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Proximity-based haptic feedback for collaborative robotic needle insertion
Citation Link: https://doi.org/10.15480/882.4539
Publikationstyp
Conference Paper
Date Issued
2022-05
Sprache
English
TORE-DOI
First published in
Number in series
13235 LNCS
Start Page
301
End Page
309
Citation
Lecture Notes in Computer Science 13235 LNCS: 301-309 (2022)
Publisher DOI
Scopus ID
Publisher
Springer International Publishing AG
Collaborative robotic needle insertions have the potential to improve placement accuracy and safety, e.g., during epidural anesthesia. Epidural anesthesia provides effective regional pain management but can lead to serious complications, such as nerve injury or cerebrospinal fluid leakage. Robotic assistance might prevent inadvertent puncture by providing haptic feedback to the physician. Haptic feedback can be realized on the basis of force measurements at the needle. However, contact should be avoided for delicate structures. We propose a proximity-based method to provide feedback prior to contact. We measure the distance to boundary layers, visualize the proximity for the operator and further feedback it as a haptic resistance. We compare our approach to haptic feedback based on needle forces and visual feedback without haptics. Participants are asked to realize needle insertions with each of the three feedback modes. We use phantoms that mimic the structures punctured during epidural anesthesia. We show that visual feedback improves needle placement, but only proximity-based haptic feedback reduces accidental puncture. The puncture rate is 62% for force-based haptic feedback, 60% for visual feedback and 6% for proximity-based haptic feedback. Final needle placement inside the epidural space is achieved in 38%, 70% and 96% for force-based haptic, visual and proximity-based haptic feedback, respectively. Our results suggest that proximity-based haptic feedback could improve needle placement safety in the context of epidural anesthesia.
Subjects
Collaboration
Epidural anesthesia
Force feedback
Human-robot interaction
Optical coherence tomography
DDC Class
610: Medizin
Publication version
publishedVersion
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Mieling2022_Chapter_Proximity-BasedHapticFeedbackF.pdf
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