发表机构
Data Science Research Centre, Tampere University（坦佩雷大学数据科学研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究为基于生理响应的休闲活动对幸福感影响的AI驱动分析相关文献进行综述，并提出优化幸福感评估的数据采集、分析及可视化设置的框架。
AI 中文摘要
幸福感是涵盖心理、社会、身体及认知健康的更广泛概念，休闲活动是促进幸福感的主要途径之一，在可衡量幸福感的各个领域存在多种休闲活动。尽管幸福感常通过主观量表评估，但心率、心率变异性、皮肤反应及脑活动数据等生理响应提供了评估幸福感水平的客观方式。相关研究聚焦于利用这些可测量生理信号开发AI驱动的幸福感分析概念。本研究对以往分析幸福感的相关文献进行综述，按休闲活动、数据采集场景、主观与客观数据、数据分析方法及评估标准对研究进行总结，此外，本研究还提出了一个用于优化幸福感评估的数据采集、分析及可视化设置的框架。
英文摘要
Well-being is a broader concept ensuring psychological, social, physical, and cognitive health. Recreational activities are one of the major approaches to facilitate well-being. There are various recreational activities in each of the domains in which well-being can be measured. Although well-being is often assessed using subjective scales, physiological responses such as heart rate, heart rate variability, skin responses and brain activity data provide objective ways to estimate the level of well-being. Research has focused on using these measurable physiological signals to develop AI driven well-being analysis concepts. This study presents a review of previous studies that have considered analyzing well-being. This review summarizes studies on the basis of recreational activities, data collection scenarios, subjective and objective data, data analysis methods and evaluation criteria. Furthermore, this study also proposes a framework to enhance data collection, analysis and visualization setup for the assessment of well-being.
