Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Energy Efficient Telemonitoring of Physiological Signals via Compressed
  Sensing: A Fast Algorithm and Power Consumption Evaluation   Wireless telemonitoring of physiological signals is an important topic in
eHealth. In order to reduce on-chip energy consumption and extend sensor life,
recorded signals are usually compressed before transmission. In this paper, we
adopt compressed sensing (CS) as a low-power compression framework, and propose
a fast block sparse Bayesian learning (BSBL) algorithm to reconstruct original
signals. Experiments on real-world fetal ECG signals and epilepsy EEG signals
showed that the proposed algorithm has good balance between speed and data
reconstruction fidelity when compared to state-of-the-art CS algorithms.
Further, we implemented the CS-based compression procedure and a low-power
compression procedure based on a wavelet transform in Filed Programmable Gate
Array (FPGA), showing that the CS-based compression can largely save energy and
other on-chip computing resources.

9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas