Ambient water usage sensor for the identification of daily activities
| Autor: | Marco Eichelberg, Andreas Hein, Alexander Gerka, Finn Bayer, Melina Frenken |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Activities of daily living
020205 medical informatics Bathing Computer science business.industry Real-time computing SIGNAL (programming language) 020207 software engineering 02 engineering and technology Ambient water Identification (information) Embedded system 0202 electrical engineering electronic engineering information engineering business |
| Zdroj: | GIoTS |
| DOI: | 10.1109/giots.2017.8016249 |
| Popis: | Dementia patients, like most older adults, prefer to live in their own home as long as possible. This requires, however, that they are able to perform activities of daily living (ADL). Therefore, many research projects install different sensor setups to identify ADLs. Though the water usage correlates with many ADLs (i.e.: bathing, cooking) only few of these systems use water usage sensors. The reason is that there is no water usage sensor available that is unobtrusive, ambient and precise. In this article, we propose a water usage sensor that is based on a piezoelectric element that fulfills these requirements. We describe the implementation of the sensor system in a living lab. Additionally, we discuss different features that were extracted from the sensor signal and different machine learning algorithms that were used to classify the data. Finally, we present the results to several tests we performed to determine the accuracy of our sensor system under different environmental conditions. |
| Databáze: | OpenAIRE |
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