Keep the Stress Away with SoDA: Stress Detection and Alleviation System

Ayten Ozge Akmandor, Niraj K. Jha

Research output: Contribution to journalArticlepeer-review

102 Scopus citations


Long-term exposure to stress may lead to serious health problems such as those related to the immune, cardiovascular, and endocrine systems. Once having arisen, these problems require a considerable investment of time and money to recover from. With early detection and treatment, however, these health problems may be nipped in the bud, thus improving quality of life. We present an automatic stress detection and alleviation system, called SoDA, to address this issue. SoDA takes advantage of emerging wearable medical sensors (WMSs), specifically, electrocardiogram (ECG), galvanic skin response (GSR), respiration rate, blood pressure, and blood oximeter, to continuously monitor human stress levels and mitigate stress as it arises. It performs stress detection and alleviation in a user-transparent manner, i.e., without the need for user intervention. When it detects stress, SoDA employs a stress alleviation technique in an adaptive manner based on the stress response of the user. We establish the effectiveness of the proposed system through a detailed analysis of data collected from 32 participants. A total of four stressors and three stress reduction techniques are employed. In the stress detection stage, SoDA achieves 95.8 percent accuracy with a distinct combination of supervised feature selection and unsupervised dimensionality reduction. In the stress alleviation stage, we compare SoDA with the 'no alleviation' baseline and validate its efficacy in responding to and alleviating stress.

Original languageEnglish (US)
Article number7926455
Pages (from-to)269-282
Number of pages14
JournalIEEE Transactions on Multi-Scale Computing Systems
Issue number4
StatePublished - Oct 1 2017

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Hardware and Architecture


  • Feature selection
  • physiological signals
  • stress alleviation
  • stress detection
  • wearable medical sensors


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