Rus, Silvia ; Grosse-Puppendahl, Tobias ; Kuijper, Arjan (2017)
Evaluating the recognition of bed postures using mutual capacitance sensing.
In: Journal of Ambient Intelligence and Smart Environments, 9 (1)
doi: 10.3233/AIS-160414
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Capacitive sensing is increasingly used to gather contextual information about humans. They can be used to create stationary or mobile systems for non-contact activity recognition. They are able to sense any conductive objects at distances up to 50 cm. This paper investigates an approach to classify bed postures using mutual capacitance sensing. The goal is to develop a system that prevents decubitus ulcers, which is a condition caused by prolonged pressure on the skin that can result in injuries to the skin and underlying tissues. The posture recognition is used to detect prolonged lying in a single pose and can notify care personnel. A low-cost grid of crossed wires is proposed that is placed between the mattress and the bed sheet that creates 48 measurement points. The experiments analyze a set of five bedding positions with 14 users. Using self-defined features, we achieved an accuracy of 80.8% for all users and an accuracy of 93.8% for individuals of similar body size. Refining the classification approach by directly classifying the raw data an overall accuracy of 90.5% was reached. By introducing an uncertainty threshold the classification is correct in 97.6% of cases.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Rus, Silvia ; Grosse-Puppendahl, Tobias ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Evaluating the recognition of bed postures using mutual capacitance sensing |
| Sprache: | Englisch |
| Publikationsjahr: | 2017 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Journal of Ambient Intelligence and Smart Environments |
| Jahrgang/Volume einer Zeitschrift: | 9 |
| (Heft-)Nummer: | 1 |
| DOI: | 10.3233/AIS-160414 |
| URL / URN: | https://doi.org/10.3233/AIS-160414 |
| Kurzbeschreibung (Abstract): | Capacitive sensing is increasingly used to gather contextual information about humans. They can be used to create stationary or mobile systems for non-contact activity recognition. They are able to sense any conductive objects at distances up to 50 cm. This paper investigates an approach to classify bed postures using mutual capacitance sensing. The goal is to develop a system that prevents decubitus ulcers, which is a condition caused by prolonged pressure on the skin that can result in injuries to the skin and underlying tissues. The posture recognition is used to detect prolonged lying in a single pose and can notify care personnel. A low-cost grid of crossed wires is proposed that is placed between the mattress and the bed sheet that creates 48 measurement points. The experiments analyze a set of five bedding positions with 14 users. Using self-defined features, we achieved an accuracy of 80.8% for all users and an accuracy of 93.8% for individuals of similar body size. Refining the classification approach by directly classifying the raw data an overall accuracy of 90.5% was reached. By introducing an uncertainty threshold the classification is correct in 97.6% of cases. |
| Freie Schlagworte: | Activity recognition, Ambient assisted living (AAL), Capacitive sensors |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 04 Mai 2020 10:07 |
| Letzte Änderung: | 04 Mai 2020 10:07 |
| PPN: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum