Name
Abstract | ||
|---|---|---|
Retinal vein cannulation is a promising treatment for retinal vein occlusion that involves the injection of an anticoagulant directly into the occluded vein to dissolve the blockage. However, excessive forces applied by the injection tool during the procedure, at either the scleral incision or injection site, can result in injury to the eye. Furthermore, the force required to puncture retinal veins (around 10 mN) is well below human sensing ability and an order of magnitude smaller than those that can be safely applied at the sclera (around 100 mN). Detection and management of tool-to-tissue forces on these different scales are some of the most challenging aspects of the cannulation procedure. This work describes the development of a sensorized cannulation tool capable of detecting both tool-to-vein puncture forces and tool-to-sclera contact forces. By combining two materials, nitinol alloy for the tool tip and stainless steel for the tool shaft, to achieve dual stiffness, the tool possesses a flexible tip to capture small vein puncture forces and a stiffer shaft to maintain straightness during use. Three segments of fiber Bragg grating sensors are calibrated to measure the transverse forces at both the tool tip and sclerotomy, as well as to determine the tool insertion depth within the eye. The results of the validation experiments show that the root mean square error of the measurements for the force at the tip, the force at the sclerotomy, and the tool position are 0.70 mN, 1.59 mN, and 0.69 mm, respectively. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/EMBC.2019.8857739 | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Field | DocType | Volume |
Biomedical engineering,Computer vision,Fiber Bragg grating,Microsurgery,Transverse plane,Stiffness,Computer science,Contact force,Artificial intelligence,Sclera,Retinal,Retinal Vein | Conference | 2019 |
ISSN | Citations | PageRank |
1557-170X | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changyan He | 1 | 8 | 5.30 |
| Emily Yang | 2 | 24 | 3.19 |
| Iulian Iordachita | 3 | 332 | 62.98 |