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Exploiting Multi-Spatial Correlations of Motion Data in a Body Sensor Network
2012
IEEE Communications Letters
Human body motions usually exhibit a high degree of coherence and correlation in patterns. This allows exploiting spatial correlations of motion data being captured by a body sensor network. Since human bodies are relatively small, earlier work has shown how to compress motion data by allowing a node to overhear at most κ = 1 node's transmission and exploit the correlation with its own data for data compression. In this work, we consider multi-spatial correlations by extending κ = 1 to κ > 1
doi:10.1109/lcomm.2012.031212.120073
fatcat:gi6qzul5djgxre36y76uq2vsum