Abstract
We describe a system that facilitates speech therapists to administer cognitive rehabilitation exercises and to evaluate treatment outcomes. We started by augmenting a commercial tool with a more user-friendly interface, meeting the needs of the healthcare professionals involved. Then we integrated, into the same tool, a new type of exercise, that is particularly patient-tailored, being based on the recognition of familiar images within a picture (such as a relative, a domestic animal, a home object, etc). Segmentation techniques are used to elaborate an input picture and individuate areas including interesting objects, that will be semi-automatically linked to text and sound. The picture and associated information are then stored in the system database and may be subsequently used as objects for the new exercise. Any number of images may be elaborated, personalised and stored for each patient. The performance has been tested on voluntary subjects with good results.
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Albanesi, M.G., Panzarasa, S., Cattani, B., Dezza, S., Maggi, M., Quaglini, S. (2007). Segmentation Techniques for Automatic Region Extraction: An Application to Aphasia Rehabilitation. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science(), vol 4594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73599-1_50
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DOI: https://doi.org/10.1007/978-3-540-73599-1_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73598-4
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