This article presents a new deep-learning approach for automated fall detection from signatures of a continuous-wave micro-Doppler radar.

Motivated by these insights, we developed a deep-learning-based fall detection network on a Doppler radar sensor called convolutional bidirectional long short- ...

Abstract— Falls are a major public health concern and the leading cause of accidental deaths among elders. Technologies capable of fast and accurate fall ...

The results demonstrate that the proposed fall detection method outperforms the other methods in terms of higher accuracy, precision, sensitivity, and.

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A new deep-learning approach for automated fall detection from signatures of a continuous-wave micro-Doppler radar that applies convolutional neural networks.

In particular, the proposed method utilizes a deep convolutional neural network for automating feature extraction as well as global maximum pooling technique ...

Aryokee is introduced, an RF-based fall detection system that uses convolutional neural networks governed by a state machine that works with new people and ...

This survey offers an in-depth analysis of radar-based fall detection, with emphasis on Micro-Doppler, Range-Doppler, and Range-Doppler-Angles techniques.

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