Model-based microforce measurement for a flexure-jointed mechanism with cell-injection application

Abstract

Manual and semi-automated micromanipulators used for cell-injection procedures require skilled operators to control the manipulator, and the process can be time-consuming and prone to error. For automating this process, it is useful to know the injection force that occurs during operation to help avoid causing damage to the cell. This thesis presents a force measurement approach for a micro-injection system that does not require using a force sensor. The design of the system is based on a 3d-printed flexure-jointed mechanism with two parallel Hoeken's linkages, powered by rotary voice coil actuators. The main difficulty for estimation of the injection force is that the mechanical properties of the mechanism, and also the actuation force, must known very accurately. Two different dynamic models were considered for force estimation using an extended state estimator (disturbance observer). The first method involves a simple single degree of freedom model. The second method involves a general fourth-order transfer function model obtained by using system identification methods. An extended state estimator was designed using optimal stochastic solutions (Kalman filters) to estimate the injection force during operation, based on the identified models. The experimental tests of cell injection were performed using shishamo fish eggs. For a typical egg cell injection procedure, the maximum force that occurred just before penetration was approximately 1000 𝜇𝑁. The real-time force estimation method was shown to be suitable for penetration detection to enhance the efficiency and reliability of the cell-injection procedure.