Fall Detection and Posture Tracking
Indoor Positioning and Fall Detection System Without Wearables
C.T. Kopar (TU Delft - Electrical Engineering, Mathematics and Computer Science)
D.J. Rugge (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M. Rozema (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Kianoush Rassels – Mentor (TU Delft - Biomechatronics & Human-Machine Control)
P. J. French – Mentor (TU Delft - Bio-Electronics)
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Abstract
In the past decades, the workload and the pressure on medical personnel has been growing to an unprecedented peak. This is partly due to the ageing population and the increasing capabilities to be independent at an older age, increasing the age people enter nursing homes. This paper focuses on a novel way to detect incidents that could occur in the daily life of the elderly. Unlike most systems already proposed by others, there will be no use of wearable positioning sensors and the system is implemented on an Single Board Computer (SBC). This thesis report is one of a set of two reports discussing the final implementation of the system.