TY - GEN
T1 - An efficient rate allocation algorithm for transmission and storage of compressed biomedical signals in wireless health monitoring systems
AU - Wu, J. F.
AU - Chan, S. C.
AU - Liu, A. L.
AU - Wu, H. C.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/2/8
Y1 - 2017/2/8
N2 - Efficient utilization of available bandwidth for wireless transmission or local recording of compressed biomedical signals is an important aspect of wireless health monitoring systems (WHMS). Although many compression methods have been developed for coding different biomedical signals individually, rate allocation problem for compressed signals which may come from multiple patients with different importance has not yet been fully addressed. This paper proposes an efficient and yet simple rate allocation algorithm for the compressed signals over WHMS. The proposed rate allocation algorithm makes use of an improved rate-distortion (R-D) model previously proposed by the authors and formulates the rate allocation problem as a convex optimization problem, from which an analytical solution with reduced complexity can be derived. Experimental results show that the proposed analytical rate allocation algorithm can effectively allocate the available bandwidth or local storage to guarantee the quality of the compressed biomedical signals as well as control the output bit rate.
AB - Efficient utilization of available bandwidth for wireless transmission or local recording of compressed biomedical signals is an important aspect of wireless health monitoring systems (WHMS). Although many compression methods have been developed for coding different biomedical signals individually, rate allocation problem for compressed signals which may come from multiple patients with different importance has not yet been fully addressed. This paper proposes an efficient and yet simple rate allocation algorithm for the compressed signals over WHMS. The proposed rate allocation algorithm makes use of an improved rate-distortion (R-D) model previously proposed by the authors and formulates the rate allocation problem as a convex optimization problem, from which an analytical solution with reduced complexity can be derived. Experimental results show that the proposed analytical rate allocation algorithm can effectively allocate the available bandwidth or local storage to guarantee the quality of the compressed biomedical signals as well as control the output bit rate.
UR - http://www.scopus.com/inward/record.url?scp=85015384935&partnerID=8YFLogxK
U2 - 10.1109/TENCON.2016.7848528
DO - 10.1109/TENCON.2016.7848528
M3 - Conference contribution
AN - SCOPUS:85015384935
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
SP - 2694
EP - 2697
BT - Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
T2 - 2016 IEEE Region 10 Conference, TENCON 2016
Y2 - 22 November 2016 through 25 November 2016
ER -