Driver drowsiness detection using the Humantenna effect

part 1

Bachelor Thesis (2025)
Author(s)

P. Nagy (TU Delft - Electrical Engineering, Mathematics and Computer Science)

S.M. Romijn (TU Delft - Electrical Engineering, Mathematics and Computer Science)

M. Demeestere (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

H. Bastawrous – Mentor (TU Delft - Electrical Engineering Education)

Willem D. van Driel – Graduation committee member (TU Delft - Electronic Components, Technology and Materials)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2025
Language
English
Graduation Date
24-06-2025
Awarding Institution
Delft University of Technology
Project
['EE3L11 Bachelor graduation project Electrical Engineering']
Programme
['Electrical Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Drowsy driving is a significant contributor to road accidents with existing detection technologies often falling short due to intrusiveness or environmental sensitivity. This thesis presents a non-invasive method for detecting driver alertness using the Humantenna effect: the phenomenon whereby the human body passively couples with ambient 50 Hz electromagnetic fields. By capacitively coupling the human body into a sensor in the vehicle’s steering wheel, grip strength and hand placement can be continuously monitored without requiring any wearable devices.
This project involves experimental validation of the Humantenna effect in a controlled environment, modelling of capacitive coupling as a function of grip strength, and the development of a custom amplifier circuit to condition the signal. Results demonstrate a consistent and measurable relation between grip strength and the amplitude of the 50 Hz signal. An operational amplifier-based configuration was found to be the most suitable for reliable signal conditioning. A functional multi-sensor prototype was developed and evaluated, indicating that the system is suitable for indoor use and scalable for integration into vehicle systems.

Files

Thesis_Hardware.pdf
(pdf | 6.22 Mb)
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