Name
Title | ||
|---|---|---|
Low Complexity Single Channel ICA Architecture Design Methodology for Pervasive Healthcare Applications |
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/SiPS.2016.15 | 2016 IEEE International Workshop on Signal Processing Systems (SiPS) |
Keywords | Field | DocType |
SCICA,FFT,EVD,CORDIC,k-means clustering,Pervasive Healthcare | Computer science,Parallel computing,Systems design,Communication channel,Real-time computing,CORDIC,Fast Fourier transform,Independent component analysis,Standard cell,Cluster analysis,Backup | Conference |
ISBN | Citations | PageRank |
978-1-5090-3362-1 | 1 | 0.38 |
References | Authors | |
15 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Swati Bhardwaj | 1 | 7 | 2.65 |
| Bhagyaraja Adapa | 2 | 1 | 1.05 |
| R. Shashank | 3 | 1 | 0.38 |
| P N Jadhav | 4 | 8 | 1.24 |
| Dwaipayan Biswas | 5 | 67 | 10.49 |
| Amit Acharyya | 6 | 139 | 31.20 |
| Ganesh R. Naik | 7 | 298 | 25.37 |