Autonomous Navigating Robot for Detecting Falls and Risk of Falls in Nursing Home Residents with Alzheimer's Disease /ADRD

摘要 每年有一半到四分之三的养老院(NH)居民倒闭。约5%的 65岁及以上的成年人住在养老院，但养老院的居民占20% 这个年龄段的跌倒死亡人数。50%的养老院居民患有中度或重度 认知障碍。患有阿尔茨海默病或ADRD的老年人比 他们的同龄人没有认知障碍。跌倒往往会造成严重的后果，特别是在 虚弱的老年居民。每10名跌倒的居民中就有一人有严重的相关伤害，大约 每年有6.5万名患者患有髋部骨折。没有受伤的跌倒的居民通常会患上 对跌倒的恐惧导致自我限制活动，从而导致能力下降 功能障碍和生活质量下降。坠落会对设施造成重大影响，包括 跌倒者需要更多的护理，工作人员的文书工作增加，调查结果不佳， 诉讼和更高的保险费。大多数跌倒(66%-75%)发生在居民的房间和 几乎一半(48%)的人以受伤告终。对跌倒后不久的人进行治疗对 从身体和精神上从跌倒中恢复过来。现有的跌倒检测系统使用静态 居民房间里的摄像头侵犯了居民的隐私，可能无法检测到 从摄像机中隐藏的或在黑暗中发生的坠落。工作人员的严重短缺 养老院可能会造成在一段时间内没有察觉到跌倒的情况。 拟议的研究涉及集成一种负担得起的自主导航机器人，该机器人 已成功应用于疗养院痴呆症病房，配有红外摄像机，图像 处理软件和人工智能将成为巡逻走廊和房间的另一双“眼睛” 养老院的居民，并检测跌倒和跌倒的风险，并提醒工作人员，以便他们可以 立即处理。

ABSTRACT Between half and three-quarters of nursing home (NH) residents fall each year. About 5% of adults 65 and older live in nursing homes, but nursing home residents account for 20% of deaths from falls in this age group. 50% of nursing home residents have moderate or severe cognitive impairment. Older adults with Alzheimer’s Disease or ADRD are more likely to fall than their peers without cognitive impairment. Falls often have serious consequences, especially in frail older residents. One in every 10 residents who fall has a serious related injury and about 65,000 patients suffer hip fracture each year. Residents who fall without injury often develop a fear of falling that leads to self-imposed limitation of activity leading to a decrease in the ability to function and a reduced quality of life. Falls have major consequences for facilities including increased levels of care required for fallers, increased paperwork for staff, poor survey results, lawsuits and higher insurance premiums. Most falls (66%-75%) occur in the resident’s room and almost half (48%) end in an injury. Treating a person shortly after falling is critical to the recovery from the fall both physically and mentally. Existing fall detection systems use static cameras in the rooms of residents which violate resident privacy and may be unable to detect falls that are hidden from the camera or that occur in the dark. The acute shortage of staff in nursing homes may create situations where a fall is undetected for a while. The proposed study involves integration of an affordable autonomous navigating robot which has been used successfully in nursing home dementia units, with an infra-red camera, image processing software and AI to be an additional “set of eyes” to patrol the corridors and rooms of nursing homes residents and to detect falls and risk of falls and alert staff so they can be handled immediately.