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Journal of Biomedical Sciences

  • ISSN: 2254-609X
  • Journal h-index: 14
  • Journal CiteScore: 5.48
  • Average acceptance to publication time (5-7 days)
  • Average article processing time (30-45 days) Less than 5 volumes 30 days
    8 - 9 volumes 40 days
    10 and more volumes 45 days
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  • China National Knowledge Infrastructure (CNKI)
  • Directory of Research Journal Indexing (DRJI)
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Abstract

Determination of Stress in Humans using Data Fusion of Off-the-Shelf Wearable Sensors Data for Electrocardiogram and Galvanic Skin Response

Odafe E Jeroh*, Linda S Powers and Janet M Roveda

Stress detection helps individuals understand their stress levels and advises them when to take a break from activities causing stress. Physical activities and environmental influences can affect a person’s stress levels. People with professions as first responders, pilots, and working parents with newborns are examples of people exposed to a large amount of stress. Acquisition and proper analysis of physiological data is helpful in managing stress. In this paper, the results from two commercial, off-the-shelf sensors, Electrocardiogram [ECG] and Galvanic Skin Response [GSR] measurements, are fused to analyze stress in individuals; these sensors are noninvasive and wearable. Data from these sensors are collected simultaneously over a period of 25 minutes from 25 people which are undergoing a simulated stressor. Support Vector Machine [SVM] and Multilayer Perceptron [MLP] are used as the classifiers while Linear Discriminant Analysis [LDA] is used as the stress detection algorithm. The stress detection accuracy achieved varies with individuals and ranges from 85% to 92%. This approach of measuring stress is very suitable for real-time applications and can be used by anybody who wants to improve their performance.