Detecting fraudulent whiplash claims by support vector machines

Abstract A new method is proposed for detecting fraudulent whiplash claims based on measurements of movement control of the neck. The method is noninvasive and inexpensive. The subjects track a slowly moving object on a computer screen with their head. The deviation between the measured and actual trajectory is quantified and used as input to an ensemble of support vector machine classifiers. The ensemble was trained on a group of 34 subjects with chronic whiplash disorder together with a group of 31 healthy subjects instructed to feign whiplash injury. The sensitivity of the proposed method was 86%, the specificity 84% and the area under curve (AUC) was 0.86. This suggests that the method can be of practical use for evaluating the validity of whiplash claims.

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