RESUMEN
Palpation (the application of touch to the surface of the body) is an essential clinical skill. Correct palpation is part of a complete physical examination and it assists a clinician in making an accurate diagnosis, while poor palpatory skills can lead to diagnostic errors. As with any clinical skill, palpation is best learned through repetitive practice with constructive feedback. Unfortunately, changes in healthcare provide fewer opportunities for hands-on learning of this essential skill. Unlike other clinical skills, palpation has no immediate feedback to the learner regarding their performance. For example, when students are learning how to insert an intravenous catheter, failure to perform the technique correctly results in no blood return in the catheter. However, students do not know if they are palpating an abnormality if they have never felt it before. This inherent difficulty makes expert feedback even more vital to learning correct palpation. Existing research tools have addressed some of these challenges through simulation techniques that do not require experts, and can provide feedback on palpation pressures and palpation patterns. We describe a novel computer-based palpation training system, leveraging existing approaches, with an emphasis on sensing accuracy, directed-feedback, portability, and user experience.