mmFall: Fall Detection Using 4-D mmWave Radar and a Hybrid Variational RNN AutoEncoder

Elderly fall prevention and detection becomes extremely crucial with the fast aging population globally. In this article, we propose mmFall , a novel fall detection system, which comprises 1) the emerging millimeter-wave (mmWave) radar sensor to collect the human body's point cloud along with t...

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Bibliographic Details
Published in:	IEEE transactions on automation science and engineering Vol. 19; no. 2; pp. 1245 - 1257
Main Authors:	Jin, Feng, Sengupta, Arindam, Cao, Siyang
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Activities of daily living Anomalies Anomaly detection Cameras Centroids Conditional probability Data collection Doppler radar Fall detection False alarms Inference Labelling millimeter wave (mmWave) radar Millimeter waves Older people Privacy Radar Radar antennas Radar data Radar detection Radar measurements Randomness recurrent autoencoder (RAE) Recurrent neural networks semisupervised learning Senior citizens Sensors Three-dimensional displays variational autoencoder
ISSN:	1545-5955, 1558-3783
Online Access:	Get full text
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