Journal of Forensic Biomechanics

Abstrait

Hybrid Bayesian Network Modeling of Slips and Falls for Forensic Analysis in Civil Litigation

Richard E. Hughes

Experts in biomechanics and human factors are often asked to opine about the cause of a slip and fall event that resulted in an injury. The question posed to the expert is fundamentally different than the question answered by the traditional engineering analysis methods. Instead of trying to predict the probability of slip given available coefficient of friction (aCOF) and required coefficient of friction (rCOF), the expert knows a slip occurred and is trying to make inferences about the causes of aCOR and rCOF. It is apparent that what links the traditional engineering approach and needs of the litigation expert is Bayes’ theorem. A hypothetical case study was used to illustrate how a hybrid Bayesian network could be developed to compute a probabilistic statement about two competing theories of injury causation, one put forward by the plaintiff and one by the defense. The resulting probability aligns well with the requirement that the expert deliver an opinion based on the civil litigation standard of “more probable than not.”