMG) signals were recorded. We analyzed the complexity of recorded EMG signals using fractal theory, sample entropy, and approximate entropy (ApEn). The results showed that the techniques are able to decode the changes in the complexity of EMG signals between different eye movements. In other words, we can use these methods to study extraocular muscle activations in different conditions.

Decoding of the Extraocular Muscles Activations by Complexity-Based Analysis of Electromyogram (Emg) Signals

SRIRAM,

RAJAGOPAL,

KREJCAR

et al. 2024

Complexity-Based Analysis of the Variations in the Brain Response of Porn-Addicted and Healthy Individuals Under Different Function Tasks

PAKNIYAT,

RAMADOSS,

KARTHIKEYAN

et al. 2024

The examination of brain responses in individuals with a pornography addiction compared to those without sheds light on the neurobiological aspects associated with this behavior. Neuroscientific studies utilizing techniques such as electroencephalography (EEG) have shown that porn-addicted individuals may exhibit alterations in neural pathways related to reward processing and impulse control. In this paper, we analyzed the variations in the brain response of porn-addicted versus healthy individuals under five function tasks including baseline, emotional state, memorize task, executive task, and recall task. For this purpose, we analyzed the complexity of EEG signals using fractal theory, approximate entropy (ApEn), and sample entropy. The results showed that the EEG signals of porn-addicted teenagers are more complex than the ones for healthy individuals, which reflects a higher level of brain activity for porn-addicted teenagers. This method of analysis can be extended to examine the brain activity of other types of addiction versus healthy brains.

Analysis of the Variations in Brain Activity in Response to Various Computer Games

VIVEKANANDHAN,

KARTHIKEYAN,

PAKNIYAT

et al. 2024

The influence of video games on the human brain has been a topic of extensive research and discussion. Video games, characterized by their dynamic and immersive qualities, have demonstrated the capacity to impact diverse cognitive processes. In this study, we conducted a detailed analysis of brain response variations to different genres of computer games, specifically focusing on boring, calm, horror, and funny games. To achieve this, we computed the sample entropy and approximate entropy of electroencephalograms (EEG) signals recorded from participants while they engaged with each type of game. Our findings revealed that EEG signals exhibited the highest complexity during the funny game and the lowest complexity during the calm game. This suggests that the brain is most active when playing the funny game and least active during the calm game. These results provide valuable insights into how different types of video game content can influence brain activity. The methodology employed in this study can be extended to explore brain activity under various conditions, potentially offering a broader understanding of how different stimuli impact cognitive processes. This approach can be useful in examining the effects of various interactive media on brain function and could inform the design of video games and other digital experiences to optimize cognitive engagement and mental well-being.