Affiliations 

  • 1 School of Engineering, Monash University, Selangor, Malaysia
  • 2 School of Pharmacy, Monash University, Selangor, Malaysia
  • 3 School of Engineering, Monash University, Selangor, Malaysia; Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada. Electronic address: [email protected]
Comput Methods Programs Biomed, 2020 Feb;184:105293.
PMID: 31887618 DOI: 10.1016/j.cmpb.2019.105293

Abstract

BACKGROUND AND OBJECTIVE: Human body is covered with skin in different parts. In fact, skin reacts to different changes around human. For instance, when the surrounding temperature changes, human skin will react differently. It is known that the activity of skin is regulated by human brain. In this research, for the first time we investigate the relation between the activities of human skin and brain by mathematical analysis of Galvanic Skin Response (GSR) and Electroencephalography (EEG) signals.

METHOD: For this purpose, we employ fractal theory and analyze the variations of fractal dimension of GSR and EEG signals when subjects are exposed to different olfactory stimuli in the form of pleasant odors.

RESULTS: Based on the obtained results, the complexity of GSR signal changes with the complexity of EEG signal in case of different stimuli, where by increasing the molecular complexity of olfactory stimuli, the complexity of EEG and GSR signals increases. The results of statistical analysis showed the significant effect of stimulation on variations of complexity of GSR signal. In addition, based on effect size analysis, fourth odor with greatest molecular complexity had the greatest effect on variations of complexity of EEG and GSR signals.

CONCLUSION: Therefore, it can be said that human skin reaction changes with the variations in the activity of human brain. The result of analysis in this research can be further used to make a model between the activities of human skin and brain that will enable us to predict skin reaction to different stimuli.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.