TRAIN-KNEE: Developing a Haptic Manikin for Knee Injury Assessment Training

We present the design and implementation of a high-fidelity haptic manikin for knee injury assessment training. Currently, such training is conducted through direct instruction on live patients or peer-to-peer practice, which may limit exposure to multiple injury severities and raise ethical concerns. Our manikin aims to assist inexperienced practitioners in mastering an injury assessment technique specifically for the medial collateral ligament (MCL). We designed the manikin collaboratively with a certified clinician. Our design incorporates a commercial human knee joint model for accurate anatomical representation, materials that closely mimic human skin properties, an injury simulation mechanism for replicating MCL injuries, and pressure sensors to capture user-applied pressure during manipulation. We conducted three evaluations: an internal test with our collaborating clinician to configure our manikin for four MCL injury conditions (i.e., healthy, grade 1, grade 2, and grade 3) using a psychophysics method; a subsequent study where 6 certified clinicians rated each condition for consistency; and a technical evaluation measuring abduction range in the healthy and grade 3 configurations. Results show that our manikin can reliably display healthy and unhealthy MCLs. However, further improvements are needed to accurately distinguish between injury grades. Our manikin’s realistic weight and shape were highly praised, but there is room for improvement in simulating the skin texture. This work shows the potential of realistic simulators to enhance clinical training with standardized and repeatable practice.