With an increasing population of elderly people the number of falls and fall-related injuries is on the rise. This will cause changes for future health care systems, and both fall detection and fall prevention will pose a major challenge. Ambient Assisted Living (AAL) is a research area in which concepts and information systems for assisting elderly individuals are developed. Fall detection, as an important discipline of AAL, investigates a broad range of approaches including wearable devices. With their growing popularity, mobile devices with their embedded motion sensors, their software capabilities and cost-efficiency are well-suited for fall detection. A test framework for collecting and analyzing data regarding fall detection is presented. The framework consists of a RESTful Web service, a relational database and a Web-based back end. It offers an open interface to support a variety of devices. The system architecture is based on the state-of-the-art theoretical background of AAL and on the evaluation of an existing software. In order to test the framework, a mobile device client recording accelerometer and gyroscope sensor data is implemented on the iOS platform.
| Autorius: | Stefan Almer |
| Leidėjas: | AV Akademikerverlag |
| Išleidimo metai: | 2012 |
| Knygos puslapių skaičius: | 184 |
| ISBN-10: | 3639457560 |
| ISBN-13: | 9783639457568 |
| Formatas: | 220 x 150 x 12 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
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