Utilizing Technology and AI Approaches to Facilitate Independence and Resilience in Older Adults

利用技术和人工智能方法促进老年人的独立性和适应能力

• 批准号: 10652011
• 负责人: Peter M. Abadir
• 金额: $ 27.81万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10652011
• 关键词: Addendum; Adverse effects; Affect; Agitation; Alzheimer' s disease related dementia; American; Anger; Antipsychotic Agents; Artificial Intelligence; Assisted Living Facilities; Awareness; Beds; Behavior; Boredom; Brain; Budgets; COVID-19; Calendar; Canada; Caregivers; Caring; Cessation of life; Classification; Client; Clinical; Code; Collaborations; Computer software; Country; Data; Data Analyses; Data Set; Databases; Dementia; Dementia caregivers; Depressed mood; Detection; Development; Development Plans; Direct Costs; Discipline of Nursing; Disinfection; Distress; Docking; Drug Prescriptions; Ear; Economics; Effectiveness; Elderly; Electronic Mail; Emerging Technologies; Emotional; Emotions; Equipment and supply inventories; Evaluation; Eye; Face; Facial Expression; Facial Muscles; Facilities and Administrative Costs; Family; Feeling; First Name; France; Frequencies; Fright; Fringe Benefit; Funding; Funding Agency; Future; Generations; Gifts; Goals; Grant; Happiness; Health; Health Technology; Healthcare; Home; Hour; Human; Human Resources; Impaired cognition; Industry; Institution; Institutional Review Boards; Instruction; Internet; Intervention; Israel; Japan; Knowledge; Language; Last Name; Lead; Life; LinkedIn; Loneliness; Long-Term Care; Machine Learning; Manuscripts; Maps; Measurement; Mediation; Memory; Mentors; Mind; Movement; Muscle; Music; National Institute on Aging; North America; Nurses; Nursing Homes; Participant; Patients; Pattern; Personal Satisfaction; Persons; Pharmaceutical Preparations; Pilot Projects; Play; Population; Positioning Attribute; Process; Provider; Psychologist; Public Health Schools; Quality of Care; Quality of life; Recording of previous events; Research; Research Assistant; Research Personnel; Resources; Robot; Role; Sampling; Schedule; Science; Sensory; Services; Side; Small Business Innovation Research Grant; Software Engineering; Standardization; Stress; Structure; Supervision; System; Systems Analysis; Techniques; Technology; Telephone; Testing; Thinking; Time; TimeLine; Training; United States; United States National Institutes of Health; Universities; Validation; Verbal Behavior; Visit; Visiting Nurse; Work; base; behavior measurement; college; community living; computer science; cost; cost effective; design; digital health; effectiveness trial; engineering design; experience; fall risk; feasibility testing; fitness; healthy aging; human subject; implementation barriers; improved; indexing; innovation; instrument; loved ones; member; movement analysis; neuropsychiatric symptom; neuropsychiatry; off-label use; pilot test; programs; recruit; research and development; resilience; software development; staff intervention; tool; translational impact; usability; web site

Detecting Agitation in Persons with AD/ADRD in a Nursing Home Using AI-based Facial Expression Analysis ABSTRACT 50% of nursing home residents have moderate or severe cognitive impairment. Persons with advanced AD/ADRD are often no longer able to communicate verbally. Agitation, which is found in 80% of residents with AD/ADRD, can pose a major problem for the resident, their family and professional caregivers. The inability to successfully manage AD/ADRD behaviors, often results in increased burden on caregivers and use of antipsychotic and other psychotropic medications which may have severe adverse effects. COVID-19 has also increased agitation incidents among residents with AD/ADRD and increased distress levels in both residents and caregivers. In this project we will integrate an AI-based facial expression analysis software with an autonomous navigating robot and validate that the integrated system can visit nursing home residents with advanced AD/ADRD and detect agitation.

使用基于人工智能的面部表情检测疗养院中 AD/ADRD 患者的躁动 分析 抽象的 50% 的疗养院居民有中度或重度认知障碍。先进人士 AD/ADRD 通常不再能够进行口头交流。躁动，80%的人都会出现这种情况 患有 AD/ADRD 的居民可能会给居民、他们的家人和专业人士带来重大问题 照顾者。无法成功管理 AD/ADRD 行为，通常会导致负担增加 关于护理人员以及使用抗精神病药和其他精神药物可能会产生严重的影响 不良影响。 COVID-19 还增加了患有 AD/ADRD 的居民的躁动事件 居民和护理人员的痛苦程度增加。 在这个项目中，我们将把基于人工智能的面部表情分析软件与自主的 导航机器人并验证集成系统可以以先进的方式拜访疗养院居民 AD/ADRD 并检测躁动。