SHS Web Conf.
Volume 33, 2017International Conference on Communication and Media: An International Communication Association Regional Conference (i-COME’16)
|Number of page(s)||7|
|Published online||02 February 2017|
Application of Motion Correction using 3D Autoregressive Model in Kinect-based Telemedicine
1 Smart Content Research team, ETRI, 11-41 Simin-daero 327 beon-gil, Dongan-gu, Anyang, Korea,
2 Department of Systems Management Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu University, Suwon, Korea
3 Department of Interaction Science, Sungkyunkwan University 25-2 Sungkyunkwan-ro, Jongro-gu, Sungkyunkwan University, Seoul, Korea
* Corresponding author: firstname.lastname@example.org
In telemedicine, where the convergence of different types of medical treatment occurs, it is very important to establish credibility regarding the mutual communication between patients and medical workers by acquiring and sharing more accurate data. For rehabilitation treatment in particular, where motion data are required, auxiliary equipment such as a Kinect sensor is being more widely used. This study proposes a methodology for improving the motion recognition rate by compensating the noise from a Kinect sensor using a 3D autoregressive model. Moreover, this study investigates the methods applied for vitalizing the area of telemedicine under this particular trend.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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