Computing grip force and torque from finger nail images using Gaussian processes

We demonstrate a simple approach with which finger force can be measured from nail coloration. By automatically extracting features from nail images of a finger-mounted CCD camera, we can directly relate these images to the force measured by a force-torque sensor. The method automatically corrects orientation and illumination differences. Using Gaussian processes, we can relate prepro-cessed images of the finger nail to measured force and torque of the finger, allowing us to predict the finger force at a level of 95%–98% accuracy at force ranges up to 10N, and torques around 90% accuracy, based on training data gathered in 90s.