There is a close correlation between stress and health risk factors such as poor immune function and cardiovascular problems. Various researches showed that long-term exposure to stress and its related diseases are responsible of dramatic increase of mortality in the Western Countries. In this context, the European Collaborative Project INTERSTRESS is aimed at designing and developing advanced simulation and sensing technologies for the assessment and treatment of psychological stress, based on mobile biosensors. In this paper a wearable system able to implement the acquisition and the real-time elaboration of the ECG signal for stress management purposes will be described. A novel and robust algorithm for QRS complex detection has been developed. Robust QRS detection is fundamental to evaluate Heart Rate and Heart Rate Variability that are relevant parameters used as quantitative marker related to mental stress. In comparison to existing solutions the realized algorithm presents many advantages: an adaptive optimal filtering technique that avoids the use of thresholds and empirical rules for R peaks detection, low computational cost for real time elaboration and good tollerance with noisy ECG signal.
Wearable biomonitoring system for stress management: A preliminary study on robust ECG signal processing
CARBONARO, NICOLA;ANANIA, GAETANO;DE ROSSI, DANILO EMILIO;TOGNETTI, ALESSANDRO;
2011-01-01
Abstract
There is a close correlation between stress and health risk factors such as poor immune function and cardiovascular problems. Various researches showed that long-term exposure to stress and its related diseases are responsible of dramatic increase of mortality in the Western Countries. In this context, the European Collaborative Project INTERSTRESS is aimed at designing and developing advanced simulation and sensing technologies for the assessment and treatment of psychological stress, based on mobile biosensors. In this paper a wearable system able to implement the acquisition and the real-time elaboration of the ECG signal for stress management purposes will be described. A novel and robust algorithm for QRS complex detection has been developed. Robust QRS detection is fundamental to evaluate Heart Rate and Heart Rate Variability that are relevant parameters used as quantitative marker related to mental stress. In comparison to existing solutions the realized algorithm presents many advantages: an adaptive optimal filtering technique that avoids the use of thresholds and empirical rules for R peaks detection, low computational cost for real time elaboration and good tollerance with noisy ECG signal.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
