tailieunhanh - báo cáo khoa học: "A radial basis classifier for the automatic detection of aspiration in children with dysphagia"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: A radial basis classifier for the automatic detection of aspiration in children with dysphagia | Journal of NeuroEngineering and Rehabilitation BioMed Central Research A radial basis classifier for the automatic detection of aspiration in children with dysphagia Joon Lee1 3 Stefanie Blain1 2 Mike Casas1 4 Dave Kenny1 4 Glenn Berall1 5 and Tom Chau 1 2 Open Access Address 1Bloorview Kids Rehab Toronto Ontario Canada institute of Biomaterials and Biomedical Engineering University of Toronto Toronto Ontario Canada 3The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto Toronto Ontario Canada 4The Hospital for Sick Children Toronto Ontario Canada and 5North York General Hospital Toronto Ontario Canada Email Joon Lee - Stefanie Blain - Mike Casas - Dave Kenny - Glenn Berall - gberall@ Tom Chau - Corresponding author Published 17 July 2006 Received 20 February 2006 Journal of NeuroEngineering and Rehabilitation 2006 3 14 doi 1743-0003-3-14 Accepted I7 July 2006 This article is available from http content 3 1 14 2006 Lee et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Silent aspiration or the inhalation of foodstuffs without overt physiological signs presents a serious health issue for children with dysphagia. To date there are no reliable means of detecting aspiration in the home or community. An assistive technology that performs in these environments could inform caregivers of adverse events and potentially reduce the morbidity and anxiety of the feeding experience for the child and caregiver respectively. This paper proposes a classifier for automatic classification of aspiration and swallow .