Mobile solutions for patient cardiac monitoring are viewed with growing interest, and improvements on current implementations\r\nare frequently reported, with wireless, and in particular, wearable devices promising to achieve ubiquity. However, due to\r\nunavoidable power consumption limitations, the amount of data acquired, processed, and transmitted needs to be diminished,\r\nwhich is counterproductive, regarding the quality of the information produced. Compressed sensing implementation in wireless\r\nsensor networks (WSNs) promises to bring gains not only in power savings to the devices, but also with minor impact in signal\r\nquality. Several cardiac signals have a sparse representation in some wavelet transformations. The compressed sensing paradigm\r\nstates that signals can be recovered from a few projections into another basis, incoherent with the first. This paper evaluates\r\nthe compressed sensing paradigm impact in a cardiac monitoring WSN, discussing the implications in data reliability, energy\r\nmanagement, and the improvements accomplished by in-network processing.
Loading....