lightbulb现实痛点情绪、压力与心理健康状态推断在公共显示中,难以非侵入性地推断用户对内容的兴趣。UbiComp '21Inverse Foraging: Inferring Users’ Interest in Pervasive Displays
lightbulb现实痛点情绪、压力与心理健康状态推断情感识别系统无法准确适应用户的个体差异。UbiComp '24Systematic Evaluation of Personalized Deep Learning Models for Affect Recognition
lightbulb现实痛点情绪、压力与心理健康状态推断用户无法通过手机屏幕文本获得实时的情绪状态反馈。UbiComp '24Predicting Affective States from Screen Text Sentiment
lightbulb现实痛点情绪、压力与心理健康状态推断用户的大量在线文本未被有效用于预测心理健康风险。UbiComp '24Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data
lightbulb现实痛点情绪、压力与心理健康状态推断用户担心隐私问题,传统情感识别方法难以应用于日常生活。UbiComp '24Emotion Recognition on the Go: Utilizing Wearable IMUs for Personalized Emotion Recognition
lightbulb现实痛点情绪、压力与心理健康状态推断现有情绪推断模型在跨文化情境中表现欠佳,难以广泛应用。UbiComp '23Generalization and Personalization of Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight Countries
lightbulb现实痛点情绪、压力与心理健康状态推断现有压力检测方法个性化过强,无法实现普适性应用。UbiComp '23GSR Based Generic Stress Prediction System