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WARE-Care: a novel RF-based system to assess and prevent falling

WARE-Care：一种基于射频的新型系统，用于评估和防止跌倒

基本信息

批准号：
10673041
负责人：
Siyang Cao
金额：
$ 21.63万
依托单位：
UNIVERSITY OF ARIZONA
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10673041
关键词：
3-Dimensional Adult Age Aging Agreement Alzheimer&apos s Disease Arizona Behavior Behavior monitoring Calibration Canes Care given by nurses Caring Cessation of life Charge Clinical Clinical Trials Communities Complement Data Databases Detection Development Devices Diagnostic Services Discipline of Nursing Disease Elderly Electromagnetic Energy Environment Evaluation Event Extremely High Frequency Radio Waves Face Fall prevention Forearm Gait Goals Health Height Hour Human Injury Laboratories Lighting Lower Extremity Machine Learning Maps Measurement Measures Medical Methods Modeling Monitor Motion Movement Network-based Nursing Homes Nursing Staff Participant Performance Persons Posture Prevention Privacy Privatization Probability Quality of life Radar Radiation Recovery Reporting Research Residual state Risk Risk Assessment Safety Sample Size Seizures Services Skeleton Sleep System Techniques Technology Testing Thigh structure Time Training Universities Unmarried person Upper Extremity Upper arm Validation Visual Walking Weight Work adverse outcome arm care costs care systems computer center cost data exchange deep learning design exposed human population fall risk falls fear of falling follow-up follower of religion Jewish frailty improved interest irritation kinematics learning network long short term memory meter motion sensor network architecture neural network neural network architecture novel pandemic disease portability privacy protection recruit response sensor sex signal processing skeletal movement smartphone application software development telehealth tool user-friendly walker wearable device wearable sensor technology wireless

项目摘要

Project Summary/Abstract Many falls in nursing facilities are not reported during night when older adults are alone. It can lead to reduced quality of life, increased fear of falling and restriction of activities, decreased ability to function, and increased risk of injuries or death. We propose WARE-Care: mmWave based fall Assessment and pRevEntion, 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. The system is safe, private, and user-friendly for nursing facility applications. The system is of strong interest to the nursing centers, including the local Handmaker Jewish Services For Aging center. The WARE-Care system is novel and unique and is based on the PI’s developments in mmWave radar combined with advanced machine learning techniques. The new field of mmWave radar opens opportunities for 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 accurately create a skeleton while respecting privacy, e.g. no detailed facial information will be collected. The non-touch, non-obtrusive sensor can be preferred to battery limited and potentially irritating body worn sensors during sleeping hours for elders. We will first build and verify the proposed system in different rooms including a typical restroom and bedroom in the nursing home. We will then apply new neural-network based methods to recover accurate skeleton movement and detect abnormal behavior of people regardless of age, sex, weight, or height. We will first recruit a group of healthy adults (18 or older) for setting up and training the proposed system. The system will further be validated on a targeted older group (65 and older), and be compared with wearable motion sensors. An interdisciplinary team has been assembled to develop and perform initial clinical validation of this novel system.

项目总结/文摘