Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to lifelong disability, in particular Cerebral Palsy (CP). In clinical settings, Prechtlu0027s General Movement Assessment (GMA) can be used to classify infant movements using a Gestalt approach, identifying infants at high risk of developing PS. Training and maintenance of assessment skills are essential and expensive for the correct use of GMA, yet many practitioners lack these skills, preventing largerscale screening and leading to significant risks of missing opportunities for early detection and intervention for affected infants. We present an automated approach to GMA, based on bodyworn accelerometers and a novel sensor data analysis methodDiscriminative Pattern Discovery (DPD)that is designed to cope with scenarios where only coarse annotations of data are available for model training. We demonstrate the effectiveness of our approach in a study with 34 newborns (21 typically developing infants and 13 PS infants with abnormal movements). Our method is able to correctly recognise the trials with abnormal movements with at least the accuracy that is required by newly trained human annotators (75%), which is encouraging towards our ultimate goal of an automated PS screening system that can be used populationwide.

Design of a Robotic Crib Mobile to Support Studies in the Early Detection of Cerebral Palsy: A Pilot Study According to data from the Centers for Disease Control and Prevention, developmental disorders such as Autism Spectrum Disorder (ASD) and Cerebral Palsy (CP) affect nearly one in six children between the ages of 3 to 17 in the United States alone. In order to improve the quality of life for these individuals, there is increased emphasis on providing early intervention at infancy, when key developmental milestones are being achieved. This however requires accurate early detection of motor development delays in atrisk infants. Our research focuses on enabling early detection through the design of a robotic crib mobile that affects infant behavior. Stimuli integrated into the robotic mobile can be used to encourage certain motions such as kicking among infants in order to study infant motor development and identify atrisk populations. In this paper, we propose the design of such a robotic crib mobile and discuss preliminary results from deploying the mobile in the infantsxe2x80x99 home environment during a pilot study.