Abnormality recognition during drowsy state from ECG and EEG

Monitoring of abnormality for aged patients while sleeping is one of the emerging applications in biomedical research. Now a day, most of the people are passed away while sleeping which is named as Sudden Unexpected Nocturnal Death Syndrome (SUNDS). The main reasons for SUNDS are failure of the heart and discontinuous breathing. The proposed work has employed both Electrocardiogram (ECG) and Electroencephalogram (EEG) to detect drowsy state. The Heart Rate Variability (HRV) is used to discover the abnormality during slumberous state. So the detection of QRS complexes in an Electrocardiogram signal provides information about the heart rate as well as various abnormalities such as hyperkalemia, cardiac hypertrophy, apnoea etc. The purpose of the proposed methodology is to generate warning flag for cardiac abnormality while sleeping. So the proposed consists both an ECG waveform and EEG waveform to check whether the person is in drowsy state or not. From Heart rate variability (HRV) analysis, develop a model for non-intrusive slumbering detection using LabVIEW on certain threshold value.