Chip Layout for Adaptive Line Enhancer Design using Adaptive Filtering Algorithms and Metrics Computation for Auscultation Signal Separation

S. Rajkumar, K. Sathesh, Bayisa Taye Mulatu

Journal of Beijing Institute of Technology ›› 2022, Vol. 31 ›› Issue (3) : 317 -326.

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Journal of Beijing Institute of Technology ›› 2022, Vol. 31 ›› Issue (3) : 317 -326. DOI: 10.15918/j.jbit1004-0579.2021.102

Chip Layout for Adaptive Line Enhancer Design using Adaptive Filtering Algorithms and Metrics Computation for Auscultation Signal Separation

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Abstract

Currently, the growth of micro and nano (very large scale integration-ultra large-scale integration) electronics technology has greatly impacted biomedical signal processing devices. These high-speed micro and nano technology devices are very reliable despite their capacity to operate at tremendous speed, and can be designed to consume less power in minimum response time, which is particularly useful in biomedical products. The rapid technological scaling of the metal-oxide-semiconductor (MOS) devices aids in mapping multiple applications for a specific purpose on a single chip which motivates us to design a sophisticated, small and reliable application specific integrated circuit (ASIC) chip for future real time medical signal separation and processing (digital stethoscopes and digital microelectromechanical systems (MEMS) microphone). In this paper, ASIC level implementation of the adaptive line enhancer design using adaptive filtering algorithms (least mean square (LMS) and normalized least mean square (NLMS)) integrated design is used to separate the real-time auscultation sound signals effectively. Adaptive line enhancer (ALE) design is implemented in Verilog hardware description language (HDL) language to obtain both the network and adaptive algorithm in cadence Taiwan Semiconductor Manufacturing Company (TSMC) 90 nm standard cell library environment for ASIC level implementation. Native compiled simulator (NC) sim and RC lab were used for functional verification and design constraints and the physical design is implemented in Encounter to obtain the Geometric Data Stream (GDS II). In this architecture, the area occupied is 0.08 mm, the total power consumed is 5.05 mW and the computation time of the proposed system is 0.82 μs for LMS design and the area occupied is 0.14 mm, the total power consumed is 4.54 mW and the computation time of the proposed system is 0.03 μs for NLMS design that will pave a better way in future electronic stethoscope design.

Keywords

adaptive line enhancer (ALE) / auscultation / least mean square (LMS) / normalized least mean square (NLMS) / application-specific integrated circuit (ASIC) / cadence

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S. Rajkumar, K. Sathesh, Bayisa Taye Mulatu. Chip Layout for Adaptive Line Enhancer Design using Adaptive Filtering Algorithms and Metrics Computation for Auscultation Signal Separation. Journal of Beijing Institute of Technology, 2022, 31(3): 317-326 DOI:10.15918/j.jbit1004-0579.2021.102

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