ENIGMA – Enhanced interactive general movement assessment

摘要

General movement assessment is an accurate clinical method for predicting severe neurological dysfunctions such as cerebral palsy in young infants. Development of a computer-based diagnosis support system based on the General Movement Assessment method is dependent on features being effectively elicited from a General Movement expert. We present ENIGMA, a software tool for General Movement knowledge elicitation and modeling.Video and motion data were collected in 15 recordings containing both normal and abnormal general movements from the fidgety period of infant development. ENIGMA shows video in synchrony with different visualized features of recorded motion data. Movement patterns are modeled through an iterative and incremental process, where the General Movement expert is guiding the modeling process through comparing movement patterns observed in video with corresponding visual patterns observed in visualized features, and giving feedback to the knowledge engineer.Three visualized features were developed for exploring the so-called fidgety movements. The interactive work procedure introduced by ENIGMA enabled explicit motion features to be defined based on unconscious expert knowledge. Normal fidgety movements were found to be partly characterized by periodic patterns.Our results demonstrate that ENIGMA is a capable tool for General Movement expert knowledge elicitation. It facilitates the modeling process and provides a basis for detailed discussions. Clinical and technical concepts are communicated well through visual notions.