An Emergency Response System to Support Early Stage Dementia Patients

Md. Akbar Hossain, S. Ray, Geri Harris, Shakil Ahmed
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Abstract

Dementia patients living alone in the communities without much support from near and dear ones find it chal-lenging to receive instant help when needed including during emergencies. This work focuses on designing an end - to-end response system primarily to support early-stage Alzheimer's dementia (AD) patients living alone in their homes, in case of emergencies, including medical emergencies. The system aided with pervasive technologies can integrate AD patients, informal caregivers, and formal caregivers to support AD patients in need. Informal caregivers act as first responders to attend to patients and selecting appropriate informal caregivers based on certain predefined parameters is an important component of this system. This work has used single and ensemble Machine Learning (ML) algorithms for binary (to check if informal caregiver is available) and multiclass (to select the most suitable informal caregiver) classification.
支持早期痴呆患者的紧急响应系统
独居社区的痴呆症患者没有亲朋好友的支持,在需要的时候,包括紧急情况下,很难获得即时帮助。这项工作的重点是设计一个端到端响应系统,主要用于在紧急情况下,包括医疗紧急情况下,支持独居的早期阿尔茨海默氏痴呆症(AD)患者。在普及技术的帮助下,该系统可以整合阿尔茨海默病患者、非正式护理人员和正式护理人员,以支持有需要的阿尔茨海默病患者。非正式护理人员作为第一响应者来照顾患者,根据某些预定义参数选择合适的非正式护理人员是该系统的重要组成部分。这项工作使用了单一和集成机器学习(ML)算法进行二进制(检查是否有非正式护理人员)和多类(选择最合适的非正式护理人员)分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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