Scherf, Lisa ; Kirchbuchner, Florian ; Wilmsdorff, Julian von ; Fu, Biying ; Braun, Andreas ; Kuijper, Arjan (2018)
Step by Step: Early Detection of Diseases Using an Intelligent Floor.
European Conference on Ambient Intelligence (AmI). Larnaca, Cyprus (12.11.2018-14.11.2018)
doi: 10.1007/978-3-030-03062-9_11
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2018 |
| Autor(en): | Scherf, Lisa ; Kirchbuchner, Florian ; Wilmsdorff, Julian von ; Fu, Biying ; Braun, Andreas ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Step by Step: Early Detection of Diseases Using an Intelligent Floor |
| Sprache: | Englisch |
| Publikationsjahr: | 2018 |
| Ort: | Cham |
| Verlag: | Springer |
| Buchtitel: | Ambient Intelligence |
| Reihe: | Lecture Notes in Computer Science (LNCS) |
| Band einer Reihe: | 11249 |
| Veranstaltungstitel: | European Conference on Ambient Intelligence (AmI) |
| Veranstaltungsort: | Larnaca, Cyprus |
| Veranstaltungsdatum: | 12.11.2018-14.11.2018 |
| DOI: | 10.1007/978-3-030-03062-9_11 |
| URL / URN: | https://doi.org/10.1007/978-3-030-03062-9_11 |
| Kurzbeschreibung (Abstract): | 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. |
| Freie Schlagworte: | Mental health, Personal health, Home care, Smart home, Activity monitoring, Activities of daily living (ADLs) |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 10 Jul 2019 08:29 |
| Letzte Änderung: | 03 Jul 2024 10:57 |
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