@inproceedings{36,
  author = {Melanie Jouaiti and Negin Azizi and Kerstin Dautenhahn},
  title = {Computational Methods to Support Prototyping of an Adaptive Robot Joystick Controller for Children with Upper Limb Impairments},
  abstract = {<p>Between 2% to 5% of children are affected by Developmental Coordination Disorders in Canada and have been diagnosed with upper limb impairments, which affect their daily lives and reduces their autonomy. Motor impairments can be part of progressive disorders, so despite regular therapy, progress remains fleeting. Affected individuals therefore consistently face many barriers, including entertainment opportunities, as availability of off-the-shelf inclusive technology is very limited. Our long-term goal is to develop a play-mediator robot, which would facilitate play between children with motor impairments and their peers or family members. Here, games that the robot can play are remotely controlled by the participants, using appropriate interfaces (e.g. joysticks). In this paper, we take the first step towards that goal and develop an adaptive joystick controller that can compensate for individual deficits. We monitor movement statistics to determine if re-calibration of the controller is necessary. Moreover, we propose a computational model of data ‘distortion’, as a tool for developers to test their technology in the very early stages of prototype development, without requiring access to participants. This work is validated with data from healthy adults and children with upper limb impairments.</p>
},
  year = {2023},
  journal = {IEEE International Conference on Robotics and Automation (ICRA)},
  pages = {12001-12007},
  month = {May},
  doi = {10.1109/ICRA48891.2023.10160808},
}