Robotic surgical system for virtual reality based robotic telesurgical operations
Methods, apparatuses, and systems for performing a virtual reality based robotic telesurgical demonstration, training, and credentialing are disclosed. A user may select from a variety of procedure simulations and perform a surgical procedure in a virtual environment. A virtual reality surgical simulation allows the user to demonstrate, train, or earn credentials based upon the user's performance. The simulations may provide the user with points, rankings, rewards, or credentials, in which the user can track their performance and progression as well as practice or fine tune their skills in a safe environment.
1. A method performed by a robotic surgical system, comprising:
generating an extended-reality (XR) surgical simulation environment that includes a digital anatomical model of a patient,
wherein the XR surgical simulation environment is configured to enable a user to simulate performing a surgical procedure on the patient using the digital anatomical model;
connecting at least one XR device to the XR surgical simulation environment for the user to interact virtually with the digital anatomical model;
detecting completion of a simulated surgical procedure based on at least one action by the user;
performing a comparison of simulation data of the simulated surgical procedure to stored simulation performance data;
determining, based on the comparison, a performance score of the user performing at least a portion of the simulated surgical procedure; and
storing the performance score and data associated with the at least the portion of the simulated surgical procedure in a user profile.
2. The method of claim 1 , comprising:
displaying a list of available procedure simulations for the user to perform via the at least one XR device in the XR surgical simulation environment;
receiving a user selection of the simulated surgical procedure from the list of available procedure simulations; and
displaying the XR surgical simulation environment for performing the surgical procedure using the digital anatomical model based on the user selection.
3. The method of claim 1 , wherein determining the performance score further comprises:
identifying one or more user movements during the simulated surgical procedure;
determining an accuracy metric of the one or more user movements based on a difference to one or more correct movements; and
determining the performance score based on the accuracy metric.
4. The method of claim 1 , comprising:
mapping one or more anatomical features of a body of the patient using a machine-learning platform, wherein the machine-learning platform includes a plurality of surgery-type-specific machine learning modules to be applied to image data of the patient to provide the digital anatomical model.
5. The method of claim 1 , comprising:
receiving a request for the user to access available surgical procedure simulations;
selecting at least one simulation based on a progression level of the user that corresponds to a credential of the user; and
displaying the at least one simulation to the user.
6. The method of claim 1 , comprising:
designing the XR surgical simulation environment to match an operating room the user will perform the surgical procedure in, wherein a virtual location of at least one surgical simulation item in the XR surgical simulation environment matches a location of at least one surgical item in the operating room.
7. The method of claim 1 , comprising:
wherein the performance score is identified by at least one machine-learning algorithm, wherein the at least one machine-learning algorithm is trained based on at least one dataset associated with previously identified performance scores.
8. A system comprising:
one or more processors; and
one or more memories storing instructions that, when executed by the one or more processors, cause the system to perform a process performed by a robotic surgical system, the process comprising:
generating an extended-reality (XR) surgical simulation environment that includes a digital anatomical model of a patient,
wherein the XR surgical simulation environment is configured to enable a user to simulate performing a surgical procedure on the patient using the digital anatomical model;
connecting at least one XR device to the XR surgical simulation environment for the user to interact virtually with the digital anatomical model;
detecting completion of a simulated surgical procedure based on at least one action by the user;
performing a comparison of simulation data of the simulated surgical procedure to stored simulation performance data;
determining, based on the comparison, a performance score of the user performing at least a portion of the simulated surgical procedure; and
storing the performance score and data associated with the at least the portion of the simulated surgical procedure in a user profile.
9. The system according to claim 8 , wherein the process further comprises:
displaying a list of available procedure simulations for the user to perform via the at least one XR device in the XR surgical simulation environment;
receiving a user selection of the simulated surgical procedure from the list of available procedure simulations; and
displaying the XR surgical simulation environment for performing the surgical procedure using the digital anatomical model based on the user selection.
10. The system according to claim 8 , wherein the process further comprises:
identifying one or more user movements during the simulated surgical procedure;
determining an accuracy metric of the one or more user movements based on a difference to one or more correct movements; and
determining the performance score based on the accuracy metric.
11. The system according to claim 8 , wherein the process further comprises:
mapping one or more anatomical features of a body of the patient using a machine-learning platform, wherein the machine-learning platform includes a plurality of surgery-type-specific machine learning modules to be applied to image data of the patient to provide the digital anatomical model.
12. The system according to claim 8 , wherein the process further comprises:
receiving a request for the user to access available surgical procedure simulations;
selecting at least one simulation based on a progression level of the user that corresponds to a credential of the user; and
displaying the at least one simulation to the user.
13. The system according to claim 8 wherein the process further comprises:
designing the XR surgical simulation environment to match an operating room the user will perform the surgical procedure in, wherein a virtual location of at least one surgical simulation item in the XR surgical simulation environment matches a location of at least one surgical item in the operating room.
14. The system according to claim 8 ,
wherein the performance score is identified by at least one machine-learning algorithm, wherein the at least one machine-learning algorithm is trained based on at least one dataset associated with previously identified performance scores.
15. A non-transitory computer-readable medium storing instructions that, when executed by a computing system, cause the computing system to perform operations performed by a robotic surgical system, the operations comprising:
generating an extended-reality (XR) surgical simulation environment that includes a digital anatomical model of a patient,
wherein the XR surgical simulation environment is configured to enable a user to simulate performing a surgical procedure on the patient using the digital anatomical model;
connecting at least one XR device to the XR surgical simulation environment for the user to interact virtually with the digital anatomical model;
detecting completion of a simulated surgical procedure based on at least one action by the user;
performing a comparison of simulation data of the simulated surgical procedure to stored simulation performance data;
determining, based on the comparison, a performance score of the user performing at least a portion of the simulated surgical procedure; and
storing the performance score and data associated with the at least the portion of the simulated surgical procedure in a user profile.
16. The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
displaying a list of available procedure simulations for the user to perform via the at least one XR device in the XR surgical simulation environment;
receiving a user selection of the simulated surgical procedure from the list of available procedure simulations; and
displaying the XR surgical simulation environment for performing the surgical procedure using the digital anatomical model based on the user selection.
17. The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
identifying one or more user movements during the simulated surgical procedure;
determining an accuracy metric of the one or more user movements based on a difference to one or more correct movements; and
determining the performance score based on the accuracy metric.
18. The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
mapping one or more anatomical features of a body of the patient using a machine-learning platform, wherein the machine-learning platform includes a plurality of surgery-type-specific machine learning modules to be applied to image data of the patient to provide the digital anatomical model.
19. The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
receiving a request for the user to access available surgical procedure simulations;
selecting at least one simulation based on a progression level of the user that corresponds to a credential of the user; and
displaying the at least one simulation to the user.
20. The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
designing the XR surgical simulation environment to match an operating room the user will perform the surgical procedure in, wherein a virtual location of at least one surgical simulation item in the XR surgical simulation environment matches a location of at least one surgical item in the operating room.