Networked multi-sensor rollator with AI-assisted fall detection
Markus L. R. Schwarz, Vincent Gauda, Markus Kaiser, Henrik K. J. Kuttruff, Jonas Rentzsch, Maximilian Thür · 2023
This contribution describes a networked and energy-autonomous rollator, primarily designed to increase the users safety. To achieve this, a multi-sensor approach is used to provide sufficient data for classification of activity patterns, detection of long term changes in agility as well as fall detection, supported by AI technology. For data economy, networking of the rollator in outdoor areas is limited to the transmission of emergency situations via mobile radio to inform caregivers. With the user's consent, analysis of medium-and long-term changes in movement and activity behaviour can also be transmitted as an option.