3-D Fingertip Touch Force Prediction Using Fingernail Imaging With Automated Calibration

This paper presents an automated routine for calibrating a fingernail imaging system, with the intent of predicting fingerpad forces. The system uses a magnetic levitation haptic device to apply forces to the human fingerpad while recording images of the nail and surrounding skin. A novel force controller is implemented to interact stably with the human fingerpad. The data are used to calibrate a principal component regression model relating pixel intensity to 3-D force. Using data from this automated routine, this model simultaneously predicts 3-D force with an RMS error of 0.56 ± 0.03 N (7.7% of the full range of forces).