Entropy and Statistical Complexity in Bioelectrical Signals: A Literature Review

In biomedical engineering, Information Theory Quantifiers (ITQs) are used to analyze diseases by evaluating bioelectrical signals. This review article presents a meta-analysis to highlight the knowledge gap regarding the various perspectives and existing theories in this field. It intends to serve as an international reference, highlighting new opportunities for analysis in this field. Methodologically, it has gone through several stages: (i) the heuristic stage, which defined the characteristics of the documentary sample; (ii) the systematic classification and review of 70 texts using the Latent Dirichlet Allocation (LDA) model to identify topics; (iii) the hermeneutic analysis of seven thematic focuses; and (iv) the presentation of the final results. Among the findings are that continuous signals are analyzed discretely through sampling, probability distributions, and quantization, allowing entropy to be calculated. The complexity–entropy plane illustrates the relationship between disorder, organization, and structure in a system. It is concluded that the latter is useful to analyze bioelectrical signals in various diseases. However, its limited application in digestive disorders is evident, which highlights the need to integrate these concepts to improve their understanding and clinical diagnosis.