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Assessing human-human therapy kinematics for retargeting to human-robot therapy

2015

Conference Paper

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In this paper, we present experiments examining the accuracy of data collected from a Kinect sensor for capturing close interactive actions of a therapist with a patient during stroke rehabilitation. Our long-term goal is to map human-human interactions such as these patient-therapist ones onto human-robot interactions. In many robot interaction scenarios, the robot does not mimic interaction between two or more humans, which is a major part of stroke therapy. The Kinect works for functional tasks such as a reaching task where the interaction to be retargeted by the robot is minimal to none; though this data is not good for a functional task involving touching another person. We demonstrate that the noisy data from Kinect does not produce a system robust enough to be for remapping to a humanoid robot a therapit's movements when in contact with a person.

Author(s): Michelle J Johnson and Seethu M Christopher and Mayumi Mohan and Rochelle Mendonca
Book Title: Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR)
Year: 2015
Month: August

Department(s): Haptic Intelligence
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

DOI: 10.1109/ICORR.2015.7281312

Address: Singapore

BibTex

@inproceedings{Johnson15-ICORR-Therapy,
  title = {Assessing human-human therapy kinematics for retargeting to human-robot therapy},
  author = {Johnson, Michelle J and Christopher, Seethu M and Mohan, Mayumi and Mendonca, Rochelle},
  booktitle = {Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR)},
  address = {Singapore},
  month = aug,
  year = {2015},
  month_numeric = {8}
}