ECG and wearable computing for drowsiness detection

This thesis examines the challenges of using Electrocardiogram (ECG) signals in wearable computing systems, specifically in addressing drowsiness detection while driving. First, the analysis of ECG signal quality obtained from off-the-shelf wearable ECG monitors is presented. Then various approaches for extrapolating a person's waking/sleeping state using ECG time-series data is provided, and verified against real ECG data available from the PhysioBank data archives. Finally, the wearable system incorporating an ECG monitor and a mobile application for carrying out the data analysis and computation is described. The system's interface design is also presented, along with the approach to alerting drowsy drivers.