Method of hub communication, processing, storage and display

1. A method, comprising:

detecting a first modular surgical device within bounds of a surgical operating room;

detecting a second modular surgical device within the bounds of the surgical operating room;

connecting the first modular surgical device to a surgical hub;

connecting the surgical hub to a cloud-based system;

transmitting surgical data associated with a surgical procedure being performed in the surgical operating room from the first modular surgical device to the surgical hub;

transmitting the surgical data from the surgical hub to the cloud-based system; and

controlling a surgical function of the first modular surgical device with the second modular surgical device during the surgical procedure, wherein the surgical function comprises a tissue-treatment function performed by the first modular surgical device.

2. The method of claim 1 , further comprising connecting the second modular surgical device to the surgical hub.

3. The method of claim 1 , further comprising inferring progression of the surgical procedure from the surgical data.

4. A method, comprising:

detecting a medical imaging device within bounds of a surgical operating room;

connecting the medical imaging device to a surgical hub including an imaging module;

transmitting a livestream of a surgical site in the surgical operating room from the medical imaging device to the imaging module;

capturing, by the imaging module, at least one image frame from the livestream, at a frame capturing rate dependent upon a detected motion in the surgical site;

deriving information relevant to a surgical activity performed by an end effector of a modular surgical device at the surgical site from data extracted from the at least one image frame, wherein deriving information relevant to the surgical activity comprises:

retrieving a candidate image;

performing an image recognition algorithm on the at least one image frame and the candidate image to obtain an image recognition algorithm output;

comparing the image recognition algorithm output to a pre-selected range; and

accepting or rejecting the candidate image as the at least one image frame based on the comparison;

transmitting the information from the surgical hub to the medical imaging device; and

overlaying the information onto the livestream.

5. The method of claim 4 , further comprising detecting the modular surgical device within the bounds of the surgical operating room.

6. The method of claim 5 , further comprising connecting the modular surgical device to the surgical hub.

7. The method of claim 6 , further comprising assessing the surgical activity performed by the end effector of the modular surgical device at the surgical site from the data extracted from the at least one image frame.

8. The method of claim 4 , further comprising connecting the surgical hub to a cloud-based control system.

9. The method of claim 8 , further comprising transmitting the information from the surgical hub to the cloud-based control system.

10. The method of claim 4 , wherein deriving information relevant to the surgical activity comprises deriving, with a situational awareness module, information relevant to the surgical activity.

11. The method of claim 4 , further comprising proactively changing, with the surgical hub, a displayed view of the livestream throughout the surgical activity.

12. A method, comprising:

detecting a modular surgical device within bounds of a surgical operating room;

connecting the modular surgical device to a surgical hub;

transmitting a livestream of a surgical site in the surgical operating room to an imaging module of the surgical hub;

capturing, by the imaging module, at least one image frame from the livestream, at a frame capturing rate dependent upon a detected motion in the surgical site; and

inferring progression of a surgical activity performed by an end effector of the modular surgical device at the surgical site from data extracted from the at least one image frame, wherein the end effector includes a first jaw and a second jaw configured to engage tissue, and wherein the surgical activity comprises applying a tissue treatment to tissue grasped by the first jaw and the second jaw, wherein inferring progression of the surgical activity comprises:

retrieving a candidate image;

performing an image recognition algorithm on the at least one image frame and the candidate image to obtain an image recognition algorithm output;

comparing the image recognition algorithm output to a pre-selected range; and

accepting or rejecting the candidate image as the at least one image frame based on the comparison.

13. The method of claim 12 , further comprising connecting the surgical hub to a cloud-based control system.

14. The method of claim 13 , further comprising transmitting the data from the surgical hub to the cloud-based control system.

15. The method of claim 12 , wherein inferring progression of the surgical activity comprises inferring a step of the surgical activity that is being performed.

16. The method of claim 12 , further comprising inferring a type of the surgical activity that is being performed.

17. The method of claim 12 , further comprising inferring a type of tissue to which the surgical activity is being applied.

18. The method of claim 12 , wherein the tissue treatment comprises applying radio-frequency (RF) energy to the tissue with the end effector.

19. The method of claim 12 , wherein the tissue treatment comprises apply staples to the tissue with the end effector.

20. The method of claim 12 , wherein a resolution of an area of the at least one image frame that includes the end effector is scaled at a higher resolution compared to other parts of the at least one image frame.