Health Secure Radar: Use of Micro Doppler Signatures for Health Care and Security Applications

Microwave-based radar sensors are increasingly been used for healthcare and security applications. The software defined implementation of the radars allows fall detection and classification of different types of motions enabling elderly care and monitoring without privacy invading cameras. In addition, such radar sensor allow seeing through visually opaque materials suitable for security applications. This paper investigates the use of micro-Doppler signatures of slowly moving objects to localize and detect and classify human micro-motions. Using the NI SDRs, we measure micro-Doppler signatures of various human motion scenarios. Thereafter, the micro Doppler signatures' data is augmented before being used to train a convolutional neural network that detects and identifies the fall events.

Automated summary

Microwave-based radar sensors are increasingly used in healthcare and security applications. The software-defined implementation allows detection and classification of different types of motions, suitable for elderly care and monitoring, as well as seeing through visually opaque materials for security applications. Investigating the use of micro-Doppler signatures for localizing and detecting human micro-motions, a convolutional neural network is trained to identify fall events after augmenting the micro-Doppler data.