Low Complexity Single Channel ICA Architecture Design Methodology for Pervasive Healthcare Applications

Bhardwaj, S and Adapa, B and Ranjan, Shashank and Jadhav, P and Biswas, D and Acharyya, Amit and Naik, G R (2016) Low Complexity Single Channel ICA Architecture Design Methodology for Pervasive Healthcare Applications. In: IEEE International Workshop on Signal Processing Systems (SIPS), 26-28 Oct. 2016, Dallas, TX.

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Abstract

In this paper, we propose a low-complexity architecture design methodology for the Single Channel Independent Component Analysis (SCICA) algorithm targeting pervasive personalized healthcare. SCICA, unlike the conventional ICA, separates the signal from multiple sources using only a single sensor that has tremendous potential for reducing the number of body-worn sensors. However, such applications are constrained by power consumption limitation due to the battery backup necessitating low-complexity system design and the on-chip area requirement. On the other hand, SCICA, involving computationally intensive stages including ICA, Fast Fourier Transform (FFT), Eigen Value Decomposition (EVD) and k-means clustering, is not possible to be mapped onto the low-complexity architecture directly from the algorithmic level. Hence, in this paper, adopting algorithm-architecture holistic approach, we introduce the Coordinate Rotation Digital Computer (CORDIC) based low-complexity SCICA architecture design methodology suitable for such resource constrained applications. K-means architecture used for low-complex SCICA based on the proposed methodology consumes core silicon area of 0.28mm2 and power of 0.25mW at 1.2 V, 1-MHz frequency using 0.13µm standard cell technology library (TSMC) that is about 50% less than that of the state-of-the art approaches. The functionality has been compared favorably with the conventional SCICA and hardware analysis has also cross-verified the low complexity nature of the proposed methodology.

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IITH Creators:
IITH CreatorsORCiD
Acharyya, Amithttp://orcid.org/0000-0002-5636-0676
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: SCICA; FFT; EVD; CORDIC; k-means clustering; Pervasive Healthcare
Subjects: Others > Electricity
Others > Engineering technology
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 22 Dec 2016 11:04
Last Modified: 29 Aug 2017 11:00
URI: http://raiith.iith.ac.in/id/eprint/2927
Publisher URL: https://doi.org/10.1109/SiPS.2016.15
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