Pain Assessment Using Intelligent Computing Systems

Abstract

Inadequate pain assessment, increased medical expenditure, decreased productivity and improper treatment are the global challenging problems which often lead to hindrances and loss of interest in life. Intelligent computing systems (ICS) play a significant role in improving the accuracy of pain assessment and supporting the health care practitioners in the clinical decision-making process . The computational aspects of pain assessment, to acquire knowledge from the clinical data received by patients or experts, are focused in this review. The method used an extensive literature search in various reputed journals and electronic databases in order to extract the articles related to ICS considering both chronic and acute pain symptoms of patients, published between 1992 and 2014 in the English language. In total, forty-five studies were analyzed, thirty-two were selected from 1320 citations, and ten were obtained from reference tracking. The computer technologies identified were grouped together into following four categories in the result section comprising of artificial neural networks, rule-based algorithms, statistical learning algorithms and nonstandard set theory. Methodologies such as questionnaires, scores and terminologies were found for content processing. Literature suggests that the current state of the art focuses on the real-time aspects of pain assessment through facial expressions, demanding the design of ICS to incorporate these issues which provided better accuracy. It would contribute to clinical practice if well-designed computerized methodologies would streamline the process of patient assessment, increasing its accessibility to physicians and improving quality of care.