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Recognition of Bed Postures Using Mutual Capacitance Sensing

Rus, Silvia and Große-Puppendahl, Tobias and Kuijper, Arjan (2014):
Recognition of Bed Postures Using Mutual Capacitance Sensing.
In: Lecture Notes in Computer Science (LNCS); 8850, pp. 51-66, Springer, Berlin, Heidelberg, New York, Ambient Intelligence, DOI: 10.1007/978-3-319-14112-1₅,
[Conference or Workshop Item]

Abstract

In recent years, mutual capacitive sensing made significant advances in the field of gathering implicit contextual data. These systems find broad usage in pervasive activity-recognition systems, installed stationary or made portable. In the domain of context recognition new ways of interaction with the environment opened up since conductive objects can be detected under certain conditions at distances up to 50 cm. This paper investigates an approach to recognize bed postures using mutual capacitance sensing. The overall goal is to develop a technological concept that can be applied to recognize bed postures of patients in elderly homes. The use of this contextual data may lead to many desired benefits in elderly care e.g. the better prevention of decubitus ulcer, a condition caused by prolonged pressure on the skin resulting in injuries to skin and underlying tissues. For this, we propose a low-cost grid of crossed wires of 48 measurement points placed between the mattress and the bed sheet. The experimental results analyze a set of five lying positions. We achieved for all tested individuals an accuracy of 80.76 and for several individuals of the same bodysize an accuracy of 93.8.

Item Type: Conference or Workshop Item
Erschienen: 2014
Creators: Rus, Silvia and Große-Puppendahl, Tobias and Kuijper, Arjan
Title: Recognition of Bed Postures Using Mutual Capacitance Sensing
Language: English
Abstract:

In recent years, mutual capacitive sensing made significant advances in the field of gathering implicit contextual data. These systems find broad usage in pervasive activity-recognition systems, installed stationary or made portable. In the domain of context recognition new ways of interaction with the environment opened up since conductive objects can be detected under certain conditions at distances up to 50 cm. This paper investigates an approach to recognize bed postures using mutual capacitance sensing. The overall goal is to develop a technological concept that can be applied to recognize bed postures of patients in elderly homes. The use of this contextual data may lead to many desired benefits in elderly care e.g. the better prevention of decubitus ulcer, a condition caused by prolonged pressure on the skin resulting in injuries to skin and underlying tissues. For this, we propose a low-cost grid of crossed wires of 48 measurement points placed between the mattress and the bed sheet. The experimental results analyze a set of five lying positions. We achieved for all tested individuals an accuracy of 80.76 and for several individuals of the same bodysize an accuracy of 93.8.

Series Name: Lecture Notes in Computer Science (LNCS); 8850
Publisher: Springer, Berlin, Heidelberg, New York
Uncontrolled Keywords: Business Field: Digital society, Research Area: Human computer interaction (HCI), Activity recognition, Capacitive sensors, Ambient assisted living (AAL)
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: Ambient Intelligence
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1007/978-3-319-14112-1₅
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