Aim To evaluate a kinematic paradigm of automatic general movements analysis in comparison to clinical assessment in 3‐month‐old infants and its prediction for neurodevelopmental outcome. Method Preterm infants at high risk (n=49; 26 males, 23 females) and term infants at low risk (n=18; eight males, 10 females) of developmental impairment were recruited from hospitals around Heidelberg, Germany. Kinematic analysis of general movements by magnet tracking and clinical video‐based assessment of general movements were performed at 3 months of age. Neurodevelopmental outcome was evaluated at 2 years. By comparing the general movements of small samples of children with and without cerebral palsy (CP), we developed a kinematic paradigm typical for infants at risk of developing CP. We tested the validity of this paradigm as a tool to predict CP and neurodevelopmental impairment. Results Clinical assessment correctly identified almost all infants with neurodevelopmental impairment including CP, but did not predict if the infant would be affected by CP or not. The kinematic analysis, in particular the stereotypy score of arm movements, was an excellent predictor of CP, whereas stereotyped repetitive movements of the legs predicted any neurodevelopmental impairment. Interpretation The automatic assessment of the stereotypy score by magnet tracking in 3‐month‐old spontaneously moving infants at high risk of developmental abnormalities allowed a valid detection of infants affected and unaffected by CP.

Movement variation constitutes a crucial feature of infant motor development. Reduced variation of spontaneous infant movements, i.e. stereotyped movements, may indicate severe neurological de cit at an early stage. Hitherto evaluation of movement variation has been mainly restricted to subjective assessment based on observation. is article introduces a method for quantitative assessment yielding an objective de nition of stereotyped movements which may be used for the prognosis of neurological de cits such as cerebral palsy ( ).Movements of 3-months-old infants were recorded with an electromagnetic tracking system facilitating the analysis of joint angles of the upper and lower limb. A stereotypy score based on dynamic time warping has been developed describing movements which are self-similar in multiple degrees of freedom. For clinical evaluation, this measure was calculated in a group of infants at risk for neurological disorders (n=54) and a control group of typically developing children (n=21) on the basis of spontaneous movements at the age of three months. e stereotypy score was related to outcome at the age of 24 months in terms of (n=10) or no-(n=53). Using the stereotypy score of upper limb movements cases could be identi ed with a sensitivity of 90% and a speci city of 96%. e corresponding score of the leg movements did not allow for valid discrimination of the groups. e presented stereotypy feature is a promising candidate for a marker that may be used as a simple and noninvasive quantitative measure in the prediction of . e method can be adopted for the assessment of infant movement variation in research and clinical applications.

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Using the complexity score we were able to quantify movement complexity in regard of the understanding of physicians. This could be useful for clinical applications.

In motion capture applications using electromagnetic tracking systems the process of anatomical calibration associates the technical frames of sensors attached to the skin with the human anatomy. Joint centers and axes are determined relative to these frames. A change of orientation of the sensor relative to the skin renders this calibration faulty. is sensitivity regarding sensor displacement can turn out to be a serious problem with movement recordings of several minutes duration. We propose the "dislocation distance" as a novel method to quantify sensor displacement and to detect gradual and sudden changes of sensor orientation. Furthermore a method to de ne a so called xed technical frame is proposed as a robust reference frame which can adapt to a new sensor orientation on the skin. e proposed methods are applied to quantify the effects of sensor displacement of 120 upper and lower limb movement recordings of newborns revealing the need for a method to compensate for sensor displacement. e reliability of the xed technical frame is quanti ed and it is shown that trend and dispersion of the dislocation distance can be significantly reduced. A working example illustrates the consequences of sensor displacement on derived angle time series and how they are avoided using the xed technical frame.

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