SCH: Robotic Caregiver to Comprehend, Assist, Relieve, and Evaluate for Patients with Alzheimer’s Disease (Robotic CARE for AD)

SCH：用于理解、协助、缓解和评估阿尔茨海默病患者的机器人护理员（Robotic CARE for AD）

• 批准号: 10437154
• 负责人: Xiaopeng Zhao
• 金额: $ 29.93万
• 依托单位: UNIVERSITY OF TENNESSEE KNOXVILLE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-15 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10437154
• 关键词: Accounting; Address; Alzheimer' s Disease; Alzheimer' s disease care; Alzheimer' s disease patient; Alzheimer' s disease related dementia; American; Biomedical Engineering; Caregivers; Caring; Cognitive; Dementia; Discipline of Nursing; Emotions; Family; Gerontology; Intelligence; Learning; Patients; Personal Satisfaction; Persons; Preparation; Psychological reinforcement; Quality of life; Resources; Robot; Robotics; Societies; Stress; System; United States; aged; brain computer interface; cognitive rehabilitation; cognitive testing; computer science; deep learning; dementia care; feeding; humanoid robot; improved; innovation; instrumental activity of daily living; interdisciplinary approach; medical specialties; multimodality; neurophysiology; robot assistance; unsupervised learning

As the number and proportion of people aged 65 or older continue to increase in the United States, the number of Americans living with dementia is also growing. Among all dementia, Alzheimer’s disease (AD) and related dementia (ADRD) is the most common cause, accounting for approximately 60%-80% of the cases. Improving the care of people living with ADRD impacts the lives of not only the patients and their family but also the caregivers and their family, posing significant challenges to the well-being of the society. The purpose of this project is to exploit the autonomy and intelligence capability of a humanoid robot to comprehend, assist, relieve, and evaluate (CARE) patients with AD. The proposed Robotic CARE system has the capacity to detect the emotion and cognitive state of an AD patient, communicate and collaborate with the patient to accomplish basic instrumental activities of daily living (IADL) such as meal preparation, laundry, self-feeding, as well as help caregivers by reducing their levels of burden and stress. The proposed system could effectively bridge the CARE gap in our society, offering unprecedented potential for improving the quality of lives of both the patients and their caregivers. It is worth mentioning that the proposed Robotic CARE system is not to replace the caregivers, but rather to supplement the caregivers while providing companionship for AD patients since the system will learn to automatically assess patients’ cognitive state so as to better understand and respond to patients’ need. The CARE system is expected to advance the state-of-the-art in several related fields with its innovative and unique integration of cognitive assessment and rehabilitation with robot-assisted care. The proposed system makes contributions from three perspectives. First, cognitive assessment using instrumental activities of daily living (IADL) for patient-caregiver interaction will be conducted. Second, neurophysiological assessment using multimodal integration and unsupervised learning for patient-robot interaction will be conducted. Third, co-robot assessment using reinforcement learning for patient-robot-caregiver interaction will be conducted. The proposed team includes expertise from nursing with specialty in dementia care and gerontology, biomedical engineering with specialty in brain-computer interface, and computer science with specialty in machine/deep learning.

随着美国65岁或以上人口的数量和比例继续增加， 患有痴呆症的美国人的数量也在增加。在所有痴呆中，阿尔茨海默病(AD) 而相关痴呆症(ADRD)是最常见的原因，约占 案子。改善对ADRD患者的护理不仅影响患者和他们的生活 以及照料者和他们的家人，对老年人的福祉构成了重大挑战 社会。这个项目的目的是开发人形机器人的自主性和智力能力 机器人来理解、帮助、缓解和评估(护理)AD患者。提议的机器人护理 系统具有检测AD患者的情绪和认知状态、交流和 与患者协作完成日常生活的基本工具性活动(IADL)，如进餐 准备、洗衣、自我喂养，以及通过减轻照顾者的负担和压力来帮助他们。 拟议的系统可以有效地弥合我们社会中的护理差距，提供前所未有的 有可能提高患者及其照顾者的生活质量。值得一提的是 建议的机器人护理系统不是要取代照顾者，而是要补充 照顾者同时为AD患者提供陪伴，因为系统将自动学习 评估患者的认知状态，以便更好地了解和回应患者的需求。 该护理系统有望通过其创新的技术推动相关领域的最先进技术 认知评估和康复与机器人辅助护理的独特结合。建议数 制度从三个角度做出了贡献。第一，使用工具性的认知评估 将进行患者与照顾者互动的日常生活活动(IADL)。第二, 基于多模式集成和无监督学习的患者-机器人神经生理评估 将进行互动。第三，基于强化学习的协作机器人评估 将进行患者-机器人-护理员的互动。拟议的团队包括护理方面的专业知识 擅长痴呆症护理和老年学，擅长脑计算机的生物医学工程 接口和计算机科学，擅长机器/深度学习。