Reliable Quasi-Static Post-Fall Floor-Occupancy Detection Using Low-Cost Millimetre-Wave Radar

TL;DR

This paper presents a reliable post-fall floor-occupancy detection method using low-cost 60 GHz radar, demonstrating improved accuracy in realistic indoor environments relevant to long-term care facilities.

Contribution

It introduces a novel preprocessing approach with MVDR beamforming that enhances post-fall detection accuracy over existing vendor-provided methods.

Findings

Proposed method increases mean frame-positive rate from 0.823 to 0.916.

Evaluation conducted with 7 participants in a furnished indoor environment.

Method effectively distinguishes minimal motion post-fall signals.

Abstract

As the population ages rapidly, long-term care (LTC) facilities across North America face growing pressure to monitor residents safely while keeping staff workload manageable. Falls are among the most critical events to monitor due to their timely response requirement, yet frequent false alarms or uncertain detections can overwhelm caregivers and contribute to alarm fatigue. This motivates the design of reliable, whole end-to-end ambient monitoring systems from occupancy and activity awareness to fall and post-fall detection. In this paper, we focus on robust post-fall floor-occupancy detection using an off-the-shelf 60 GHz FMCW radar and evaluate its deployment in a realistic, furnished indoor environment representative of LTC facilities. Post-fall detection is challenging since motion is minimal, and reflections from the floor and surrounding objects can dominate the radar signal return. We compare a vendor-provided digital beamforming (DBF) pipeline against a proposed preprocessing approach based on Capon or minimum variance distortionless response (MVDR) beamforming. A cell-averaging constant false alarm rate (CA-CFAR) detector is applied and evaluated on the resulting range-azimuth maps across 7 participants. The proposed method improves the mean frame-positive rate from 0.823 (DBF) to 0.916 (Proposed).