Empathic computing is an emergent paradigm that enables a system to understand human states and feelings and to share this intimate information. The new paradigm is made possible by the convergence of affordable sensors, embedded processors and wireless ad-hoc networks. The power law for multi-resolution channels and mobile-stationary sensor webs is introduced to resolve the information avalanche problems. As empathic computing is sensor-rich computing, particular models such as semantic differential expressions and inverse physics are discussed. A case study of a wearable sensor network for detection of a falling event is presented. It is found that the location of the wearable sensor is sensitive to the results. From the machine learning algorithm, the accuracy reaches up to 90% from 21 simulated trials. Empathic computing is not limited to healthcare. It can also be applied to solve other everyday-life problems such as management of emails and stress.