Indoor Positioning and Fall Detection System Without Wearables

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Bachelor Thesis (2023)
Author(s)

G.W. Mulder (TU Delft - Electrical Engineering, Mathematics and Computer Science)

K.N. Hernández Salvador (TU Delft - Electrical Engineering, Mathematics and Computer Science)

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

Contributor(s)

P. J. French – Mentor (TU Delft - Bio-Electronics)

K. Rassels – Mentor (TU Delft - Biomechatronics & Human-Machine Control)

İlke Ercan – Coach (TU Delft - Electrical Engineering Education)

T. Costa – Coach (TU Delft - Bio-Electronics)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2023 Gerben Mulder, Kim Hernández Salvador, Mounzir Baroud
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Gerben Mulder, Kim Hernández Salvador, Mounzir Baroud
Graduation Date
27-06-2023
Awarding Institution
Delft University of Technology
Programme
['Electrical Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
Reuse Rights

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Abstract

This thesis report, one of a set of two reports, describes a novel way to detect incidents that could occur in the daily life of the elderly. Unlike most systems already implemented in this field, this system does not use any wearable (positioning) sensors and works off an Single Board Computer (SBC).Independent of both of these systems is a system for reassurance to alleviate distress.

Files

BAP_Report_Radar_redacted.pdf
(pdf | 0.0859 Mb)
License info not available