Stress Detection Using Low Cost Heart Rate Sensors

• Published in: Journal of healthcare engineering Vol. 2016; no. 2016; pp. 1 - 13
• Main Authors: Salai, Mario, Kósa, István, Vassányi, István
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2016; John Wiley & Sons, Inc
• Subjects: Adult; Algorithms; Analysis; Diagnosis; Female; Heart beat; Heart Rate - physiology; Humans; Male; Reproducibility of Results; Sensitivity and Specificity; Sensors; Signal Processing, Computer-Assisted; Stress (Psychology); Young Adult
• ISSN: 2040-2295; 2040-2309; 2040-2309
• DOI: 10.1155/2016/5136705

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.