Analysis of non-typical emotions, such as stress, depression and engagement
is less common and more complex compared to that of frequently discussed
emotions like happiness, sadness, fear, and anger. The importance of these
non-typical emotions has been increasingly recognized due to their implications
on mental health and well-being. Stress and depression impact the engagement in
daily tasks, highlighting the need to understand their interplay. This survey
is the first to simultaneously explore computational methods for analyzing
stress, depression, and engagement. We discuss the most commonly used datasets,
input modalities, data processing techniques, and information fusion methods
used for the computational analysis of stress, depression and engagement. A
timeline and taxonomy of non-typical emotion analysis approaches along with
their generic pipeline and categories are presented. Subsequently, we describe
state-of-the-art computational approaches for non-typical emotion analysis,
including a performance summary on the most commonly used datasets. Following
this, we explore the applications, along with the associated challenges,
limitations, and future research directions.

对非典型情绪（如压力、抑郁和投入度）的分析比常见的情绪（如幸福、悲伤、恐惧和愤怒）更为复杂和不常见。这篇论文介绍了计算方法用于分析压力、抑郁和投入度的先前研究和最新技术，探讨了常用的数据集、输入模式、数据处理技术和信息融合方法，并概述了应用、挑战、限制和未来研究方向。