Trajectory optimisation with musculoskeletal integration features for fracture reduction orthopaedic robot

Int J Med Robot. 2022 Apr;18(2):e2372. doi: 10.1002/rcs.2372. Epub 2022 Feb 9.

Abstract

Background: Human body is an integrated system of bones and muscles. To date, there are insufficient studies on the effect of muscles on the trajectory planning of orthopaedic robot. To this end, based on a Stewart-Gough platform (6-UPU) fracture reduction orthopaedic robot, a musculoskeletal trajectory optimisation method was constructed for the interference of soft tissue during the reduction process.

Methods: Firstly, pose description of the fracture reduction orthopaedic robot was introduced, and its working space was analysed. Secondly, an improved Hill muscle theory was used to construct the musculoskeletal system, and finite element analysis (FEA) was carried out. Thirdly, particle swarm optimisation (PSO) with variable weights was imported, and fracture reduction trajectory planning was obtained by quintic polynomial in the workspace. Then mathematical model for trajectory optimisation was presented, and targets of musculoskeletal optimisation were extracted, which include muscle energy consumption, robot-assisted repositioning time and trajectory length. In this sense, musculoskeletal integration trajectory optimisation method was put forward. Finally, comparative optimisation simulation with skeleton only and bone and muscle together were tested, and safety experiment with musculoskeletal integration was conducted.

Results: A cone shape workspace was got, whose range can be defined as 635.14 mm on the X axis, 720 mm on the Y axis, and 240 mm on the Z axis, respectively. Besides, different FEA displacements revealed the effect of bone and muscle on the movement of the robot. Moreover, the optimal results with and without muscle had showed different movement time: the former consumed about 27 s, but the latter spent about 25 s. Additionally, the speed and acceleration of the drive rods can be obtained from zero to zero during the reset.

Conclusions: The results show that the optimised trajectory obtained with this method is safe and reliable. Furthermore, the presence of muscle has great influence on the trajectory of robot, which could prolong the reduction time so as to prevent the occurrence of uneven soft and hard traction rate problem. This paper could be helpful for the future trajectory planning study of fracture reduction orthopaedic robot.

Keywords: fracture reduction; musculoskeletal integration; orthopaedic robot; parallel robot; trajectory optimisation.

MeSH terms

  • Computer Simulation
  • Fracture Fixation
  • Humans
  • Muscles
  • Orthopedics*
  • Robotics*