FALL DETECTOR WITH RANDOM CLASSIFIER OPTIMIZATION

被引：0

作者：

Mend, M. ^{[1
]}

Kullmann, W. H. ^{[1
]}

机构：

[1] Univ Appl Sci Wurzburg Schweinfurt, Inst Med Engn, Wurzburg, Germany

来源：

BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK | 2013年 / 58卷

关键词：

Fall classification; random search; tri-axial accelerometer; fall detector;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Fall accidents are one of the main causes of injuries and accidental deaths for elder people. Automated fall detectors can be helpful for detecting the accident and sending an emergency call. For this purpose, a wearable fall detector device was developed, which served to collect a training set and to test certain classifiers. The current approach uses a random search algorithm to optimize a given model for discrimination of fall events from activities of daily living by measuring tri-axial accelerometer data. In the current state the device is able to recognize significant falls and can trigger an emergency call over mobile networks.

引用

页数：2

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