VLSI architecture for fetal ECG extraction for personalized healthcare application within resource constrained environmentT
VLSI architecture for fetal ECG extraction for personalized healthcare application within resource constrained environmentT
This paper proposes a novel VLSI architecture for Fetal ECG extraction for personalized healthcare application within a mobile homecare medical device in the resource constrained environment. Novelty of this architecture lies in the application of recently proposed memory-efficient, parameterized, multiplierless Discrete Wavelet Transform and simplified decision making logic of the complex Fuzzy membership function computation method for robust and reliable detection and removal of maternal modulus maxima peaks from the composite abdominal signal. The memory efficiency is achieved in terms of reduction in memory size and nearly linear, instead of exponential, growth of memory requirement with the increase in incoming dataframe length. The simplification of the Fuzzy membership function is achieved by exploiting the inherent time-stamp information of several levels of the Discrete Wavelet Transform analysis bank. The proposed architecture is more effective for longer frames. The generic memory model implemented, will provide the flexibility to configure the on-chip memory with any type of orthonormal wavelets suitable for different applications.
Wavelet Transform, Fetal ECG Extraction, Modulus Maxima, Fuzzy membership Function, VLSI Architecture, Low Power Design
Acharyya, Amit
f7c95a87-04ac-4d13-a74c-0c4d89b1c79c
Tudugalle, Hasitha
bea144aa-c3bb-4ec0-a513-986fc39b875d
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Gunn, Steve
306af9b3-a7fa-4381-baf9-5d6a6ec89868
30 June 2010
Acharyya, Amit
f7c95a87-04ac-4d13-a74c-0c4d89b1c79c
Tudugalle, Hasitha
bea144aa-c3bb-4ec0-a513-986fc39b875d
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Gunn, Steve
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Acharyya, Amit, Tudugalle, Hasitha, Maharatna, Koushik, Al-Hashimi, Bashir and Gunn, Steve
(2010)
VLSI architecture for fetal ECG extraction for personalized healthcare application within resource constrained environmentT.
Sixth UK Embedded Forum, University of Newcastle-upon-Tyne, United Kingdom.
30 Jun - 01 Jul 2010.
Record type:
Conference or Workshop Item
(Other)
Abstract
This paper proposes a novel VLSI architecture for Fetal ECG extraction for personalized healthcare application within a mobile homecare medical device in the resource constrained environment. Novelty of this architecture lies in the application of recently proposed memory-efficient, parameterized, multiplierless Discrete Wavelet Transform and simplified decision making logic of the complex Fuzzy membership function computation method for robust and reliable detection and removal of maternal modulus maxima peaks from the composite abdominal signal. The memory efficiency is achieved in terms of reduction in memory size and nearly linear, instead of exponential, growth of memory requirement with the increase in incoming dataframe length. The simplification of the Fuzzy membership function is achieved by exploiting the inherent time-stamp information of several levels of the Discrete Wavelet Transform analysis bank. The proposed architecture is more effective for longer frames. The generic memory model implemented, will provide the flexibility to configure the on-chip memory with any type of orthonormal wavelets suitable for different applications.
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Published date: 30 June 2010
Additional Information:
Event Dates: 30 June - 1 July, 2010
Venue - Dates:
Sixth UK Embedded Forum, University of Newcastle-upon-Tyne, United Kingdom, 2010-06-30 - 2010-07-01
Keywords:
Wavelet Transform, Fetal ECG Extraction, Modulus Maxima, Fuzzy membership Function, VLSI Architecture, Low Power Design
Organisations:
Electronic & Software Systems
Identifiers
Local EPrints ID: 271156
URI: http://eprints.soton.ac.uk/id/eprint/271156
PURE UUID: bb7cfa2f-a80e-400b-898c-7e24f3595810
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Date deposited: 25 May 2010 12:07
Last modified: 14 Mar 2024 09:24
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Contributors
Author:
Amit Acharyya
Author:
Hasitha Tudugalle
Author:
Koushik Maharatna
Author:
Bashir Al-Hashimi
Author:
Steve Gunn
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