Key result
A stress detection method using three time-domain features from a low-cost heart rate chest belt achieved 74.6% accuracy, 75.0% sensitivity, and 74.2% specificity.
Why the study?
Does a low-cost heart rate sensor using time-domain features accurately detect mental stress?
Observational (n=46)
Does a low-cost heart rate sensor using time-domain features accurately detect mental stress?
A low-cost heart rate chest belt using simple time-domain features can detect mental stress with approximately 75% accuracy, suitable for mobile devices.
Supports feasibility of low-cost ambulatory stress detection; leaves open rigorous validation against clinical standards.
The automated detection of stress is a central problem for ambient assisted living solutions. The paper presents the concepts and results of two studies targeted at stress detection with a low cost heart rate sensor, a chest belt. In the device validation study ( n = 5), we compared heart rate data and other features from the belt to those measured by a gold standard device to assess the reliability of the sensor. With simple synchronization and data cleaning algorithm, we were able to select highly (>97%) correlated, low average error (2.2%) data segments of considerable length from the chest data for further processing. The protocol for the clinical study ( n = 46) included a relax phase followed by a phase with provoked mental stress, 10 minutes each. We developed a simple method for the detection of the stress using only three time-domain features of the heart rate signal. The method produced accuracy of 74.6%, sensitivity of 75.0%, and specificity of 74.2%, which is impressive compared to the performance of two state-of-the-art methods run on the same data. Since the proposed method uses only time-domain features, it can be efficiently implemented on mobile devices.
No takes yet. Share an insight, caveat, or question.
Salai et al. (2016) conducted an observational in Mental stress (n=46). Low-cost heart rate sensor (chest belt) vs. State-of-the-art methods was evaluated on Accuracy of stress detection. A stress detection method using three time-domain features from a low-cost heart rate chest belt achieved 74.6% accuracy, 75.0% sensitivity, and 74.2% specificity.