@inproceedings{087d32bfb5cb49859cdaa7f1a21da952,
title = "Online LS-SVM based multi-step prediction of physiological tremor for surgical robotics",
abstract = "Performance of robotics based hand-held surgical devices in real-time is mainly dependent on accurate filtering of physiological tremor. The presence of phase delay in sensors (hardware) and filtering (software) processes affects the cancellation accuracy. This paper focuses on developing an estimation algorithm to improve the estimation accuracy in the presence of phase delay for real-time implementations. Moving window based online training approach for least squares-support vector machines (LSSVM) is employed in this paper for tremor estimation. A study is conducted with tremor data recorded from the subjects to analyze the suitability of proposed approach for both single-step and multi-step prediction.",
author = "S. Tatinati and Y. Wang and G. Shafiq and Veluvolu, \{K. C.\}",
year = "2013",
doi = "10.1109/EMBC.2013.6610930",
language = "English",
isbn = "9781457702167",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
pages = "6043--6046",
booktitle = "2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013",
note = "2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 ; Conference date: 03-07-2013 Through 07-07-2013",
}