Assessing the Effect of Care Treatment Using Face Emotional Analysis and Cognitive Computing

Abstract

In the practice of scientific nursing care, it is essential to assess the quality and effect of nursing care services, since the caregivers must know whether or not the care was effective for the target person. Currently, however, the assessment relies on human subjective questionnaire and assessment sheets. Hence, it is difficult to justify the quality and effect as such the evidences encouraged in the scientific nursing care. To cope with the problem, this paper proposes Face Emotion Tracker (FET) that evaluates the effect of care as a transition of emotions of a person under care. The proposed system can produce real-time data quantifying emotions of the target person under care, which is more objective and fine-grained clinical data compared to the conventional manual assessment sheets. We then propose a metric that quantifies the quality of care.