Input and output for surgical simulation: devices to measure tissue properties in vivo and a haptic interface for laparoscopy simulators.
Notice bibliographique
Résumé
Current efforts in surgical simulation very often focus on creating realistic graphical feedback, but neglect some or all tactile and force (haptic) feedback that a surgeon would normally receive. Simulations that do include haptic feedback do not typically use real tissue compliance properties, favoring estimates and user feedback to determine realism. When tissue compliance data are used, there are virtually no in vivo property measurements to draw upon. Together with the Center for Innovative Minimally Invasive Therapy at the Massachusetts General Hospital, the Haptics Group is developing tools to introduce more comprehensive haptic feedback in laparoscopy simulators and to provide biological tissue material property data for our software simulation. The platform for providing haptic feedback is a PHANToM Haptic Interface, produced by SensAble Technologies, Inc. Our devices supplement the PHANToM to provide for grasping and optionally, for the roll axis of the tool. Together with feedback from the PHANToM, which provides the pitch, yaw and thrust axes of a typical laparoscopy tool, we can recreate all of the haptic sensations experienced during laparoscopy. The devices integrate real laparoscopy toolhandles and a compliant torso model to complete the set of visual and tactile sensations. Biological tissues are known to exhibit non-linear mechanical properties, and change their properties dramatically when removed from a living organism. To measure the properties in vivo, two devices are being developed. The first is a small displacement, 1-D indenter. It will measure the linear tissue compliance (stiffness and damping) over a wide range of frequencies. These data will be used as inputs to a finite element or other model. The second device will be able to deflect tissues in 3-D over a larger range, so that the non-linearities due to changes in the tissue geometry will be measured. This will allow us to validate the performance of the model on large tissue deformations. Both devices are designed to pass through standard 12 mm laparoscopy trocars, and will be suitable for use during open or minimally invasive procedures. We plan to acquire data from pigs used by surgeons for training purposes, but conceivably, the tools could be refined for use on humans undergoing surgery. Our work will provide the necessary data input for surgical simulations to accurately model the force interactions that a surgeon would have with tissue, and will provide the force output to create a truly realistic simulation of minimally invasive surgery.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».