Analysis of Mental Health using Galvanic Skin Reflectance

EasyChair Preprint no. 3109

Abstract

Our skin gives away a lot of information on how we feel when we’re exposed to emotions. Sometimes, one has to control different emotional situations which may lead the person suffering them to dangerous situations, in both the medium and short term. There are studies which indicate that stress increases the chance of cardiac problems. Stress detector classifies a stressed individual from a standard one by acquiring his/her physiological signals through appropriate sensors like Electrocardiogram (ECG), Galvanic Skin Response (GSR) etc,. These signals are pre-processed to extract the specified features which depicts the stress level in working individuals. The signal are often used for capturing the autonomic nerve responses as a parameter of the sweat gland function. The response appears as a rise within the electrical conductance of the skin (a decrease in resistance) across the palms of the hands or soles of the feet. Galvanic Skin Response (GSR) is defined as a change within the electrical properties of the skin. It is used to measure skin resistance, skin conductance and stress level of human being. The mathematical manipulation is implemented to measure these parameters skin resistance, skin conductance and stress level at various situations( i.e. listening music, mathematical calculations, breathing, etc.,). The present state of sensor technology allows to develop systems measuring physical symptoms reflecting the stress level. The problem of stress identification and categorization from the sensor data stream mining perspective, consider a reductionist approach for arousal identification as a drift detection task, highlight the foremost problems of managing with GSR data, and propose simple approaches the way to them.

Keyphrases: Arduino, Biomedical Workbench, Conductance and stress, EDR, Galvanic Skin Response (GSR), LabVIEW

@Booklet{EasyChair:3109,
  author = {Khushboo Hembrom and Puja Kumari Shah and Rajesh Siva and Deepjyoti Mahanta and Samar Jyoti Saikia and Hemashree Bordoloi},
  title = {Analysis of Mental Health using Galvanic Skin Reflectance},
  howpublished = {EasyChair Preprint no. 3109},

  year = {EasyChair, 2020}}