Driver Drowsiness Detection using the Humantenna effect
part 2
D.E. Laclé (TU Delft - Electrical Engineering, Mathematics and Computer Science)
H.I. Suleman (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M.A. Nguyen (TU Delft - Electrical Engineering, Mathematics and Computer Science)
H. Bastawrous – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M.A.P. Pertijs – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M. Taouil – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
Driver drowsiness poses significant road safety risks to both drivers and other users. This thesis proposes and evaluates a novel grip-strength sensing system that leverages the Humantenna effect, in which the human body picks up ambient electric fields from power lines, to monitor driver fatigue. Grip strength is sensed through capacitive coupling between the driver and an insulated wire embedded in the steering interface. Real-time signal processing extracts features such as root mean square (RMS) voltage levels, which are compared with measurements from a commercial force sensor. Under controlled laboratory conditions, the prototype accurately detects relative changes in grip strength. Drowsiness was additionally assessed with heart rate derived features to provide a physiological baseline, although time constraints prevented correlating grip and heart rate data within the same trials. Overall, the results demonstrate the feasibility of using power line induced voltages for grip-strength monitoring and suggest that, with further development and integration, this low-cost and non-invasive approach could contribute to future driver drowsiness detection systems.