文献类型： 会议论文

第一作者： Silvia Orlandi

作者： Silvia Orlandi ¹ ; Fanny Hotze ² ; Derrick Lim ² ; Sofia Gonzalez Estrada ² ; Destinee Muir ² ; Hilary A. Friesen ² ; Tom Chau ³ ;

作者机构： 1.Bloorview Research Institute (BRI), Holland Bloorview Kids Rehabilitation Hospital (HBKRH)

2.BRI, HBKRH

3.BRI, HBKRH, and the Institute of Biomaterials and Biomedical Engineering, University of Toronto

会议名称： Annual International Conference of the IEEE Engineering in Medicine and Biology Society

主办单位：

页码： 1783-1786

摘要： Children with cerebral palsy and complex communication needs face limitations in their access technology (AT) usage. Speech recognition software and conventional ATs (e.g., mechanical switches) can be insufficient for those with speech impairment and limited control of voluntary motion. Automatic recognition of head movements represents a promising pathway. Previous studies have shown the robustness of head pose estimation algorithms on adult participants, but further research is needed to use these methods with children. An algorithm for head movement recognition was implemented and evaluated on videos recorded in a naturalistic environment when children were playing a videogame. A face-tracking algorithm was used to detect the main facial landmarks. Head poses were then estimated using the Pose from Orthography and Scaling with Iterations (POSIT) algorithm and three head movements were classified through Hidden Markov Models (HMMs). Preliminary classification results obtained from the analysis of videos of five typically developing children showed an accuracy of up to 95.6% in predicting head movements.

分类号： Q81-53