[论文解读] Framework for an Intelligent Affect Aware Smart Home Environment for Elderly People

Nirmalya Thakur, Chia Y. Han|arXiv (Cornell University)|Feb 28, 2019

Context-Aware Activity Recognition Systems参考文献 18被引用 8

一句话总结

本文提出了一种面向老年用户的智能、情感感知型智能家居框架，通过物联网数据实时分析并预测其情绪状态与用户体验。通过在交互开始前预测情感反应，该系统增强了个性化与适应性，从而提升生活质量——在三个数据集上验证，预测性能表现良好。

ABSTRACT

The population of elderly people has been increasing at a rapid rate over the last few decades and their population is expected to further increase in the upcoming future. Their increasing population is associated with their increasing needs due to problems like physical disabilities, cognitive issues, weakened memory and disorganized behavior, that elderly people face with increasing age. To reduce their financial burden on the world economy and to enhance their quality of life, it is essential to develop technology-based solutions that are adaptive, assistive and intelligent in nature. Intelligent Affect Aware Systems that can not only analyze but also predict the behavior of elderly people in the context of their day to day interactions with technology in an IoT-based environment, holds immense potential for serving as a long-term solution for improving the user experience of elderly in smart homes. This work therefore proposes the framework for an Intelligent Affect Aware environment for elderly people that can not only analyze the affective components of their interactions but also predict their likely user experience even before they start engaging in any activity in the given smart home environment. This forecasting of user experience would provide scope for enhancing the same, thereby increasing the assistive and adaptive nature of such intelligent systems. To uphold the efficacy of this proposed framework for improving the quality of life of elderly people in smart homes, it has been tested on three datasets and the results are presented and discussed.

研究动机与目标

• 应对老龄化人群在身体和认知能力方面面临挑战时，对辅助性、适应性及智能化技术日益增长的需求。
• 通过提供长期、个性化的智能家居解决方案，减轻医疗保健系统的经济与社会负担。
• 通过实时情感状态分析与智能家居环境中用户体验的预测建模，提升老年用户的生活质量。
• 开发一种在用户交互发生前即可预测情感反应的系统，从而实现环境的主动适应。

提出的方法

• 利用基于物联网的传感技术，收集老年用户在智能家居环境中实时的行为与生理数据。
• 应用情感计算技术，从多模态数据（如语音、动作、交互模式）中分析情绪成分。
• 采用机器学习模型，基于情感状态与情境交互预测用户体验。
• 使用预测机制在活动启动前预判情感反应，实现环境的预先适应。
• 集成情感反馈回路，动态调整环境设置（如照明、温度、提醒），以提升用户舒适度。
• 通过三个真实世界数据集验证该框架，评估其预测准确率与系统响应能力。

实验结果

研究问题

• RQ1 在物联网赋能的智能家居环境中，如何准确检测并实时分析老年用户的情感状态？
• RQ2 该系统在用户活动开始前，能在多大程度上预测用户体验？
• RQ3 该框架的预测能力在多大程度上提升了智能家居系统的适应性与辅助性？
• RQ4 在多样化的现实世界数据集中，该情感感知框架在情感预测准确率方面的表现如何？

主要发现

• 该框架成功利用多模态物联网数据，分析老年用户与智能家居系统交互中的情感成分。
• 实现了在活动启动前对用户体验的预测建模，从而能够主动调整环境。
• 通过预测情感反应，系统展现出更高的适应性，从而提升了个性化程度与用户满意度。
• 在三个数据集上的验证结果证实了该框架在真实智能家居场景中的鲁棒性与可靠性。
• 结果表明，情感感知预测显著提升了智能家居系统对老年用户的辅助质量。
• 由于具备预测与自适应能力，该框架在长期居家养老解决方案中展现出潜在应用前景。