Drowsiness detection using heart rate variability analysis based on microcontroller unit

Abstract

Drowsiness is one of the main cause of road accidents. Recently, drowsiness detection of driver based on biosignal like electrocardiogram is being studied. Alterations during drowsiness, fatigue, and stress of the driver can be obtained from heart rate variability (HRV). HRV is derived from interval of RR in electrocardiogram. In this article, we present drowsiness detection using HRV analysis based on microcontroller unit. Electrocardiogram signal is obtained by AD8232 module and processed in microcontroller unit. Electrocardiogram is recorded during the subject using driving simulator. We extract features from HRV and use radial basis function neural network to classify between drowsy and normal.