Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications
Digital filters are employed in hand-held robotic instruments to separate the concomitant involuntary physiological tremor motion from the desired motion of micro-surgeons. Inherent phase-lag in digital filters induces phase distortion (time-lag/delay) into the separated tremor motion and it adverse...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
2018
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| Online Access: | https://hdl.handle.net/10356/88364 http://hdl.handle.net/10220/45765 |
| _version_ | 1826120765235265536 |
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| author | Wang, Yubo Tatinati, Sivanagaraja Adhikari, Kabita Huang, Liyu Nazarpour, Kianoush Ang, Wei Tech Veluvolu, Kalyana C. |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Wang, Yubo Tatinati, Sivanagaraja Adhikari, Kabita Huang, Liyu Nazarpour, Kianoush Ang, Wei Tech Veluvolu, Kalyana C. |
| author_sort | Wang, Yubo |
| collection | NTU |
| description | Digital filters are employed in hand-held robotic instruments to separate the concomitant involuntary physiological tremor motion from the desired motion of micro-surgeons. Inherent phase-lag in digital filters induces phase distortion (time-lag/delay) into the separated tremor motion and it adversely affects the final tremor compensation. Owing to the necessity of digital filters in hand-held instruments, multi-step prediction of physiological tremor motion is proposed as a solution to counter the induced delay. In this paper, a quaternion variant for extreme learning machines (QELMs) is developed for multi-step prediction of the tremor motion. The learning paradigm of the QELM integrates the identified underlying relationship from 3-D tremor motion in the Hermitian space with the fast learning merits of ELMs theories to predict the tremor motion for a known horizon. Real tremor data acquired from micro-surgeons and novice subjects are employed to validate the QELM for various prediction horizons in-line with the delay induced by the order of digital filters. Prediction inferences underpin that the QELM method elegantly learns the cross-dimensional coupling of the tremor motion with random quaternion neurons and hence obtained significant improvement in prediction performance at all prediction horizons compared with existing methods. |
| first_indexed | 2024-10-01T05:21:47Z |
| format | Journal Article |
| id | ntu-10356/88364 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:21:47Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/883642020-03-07T14:02:35Z Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications Wang, Yubo Tatinati, Sivanagaraja Adhikari, Kabita Huang, Liyu Nazarpour, Kianoush Ang, Wei Tech Veluvolu, Kalyana C. School of Electrical and Electronic Engineering School of Mechanical and Aerospace Engineering Surgical Robotics Physiological Tremor DRNTU::Engineering::Electrical and electronic engineering Digital filters are employed in hand-held robotic instruments to separate the concomitant involuntary physiological tremor motion from the desired motion of micro-surgeons. Inherent phase-lag in digital filters induces phase distortion (time-lag/delay) into the separated tremor motion and it adversely affects the final tremor compensation. Owing to the necessity of digital filters in hand-held instruments, multi-step prediction of physiological tremor motion is proposed as a solution to counter the induced delay. In this paper, a quaternion variant for extreme learning machines (QELMs) is developed for multi-step prediction of the tremor motion. The learning paradigm of the QELM integrates the identified underlying relationship from 3-D tremor motion in the Hermitian space with the fast learning merits of ELMs theories to predict the tremor motion for a known horizon. Real tremor data acquired from micro-surgeons and novice subjects are employed to validate the QELM for various prediction horizons in-line with the delay induced by the order of digital filters. Prediction inferences underpin that the QELM method elegantly learns the cross-dimensional coupling of the tremor motion with random quaternion neurons and hence obtained significant improvement in prediction performance at all prediction horizons compared with existing methods. Published version 2018-08-30T07:09:49Z 2019-12-06T17:01:37Z 2018-08-30T07:09:49Z 2019-12-06T17:01:37Z 2018 Journal Article Wang, Y., Tatinati, S., Adhikari, K., Huang, L., Nazarpour, K., Ang, W. T., & Veluvolu, K. C. (2018). Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications. IEEE Access, 6, 42216-42226. doi:10.1109/ACCESS.2018.2852323 https://hdl.handle.net/10356/88364 http://hdl.handle.net/10220/45765 10.1109/ACCESS.2018.2852323 en IEEE Access © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 11 p. application/pdf |
| spellingShingle | Surgical Robotics Physiological Tremor DRNTU::Engineering::Electrical and electronic engineering Wang, Yubo Tatinati, Sivanagaraja Adhikari, Kabita Huang, Liyu Nazarpour, Kianoush Ang, Wei Tech Veluvolu, Kalyana C. Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications |
| title | Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications |
| title_full | Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications |
| title_fullStr | Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications |
| title_full_unstemmed | Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications |
| title_short | Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotics applications |
| title_sort | multi step prediction of physiological tremor with random quaternion neurons for surgical robotics applications |
| topic | Surgical Robotics Physiological Tremor DRNTU::Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/88364 http://hdl.handle.net/10220/45765 |
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