Open AccessEfficient fuzzy‐controlled and hybrid entropy coding strategy lossless ECG encoder VLSI design for wireless body sensor networks
Author(s) -
Chen S.L.,
Luo G.A.,
Lin T.L.
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2013.1692
Subject(s) - lossless compression , encoder , very large scale integration , computer science , wireless , coding (social sciences) , entropy (arrow of time) , wireless sensor network , fuzzy logic , electronic engineering , algorithm , data compression , mathematics , engineering , embedded system , artificial intelligence , computer network , telecommunications , operating system , statistics , physics , quantum mechanics
An efficient VLSI design of a lossless electrocardiogram (ECG) encoder is proposed for wireless body sensor networks. To save wireless transmission power, a novel lossless encoding algorithm had been created for ECG signal compression. The proposed algorithm consists of a novel adaptive predictor based on fuzzy decision control, and a novel hybrid entropy encoder including both a two‐stage Huffman and a Golomb‐Rice coding. The VLSI architecture contains only 2.71 K gate counts and its core area is 33 929 μm 2 synthesized by a 0.18 μm CMOS process. Moreover, this design can be operated at 100 MHz processing rate by consuming only 30 μW. It achieves an average compression rate of 2.56 for the MIT‐BIH arrhythmia database. Compared with previous low‐complexity and high‐performance lossless ECG encoder studies, this design has a higher compression rate, lower power consumption and lower hardware cost than other VLSI designs.