A multimodal approach using deep learning for fall detection

作者：

Highlights：

• We achieved the state-of-art in UP-Fall dataset.

• Deep learning approach to detect falls with cheap equipment.

• Fall detection systems are cheaper compared to the daily surveillance of a person.

• Multimodality with deep learning for fall detection reduce false positives events.

摘要

•We achieved the state-of-art in UP-Fall dataset.•Deep learning approach to detect falls with cheap equipment.•Fall detection systems are cheaper compared to the daily surveillance of a person.•Multimodality with deep learning for fall detection reduce false positives events.

论文关键词：Multimodal,Fall detection,Elderly people,Deep learning,Accelerometers,Camera,Cnn,Convolutional neural network,Convnet

论文评审过程：Received 15 June 2019, Revised 2 September 2020, Accepted 2 November 2020, Available online 16 November 2020, Version of Record 24 January 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114226