A wearable physiological sensor system based on ECG, EDA, and EEG successfully captured human stress and quantified stress levels during an experimental protocol.
Observational (n=15)
Does a wearable physiological sensors system based on ECG, EDA, and EEG accurately capture human stress and correlate with salivary cortisol levels in healthy participants?
A wearable sensor system using ECG, EDA, and EEG can successfully capture and quantify human stress, which may be useful for designing portable stress monitoring devices.
OBJECTIVE: The objectives of this paper are to develop and test the ability of a wearable physiological sensors system, based on ECG, EDA, and EEG, to capture human stress and to assess whether the detected changes in physiological signals correlate with changes in salivary cortisol level, which is a reliable, objective biomarker of stress. METHODS: 15 healthy participants, eight males and seven females, mean age 40.8 ± 9.5 years, wore a set of three commercial sensors to record physiological signals during the Maastricht Acute Stress Test, an experimental protocol known to elicit robust physical and mental stress in humans. Salivary samples were collected throughout the different phases of the test. Statistical analysis was performed using a support vector machine (SVM) classification algorithm. A correlation analysis between extracted physiological features and salivary cortisol levels was also performed. RESULTS: = 0.714). CONCLUSION: The tested set of wearable sensors was able to successfully capture human stress and quantify stress level. SIGNIFICANCE: The results of this pilot study may be useful in designing portable and remote control systems, such as medical devices used to turn on interventions and prevent stress consequences.
Betti et al. (Mon,) conducted a observational in Healthy participants (n=15). Wearable physiological sensors system (ECG, EDA, EEG) was evaluated on Ability to capture human stress and correlate with salivary cortisol level. A wearable physiological sensor system based on ECG, EDA, and EEG successfully captured human stress and quantified stress levels during an experimental protocol.