  Affective computing, which aims to recognize, interpret, and understand human
emotions, provides benefits in healthcare, such as improving patient care and
enhancing doctor-patient communication. However, there is a noticeable absence
of a comprehensive summary of recent advancements in affective computing for
healthcare, which could pose difficulties for researchers entering this field.
To address this, our paper aims to provide an extensive literature review of
related studies published in the last five years. We begin by analyzing trends,
benefits, and limitations of recent datasets and affective computing methods
devised for healthcare. Subsequently, we highlight several healthcare
application hotspots of current technologies that could be promising for
real-world deployment. Through our analysis, we identify and discuss some
ongoing challenges in the field as evidenced by the literature. Concluding with
a thorough review, we further offer potential future research directions and
hope our findings and insights could guide related researchers to make better
contributions to the evolution of affective computing in healthcare.
