Removal of subject-dependent and activity-dependent variation in physiological measures of stress

F. Alamudun, J. Choi, R. Gutierrez-Osuna, H. Khan, B. Ahmed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

The ability to monitor stress levels in daily life can provide valuable information to patients and their caretakers, help identify potential stressors, determine appropriate interventions, and monitor their effectiveness. Wearable sensor technology makes it now possible to measure non-invasively a number of physiological correlates of stress, from skin conductance to heart rate variability. These measures, however, show large individual differences and are also correlated with the physical activity of the subject. In this paper, we propose two multivariate signal processing techniques to reduce the effect of both forms of interference. The first method is an unsupervised technique that removes any systematic variation that is orthogonal to the dependent variable, in this case physiological stress. In contrast, the second method is a supervised technique that first projects the data into a subspace that emphasizes these systematic variations, and then removes them from the data. The two methods were validated on an experimental dataset containing physiological recordings from multiple subjects performing physical and/or mental activities. When compared to z-score normalization, the standard method for removing individual differences, our methods can reduce stress prediction errors by as much as 50%.

Original languageEnglish
Title of host publication2012 6th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2012
Pages115-122
Number of pages8
DOIs
Publication statusPublished - 20 Aug 2012
Event2012 6th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2012 - San Diego, CA, United States
Duration: 21 May 201224 May 2012

Publication series

Name2012 6th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2012

Other

Other2012 6th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2012
CountryUnited States
CitySan Diego, CA
Period21/5/1224/5/12

Keywords

  • Electrodermal activity
  • Heart rate variability
  • Individual differences
  • Mental stress
  • Noise cancellation
  • Wearable sensors

ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management

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    Alamudun, F., Choi, J., Gutierrez-Osuna, R., Khan, H., & Ahmed, B. (2012). Removal of subject-dependent and activity-dependent variation in physiological measures of stress. In 2012 6th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2012 (pp. 115-122). (2012 6th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2012). https://doi.org/10.4108/icst.pervasivehealth.2012.248722