Method incorporating computer-implemented steps for providing surgical parameter data

1. A method for providing surgical parameter data, the method comprising computer-implemented steps of: a] being responsive to patient specific information data for deriving patient data, the patient specific information data being indicative of one or more dynamic characteristics; and b] determining a set of possible surgical parameter data according to the patient data and patient acquired data, the patient acquired data being indicative of one or more desired post-surgery activities, the patient acquired data comprising post-surgery activities preference data; and a further step of selecting the surgical parameter data from the set of possible surgical parameter data according to the post-surgery activities preference data.

2. A method as claimed in claim 1 , wherein the said further step of selecting the surgical parameter data from the set of possible surgical parameter data according to the post-surgery activities preference data is one of a computer-implemented step and a non-computer-implemented step.

3. A method as claimed in claim 1 , wherein the said further step of selecting the surgical parameter data from the set of possible surgical parameter data according to the post-surgery activities preference data is a non-computer-implemented step.

4. A method as claimed in claim 1 , wherein the surgical parameter data relates to alignment information data for the alignment of a joint of a patient during orthopaedic surgery.

5. A method as claimed in claim 4 , wherein the alignment information data comprises actual 3D model data of the joint.

6. A method as claimed in claim 1 , wherein the surgical parameter data relates to modelling data of the alignment of the joint.

7. A method as claimed in claim 1 , wherein the surgical parameter data relates to a selection of the joint.

8. A method as claimed in claim 1 , wherein the surgical parameter data relates to manufacturing surgical parameter data for manufacturing an orthopaedic implant.

9. A method as claimed in claim 1 , wherein the surgical parameter data relates to manufacturing parameters for manufacturing a patient specific jig.

10. A method as claimed in claim 1 , wherein the patient specific information data comprises patient acquired data indicative of one or more desired post-surgery activities.

11. A method as claimed in claim 10 , wherein the one or more dynamic characteristics comprise a virtual prediction based on one or more of: joint kinematics data; joint loading data; and joint articulation behaviour data during desired post-surgery activities.

12. A method as claimed in claim 11 , wherein the virtual prediction comprises a computer model prediction.

13. A method as claimed in claim 1 , wherein the patient specific information data is indicative of one or more static characteristics.

14. A method as claimed in claim 13 , wherein the one or more static characteristics comprises one or more load bearing axes of a biomechanical reference frame.

15. A method as claimed in claim 14 , wherein the one or more load bearing axes of the biomechanical reference frame comprises a primary load bearing axis.

16. A method as claimed in claim 13 , wherein the one or more static characteristics comprise one or more load bearing axes of at least one reference frame of the group of biomechanical reference frames comprising: an acetabular reference frame, a femoral reference frame, a tibial reference frame, and a spinal reference frame.

17. A method as claimed in claim 1 , wherein the patient specific information data comprises 2D imaging data.

18. A method as claimed in claim 17 , wherein the 2D imaging data comprises one or more of: X-Ray data and visual fluoroscopy data.

19. A method as claimed in claim 1 , wherein the patient specific information data comprises 3D imaging data.

20. A method as claimed in claim 19 , wherein the 3D imaging data comprises one or more of: Magnetic Resonance Imaging (MRI) data, Computed Tomography (CT) data, ultrasound data, radiological data, and motion capture data.

21. A method as claimed in claim 1 , wherein the patient specific information data comprises 4D imaging data.

22. A method as claimed in claim 21 , wherein the 4D imaging data comprises motion capture data.

23. A method as claimed in claim 1 , wherein the patient specific information data comprises 2D and 3D imaging data.

24. A method as claimed in claim 1 , wherein the patient specific information data comprises data indicative of one or more physical and/or psychological characteristics of the patient.

25. A method as claimed in claim 24 , wherein the one or more physical characteristics comprises one or more of: age data, gender data, height data, weight data, activity level data, BMI data, body condition data, and body shape data.

26. A method as claimed in claim 24 , wherein the physical and/or psychological data at least includes modification and/or removal of a or said physical characteristic during surgery.

27. A method as claimed in claim 1 , wherein the post-surgery activities preference data is a preference ratio being indicative of comparative patient preference for the one or more desired post-surgery activities.

28. A method as claimed in claim 1 , the method further comprising the step of: accessing a database of library surgical parameter data, wherein the surgical parameter data is further selected according to the library parameter information data.

29. A method as claimed in claim 28 , wherein the library surgical parameter data comprises data relating to a group of available orthopaedic procedures and/or implants for performing at least one of the one or more desired post-surgery activities.

30. A method as claimed in claim 28 , wherein the library surgical parameter data comprises data relating to a group of patients having undertaken surgery for performing at least one of the one or more desired post-surgery activities.

31. A method of controlling an alignment system to align a joint of a patient during orthopaedic surgery according to alignment information data generated by the method as claimed in claim 1 .

32. A method as claimed in claim 31 , wherein the alignment system is selected from a group of alignment systems comprising: a robotic alignment system, a haptic feedback alignment system; and a computer-assisted alignment system.

33. A method for calculating surgery data for a group of surgeries, the method comprising the steps of: receiving patient library data; receiving surgery range data; and calculating the surgery data for the group of surgeries according to the patient library data and the surgery data, wherein the patient library data comprises surgery parameter data of multiple surgeries of multiple patients provided by the method as claimed in claim 1 .

34. A method as claimed in claim 33 , wherein the surgery range data is indicative of one or more subsets of the patient library data selected according to a user input request.

35. A method as claimed in claim 34 , wherein at least one of the one or more subsets comprises patient satisfaction data relating to a number of satisfied patients selected from a group of having undertaken surgery in accordance with the determined surgical parameter data.

36. A method as claimed in claim 1 , further comprising a step of receiving patient library data, wherein the patient library data comprises patient satisfaction data relating to a number of satisfied patients selected from a group of patients having undertaken surgery in accordance with the determined surgical parameter data.

37. A method as claimed in claim 36 , wherein the said further step of receiving patient library data is one of a computer-implemented step and a non-computer-implemented step.