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Step by step: Early detection of diseases using an intelligent floor

: Scherf, Lisa; Kirchbuchner, Florian; Wilmsdorff, Julian von; Fu, Biying; Braun, Andreas; Kuijper, Arjan


Kameas, Achilles (Ed.):
Ambient Intelligence. 14th European Conference, AmI 2018 : Larnaca, Cyprus, November 12-14, 2018, Proceedings
Cham: Springer International Publishing, 2018 (Lecture Notes in Computer Science 11249)
ISBN: 978-3-030-03061-2 (Print)
ISBN: 978-3-030-03062-9 (Online)
ISBN: 978-3-030-03063-6
European Conference on Ambient Intelligence (AmI) <14, 2018, Larnaca>
Conference Paper
Fraunhofer IGD ()
Guiding Theme: Individual Health; Guiding Theme: Smart City; Research Area: Human computer interaction (HCI); mental health; personal health; home care; smart home; activity monitoring; Activities of daily living (ADLs)

The development of sensor technologies in smart homes helps to increase user comfort or to create safety through the recognition of emergency situations. For example, lighting in the home can be controlled or an emergency call can be triggered if sensors hidden in the floor detect a fall of a person. It makes sense to also use these technologies regarding prevention and early detection of diseases. By detecting deviations and behavioral changes through long-term monitoring of daily life activities it is possible to identify physical or cognitive diseases. In this work, we first examine in detail the existing possibilities to recognize the activities of daily life and the capability of such a system to conclude from the given data on illnesses. Then we propose a model for the use of floor-based sensor technology to help diagnose diseases and behavioral changes by analyzing the time spent in bed as well as the walking speed of users. Finally, we show that the system can be used in a real environment.