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. © 2006 Springer-Verlag Berlin/Heidelberg.
CITATION STYLE
Cai, Y. (2006). Empathic computing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3864 LNAI, pp. 67–85). https://doi.org/10.1007/11825890_3
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