论文标题
使用多模式生理数据和个人编年史对明天影响的客观预测：2020年监测大学生福祉的研究
Objective Prediction of Tomorrow's Affect Using Multi-Modal Physiological Data and Personal Chronicles: A Study of Monitoring College Student Well-being in 2020
论文作者
论文摘要
监测和理解情感状态是健康功能和基于情绪疾病的治疗的重要方面。无处不在的可穿戴技术的最新进展提高了此类工具在检测和准确估算精神状态（例如情绪，压力等）方面的可靠性，从而提供了随着时间的推移对个人的全面和连续监测。以前尝试建模个人精神状态的尝试仅限于主观方法或仅包含几种方式（即电话，手表）。因此，我们研究的目的是通过使用多个商业设备通过全自动和客观的方法来调查更准确预测影响的能力。纵向生理数据和每日评估情绪是从一年多的大学生中收集了一年多的大学生。结果表明，我们的模型能够以与最先进的方法相媲美的准确性来预测第二天的影响。
Monitoring and understanding affective states are important aspects of healthy functioning and treatment of mood-based disorders. Recent advancements of ubiquitous wearable technologies have increased the reliability of such tools in detecting and accurately estimating mental states (e.g., mood, stress, etc.), offering comprehensive and continuous monitoring of individuals over time. Previous attempts to model an individual's mental state were limited to subjective approaches or the inclusion of only a few modalities (i.e., phone, watch). Thus, the goal of our study was to investigate the capacity to more accurately predict affect through a fully automatic and objective approach using multiple commercial devices. Longitudinal physiological data and daily assessments of emotions were collected from a sample of college students using smart wearables and phones for over a year. Results showed that our model was able to predict next-day affect with accuracy comparable to state of the art methods.
