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Automatic Identification of Hard and Soft Bone Tissues by Analyzing Drilling Sounds

  • Published:2019-02 Issue:2 Volume:27 Page:404-414
  • ISSN:2329-9290
  • Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
  • language:
  • Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Zakeri VahidORCID,Hodgson Antony J.

Funder

Michael Smith Foundation for Health Research, British Columbia, Canada.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Pedicle drilling force control of a robotic surgical system via spine-soft tissue coupling model and parameters optimization;Computers in Biology and Medicine;2024-02

2. Tactile Perception-Based Depth and Angle Control During Robot-Assisted Bent Bone Grinding;IEEE Transactions on Industrial Informatics;2024-01

3. A Study of Vibration Signal Feature Extraction for Bone Drilling Layer Classification;2023 8th International Conference on Mechanical Engineering and Robotics Research (ICMERR);2023-12-08

4. Robotic Automatic Drilling for Craniotomy: Algorithms and In Vitro Animal Experiments;IEEE/ASME Transactions on Mechatronics;2023-12

5. Using acoustic feedback and analyses for removal of bone cement during revision knee replacement surgeries;International Journal of Computer Assisted Radiology and Surgery;2023-02-27
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