支援安全與便利生活之居家照護系統設計與實作

隨著科技的進步、醫學生技的發展、人口死亡率的逐年降低，老年人口攀升，如今「老化(aging)」已被視為現代化的社會問題。而社會變遷，現今家庭結構的轉變，以往的大家庭或折衷家庭的居住模式如今已大為減少，在未來，有90%的老人將面臨養老問題，在老人養老的過程中，其健康的狀態，是兒女及照護首要關切的問題，由於行為代表健康，針對老人行為的瞭解與分析，已是眾多研究學者所關切的問題。本論文為了趕善老人在家養老的生活，與通過感知環境變化來防止危機發生，另外，在居家環境中採用物聯網技術，佈建許多感測器與無線傳輸設備，收集老人的居家行為，並設計專屬的居家便利生活系統，以達到用最小成本獲得最大效果。本論文更進一步透過資料採集，了解被照護者的行為活動與即時狀況，提供居家養老者健康、安心、安全的生活，有助於提升居家照護的生活品質。

關鍵字

居家照護；物聯網；高齡化社會；全面感知；危機提醒；行為辨識

並列摘要

With the progress of science and technology, the development of medical technology, the decline of population mortality year by year, the elderly population climbed, and now "aging (aging)" has been regarded as a modern social problem. In the future, 90% of the elderly will face the pension problem, the elderly in the process of old age, its healthy state. In the future, 90% of the elderly will face the pension problem. , Is the primary concern of children and care, because the behavior on behalf of health, understanding and analysis of the behavior of the elderly, many researchers are concerned about the issue. In order to prevent the crisis from happening in the elderly at home, and to prevent the crisis through the perception of environmental changes, in addition, in the home environment using Internet of things technology, the deployment of many sensors and wireless transmission equipment to collect the elderly home behavior, and Design the exclusive home convenience living system to achieve maximum cost with minimal cost. This paper will further improve the quality of life of home care through data collection, understanding the behavior and immediate situation of caregivers, providing health care for home carers, peace of mind and safety.

並列關鍵字

Home Care ； Internet of Things ； Aging society ； Comprehensive Perception ； Crisis reminders ； Behavior Identification

參考文獻

[1] 降低內科住院老人跌倒發生率改善方案,馬偕護理雜誌,11卷1期

[2] Luay Fraiwan, Khaldon Lweesy, Aya Bani-Salma and Nour Mani,“A Wireless Home Safety Gas Leakage Detection System, ” 2011 1st Middle East Conference on Biomedical Engineering (MECBME) , 2011

[4] Zih-Lun Huang ,Cing-Hao Jhuang ,Chun-Hsu Ko and Kuu-Young Young, “Development of Intention Detection and Control System for Robot Walking Helper,” 2016 International Conference on Advanced Robotics and Intelligent Systems (ARIS), 2016

[5] M. Daher, A. Diab, M. El Badaoui El Najjar, M. Ali Khalil, and F. Charpillet, “Elder Tracking and Fall Detection System using Smart Tiles,” IEEE Sensors Journal, 2017.

[6] Ehsan Nazerfard and Diane J. Cook, “CRAFFT: An Activity Prediction Model Based on Bayesian Networks,” Springer-Verlag Berlin Heidelberg , 2014.

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支援安全與便利生活之居家照護系統設計與實作

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