Published December 4, 2017
| Version v1
Conference paper
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Human Fall Detection from Acceleration Measurements Using a Recurrent Neural Network
- 1. Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
Description
In this work, a method for human fall detection is presented based on Recurrent Neural Networks. The ability of these networks to process and encode sequential data, such as acceleration measurements from body-worn sensors, makes them ideal candidates for this task. Furthermore, since such networks can benefit greatly from additional data during training, the use of a data augmentation procedure involving random 3D rotations has been investigated. When evaluated on the publicly available URFD dataset, the proposed method achieved better results compared to other methods.
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