Methods and systems for real-time robotic surgical assistance in an operating room

Abstract

Methods, apparatuses, and systems for providing real-time surgical assistance to a surgical robot using an imaging module, a context computer module, and a quantum analysis module are disclosed. The imaging module receives one or more data related to a patient from an intra-operative database and performs a first step analysis based on the received data. The context computer module determines a type of resource required for analysis based on data received from a historical database and the intra-operative database. The quantum analysis module receives data from the imaging module and the context computer module. The quantum analysis module receives real-time data from operation room (OR) equipment and performs quantum analysis on the received data and real-time data. The quantum analysis module facilitates real-time surgical assistance and recommendations to the surgical robot.

I/We claim: 
     
         1 . A computer-implemented method comprising:
 identifying a particular computer based on a complexity of a surgical procedure and a computation time of the particular computer for providing the real-time surgical assistance;   determining that sensor data received during the surgical procedure indicates an adverse patient condition;   generating, using a machine learning module executed on the particular computer, instructions for a surgical robot to modify an amount of medication administered to a patient or adjust anesthesiology parameters based on the sensor data; and   executing, by the surgical robot, the instructions during the surgical procedure to stabilize the sensor data and avoid the adverse patient condition.   
     
     
         2 . The method of  claim 1 , wherein identifying the particular computer comprises:
 simulating the surgical procedure to determine the complexity; and   determining that the complexity exceeds a threshold.   
     
     
         3 . The method of  claim 1 , wherein avoiding the adverse condition comprises:
 reducing a recovery time and post-operative pain of the patient.   
     
     
         4 . The method of  claim 1 , wherein determining that the sensor data indicates the adverse patient condition comprises:
 performing at least one of a linear correlation, a parabolic correlation, or a logarithmic regression correlation.   
     
     
         5 . The method of  claim 1 , comprising generating a recommendation that the surgical procedure be delayed to avoid the adverse condition. 
     
     
         6 . The method of  claim 1 , comprising identify a surgical site based on real-time images during the surgical procedure. 
     
     
         7 . The method of  claim 1 , comprising determining a physical condition of the patient by analyzing diagnostic images of the patient taken using one or more imaging devices. 
     
     
         8 . A non-transitory computer-readable storage medium storing computer instructions, which when executed by one or more computer processors, cause the one or more computer processors to:
 identify a particular computer based on a complexity of a surgical procedure and a computation time of the particular computer for providing the real-time surgical assistance;   determine that sensor data received during the surgical procedure indicates an adverse patient condition;   generate, using a machine learning module executed on the particular computer, instructions for a surgical robot to modify an amount of medication administered to a patient or adjust anesthesiology parameters based on the sensor data; and   execute, by the surgical robot, the instructions during the surgical procedure to stabilize the sensor data and avoid the adverse patient condition.   
     
     
         9 . The storage medium of  claim 8 , wherein the computer instructions to identify the particular computer cause the one or more computer processors to:
 simulate the surgical procedure to determine the complexity; and   determine that the complexity exceeds a threshold.   
     
     
         10 . The non-transitory computer-readable storage medium of  claim 8 , wherein avoiding the adverse condition comprises:
 reducing a recovery time and post-operative pain of the patient.   
     
     
         11 . The non-transitory computer-readable storage medium of  claim 8 , wherein determining that the sensor data indicates the adverse patient condition comprises:
 performing at least one of a linear correlation, a parabolic correlation, or a logarithmic regression correlation.   
     
     
         12 . The non-transitory computer-readable storage medium of  claim 8 , wherein the computer instructions cause the one or more computer processors to generate a recommendation that the surgical procedure be delayed to avoid the adverse condition. 
     
     
         13 . The non-transitory computer-readable storage medium of  claim 8 , wherein the computer instructions cause the one or more computer processors to identify a surgical site based on real-time images during the surgical procedure. 
     
     
         14 . The non-transitory computer-readable storage medium of  claim 8 , wherein the computer instructions cause the one or more computer processors to determine a physical condition of the patient by analyzing diagnostic images of the patient taken using one or more imaging devices. 
     
     
         15 . A surgical system comprising:
 one or more computer processors; and   a non-transitory computer-readable storage medium storing computer instructions, which when executed by the one or more computer processors, cause the surgical system to:
 identify a particular computer based on a complexity of a surgical procedure and a computation time of the particular computer for providing the real-time surgical assistance; 
 determine that sensor data received during the surgical procedure indicates an adverse patient condition; 
 generate, using a machine learning module executed on the particular computer, instructions for a surgical robot to modify an amount of medication administered to a patient or adjust anesthesiology parameters based on the sensor data; and 
 execute, by the surgical robot, the instructions during the surgical procedure to stabilize the sensor data and avoid the adverse patient condition. 
   
     
     
         16 . The surgical system of  claim 15 , wherein the computer instructions to identify the particular computer cause the surgical system to:
 simulate the surgical procedure to determine the complexity; and   determine that the complexity exceeds a threshold.   
     
     
         17 . The surgical system of  claim 15 , wherein avoiding the adverse condition comprises:
 reducing a recovery time and post-operative pain of the patient.   
     
     
         18 . The surgical system of  claim 15 , wherein determining that the sensor data indicates the adverse patient condition comprises:
 performing at least one of a linear correlation, a parabolic correlation, or a logarithmic regression correlation.   
     
     
         19 . The surgical system of  claim 15 , wherein the computer instructions cause the surgical system to generate a recommendation that the surgical procedure be delayed to avoid the adverse condition. 
     
     
         20 . The surgical system of  claim 15 , wherein the computer instructions cause the surgical system to identify a surgical site based on real-time images during the surgical procedure.