Abstract
The present work deals with the development and evaluation of a radar-based fall detection system and emphasizes its potential as a non-invasive and privacy-preserving approach compared to traditional methods. The motivation for this research stems fromthe need for efficient fall detection systems that maximize user comfort and privacy.
The radar-based approach offers significant advantages over wearable devices and camera systems, as it eliminates the need for constant contact and visual monitoring.
The main results of this work include the high precision of the radar system in
recognizing typical fall movements under standardized conditions, which is due to the
effective combination of radar technology and motion analysis algorithms. The main
component of the applied algorithms is peak detection, which filters the radar data and
prepares it for further analyses. The system demonstrated a satisfactory detection rate
in various test scenarios, particularly in the case of falls from a standing position. However, analyzing the results also identifies challenges such as the need to calibrate and
adapt the system to different environments and user groups. Comparisons with existing
systems showed that the radar-based solution offers a good balance between accuracy,
comfort and privacy, although it needs to be further optimized for widespread practical
application.
In summary, the developed radar-based fall detection system is a promising solution
that offers significant advantages in terms of accuracy and privacy. Future research will
focus on overcoming current limitations and improving the integration of the system into
existing health monitoring systems, as well as improving the accuracy of fall detection
algorithms through the application of artificial intelligence or multi-sensor systems.
| Date of Award | 2024 |
|---|---|
| Original language | German (Austria) |
| Supervisor | Josef Langer (Supervisor) |