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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | De Lorenzo, D. Koseki, Y. De Momi, E. Chinzei, K. Okamura, A.M. |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Mechanical Engineering, and the Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA (Okamura, A.M.) || Politecnico di Milano, Bioengineering Department, Neuroengineering and Medical Robotics Laboratory, Piazza Leonardo Da Vinci 32, 20133 Milano, Italy (De Lorenzo, D.) || Research Institute of Human Life Technology, Advanced Industrial Science and Technology (AIST), Tsukuba, Japan (Koseki, Y.; Chinzei, K.) || Istituto di Tecnologie Industriali ed Automazione, Consiglio Nazionale delle Ricerche, Milano, Italy (De Momi, E.) |
| Abstract | During needle insertion in soft tissue, detection of change in tissue properties is important both for diagnosis to detect pathological tissue and for prevention to avoid puncture of important structures. The presence of a membrane located deep inside the tissue results in a relatively small force variation at the needle tip that can be masked by relatively large friction force between the needle shaft and the surrounding tissue. Also, user perception of force can be limited due to the overall small force amplitude in some applications (e.g. brain surgery). A novel robotic coaxial needle insertion assistant was developed to enhance operator force perception. The coaxial needle separates the cutting force at the needle tip from shear friction on the needle shaft. The assistant is force controlled (admittance control), providing the operator with force feedback that is a scaled version of the force applied by the needle tip to the tissue. The effectiveness of the assistant in enhancing the detection of different tissue types was tested experimentally. Users were asked to blindly insert a needle into artificial tissues with membranes at various depths under two force feedback conditions: (1) shaft and tip force together, and (2) only tip force. The ratio of successful to unsuccessful membrane detection was significantly higher when only the needle tip force is displayed to the user. The system proved to be compliant with the clinical applications requirements. |
| Starting Page | 3447 |
| Ending Page | 3450 |
| File Size | 792610 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424441211 |
| ISSN | 1557170X |
| e-ISBN | 9781457715891 |
| e-ISBN | 9781424441228 |
| DOI | 10.1109/IEMBS.2011.6090932 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-08-30 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Needles Force Friction Robots Biomembranes Force feedback Surgery |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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