In this paper, a new method for the detection of apnea/hypopnea periods in physiological data is presented. The method is based on the intelligent combination of an integrated sensor system for long-time cardiorespiratory signal monitoring and dedicated signal-processing packages. Integrated sensors are a PVDF film and conductive fabric sheets. The signal processing package includes dedicated respiratory cycle (RC) and QRS complex detection algorithms and a new method using the respiratory cycle variability (RCV) for detecting apnea/hypopnea periods in physiological data. Results show that our method is suitable for online analysis of long time series data.
In their study, Adnane et al. presented a new method for detecting apnea periods by using signal processing packages REF .
Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring
Sensors (Basel, Switzerland)
Sensors (Basel, Switzerland)
Computer Science Engineering Medicine