Abstract
The autistic spectrum disorders (ASD) are behaviorally-defined developmental disorders of the immature brain which affect three domains of behavior: sociability and empathy; communication, language and imagination; and mental flexibility and range of interests. Main symptoms include motion disorders and stereotyped behaviors.
This paper presents an approach based on Artificial Intelligence techniques and Ambient Intelligence technologies for the detection of stereotyped motion disorders of patients with ASD. Specifically, monitoring is realized by means of tri-axis accelerometers applied to the patient’s wrists. Signals obtained by accelerometers are pre-processed to obtain features that, in turn, are passed to classifiers that classifies the current observation in order to detect stereotyped motions. Results are under validation at the Department of Child Psychiatry at Children’s Hospital Santobono-Pausilipon in Naples.
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Coronato, A., De Pietro, G. (2012). Detection of Motion Disorders of Patients with Autism Spectrum Disorders. In: Bravo, J., Hervás, R., RodrĂguez, M. (eds) Ambient Assisted Living and Home Care. IWAAL 2012. Lecture Notes in Computer Science, vol 7657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35395-6_56
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DOI: https://doi.org/10.1007/978-3-642-35395-6_56
Publisher Name: Springer, Berlin, Heidelberg
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