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Abstract
Needle insertion in soft tissue has raised a lot of research interests lately. A spring-beam-damper model has been developed for needle-tissue interaction. Considering the tissue inhomogeneity, depth-varying mean parameters are proposed to calculate the spring/damper reaction forces. Based on this approach, an online parameter estimator has been designed using modified least square method with forgetting factor. In this paper, mathematical relationships are developed for efficient and robust needle tip trajectory prediction in an inhomogeneous and noisy environment. Extensive experiments have been carried out in various phantoms to validate the improved needle-tissue interaction model based on the online experimental data. Results reveal that the model can track the needle tip trajectory with satisfactory accuracy even in the presence of large disturbances and noises, but sometimes at the cost of the parameter estimation. Experiments also show that the convergent rate and estimation accuracy can be greatly improved when the needle gets supported.