Project Summary/Abstract Many falls in nursing facilities are not reported during night when older adults are alone. It can lead toreduced quality of life increased fear of falling and restriction of activities decreased ability to function andincreased risk of injuries or death. We propose WARE-Care: mmWave based fall Assessment andpRevEntion as a non-intrusive system to work during the night to collect and assess older adults falling data.WARE-Care will provide an accurate measurement of movement and be compact and easy to set up. Thesystem is safe private and user-friendly for nursing facility applications. The system is of strong interest to thenursing centers including the local Handmaker Jewish Services For Aging center. The WARE-Care system is novel and unique and is based on the PIs developments in mmWave radarcombined with advanced machine learning techniques. The new field of mmWave radar opens opportunitiesfor elders monitoring with significant advantages that complement existing visual and body-worn sensors.mmWave radar operates in all lighting conditions and generates a point cloud that can be used to accuratelycreate a skeleton while respecting privacy e.g. no detailed facial information will be collected. The non-touchnon-obtrusive sensor can be preferred to battery limited and potentially irritating body worn sensors duringsleeping hours for elders. We will first build and verify the proposed system in different rooms including atypical restroom and bedroom in the nursing home. We will then apply new neural-network based methods torecover accurate skeleton movement and detect abnormal behavior of people regardless of age sex weightor height. We will first recruit a group of healthy adults (18 or older) for setting up and training the proposedsystem. The system will further be validated on a targeted older group (65 and older) and be compared withwearable motion sensors. An interdisciplinary team has been assembled to develop and perform initial clinicalvalidation of this novel system.