Wireless inertial sensors enable quantified feedback, which can be applied to evaluate the efficacy of therapy and rehabilitation. In particular eccentric training promotes a beneficial rehabilitation and strength training strategy. Virtual Proprioception for eccentric training applies real-time feedback from a wireless gyroscope platform enabled through a software application for a smartphone. Virtual Proprioception for eccentric training is applied to the eccentric phase of a biceps brachii strength training and contrasted to a biceps brachii strength training scenario without feedback. During the operation of Virtual Proprioception for eccentric training the intent is to not exceed a prescribed gyroscope signal threshold based on the real-time presentation of the gyroscope signal, in order to promote the eccentric aspect of the strength training endeavor. The experimental trial data is transmitted wireless through connectivity to the Internet as an email attachment for remote post-processing. A feature set is derived from the gyroscope signal for machine learning classification of the two scenarios of Virtual Proprioception real-time feedback for eccentric training and eccentric training without feedback. Considerable classification accuracy is achieved through the application of a multilayer perceptron neural network for distinguishing between the Virtual Proprioception real-time feedback for eccentric training and eccentric training without feedback.