Surface Electromyography Signal for Control of Myoelectric Prosthesis of the Upper-Limb Using Independent Component Analysis

2014 ◽  
Vol 2 (1) ◽  
pp. 94-98 ◽  
Author(s):  
Jose B. Lazaro Jr. ◽  
Donabel D. Abuan ◽  
Noel B. Linsangan ◽  
Ayra G. Panganiban
Keyword(s):  
Independent Component Analysis ◽  
Upper Limb ◽  
Surface Electromyography ◽  
Component Analysis ◽  
Independent Component ◽  
Myoelectric Prosthesis

Independent component analysis in multi-channel forearm surface electromyography processing on armband approach for hand gesture classification

2020 ◽  
Vol 36 (4) ◽  
pp. 439-448
Author(s):  
José Jair Alves Mendes Junior ◽  
Daniel Prado Campos ◽  
Thiago Simões Dias ◽  
Hugo Valadares Siqueira ◽  
Sergio Luiz Stevan Jr ◽  
...  
Keyword(s):  
Independent Component Analysis ◽  
Surface Electromyography ◽  
Component Analysis ◽  
Independent Component ◽  
Hand Gesture ◽  
Gesture Classification

Skin Chromophore Estimation from Mobile Selfie Images using Constrained Independent Component Analysis

2020 ◽  
Vol 2020 (14) ◽  
pp. 357-1-357-6
Author(s):  
Luisa F. Polanía ◽  
Raja Bala ◽  
Ankur Purwar ◽  
Paul Matts ◽  
Martin Maltz
Keyword(s):  
Independent Component Analysis ◽  
Spectral Reflectance ◽  
Source Separation ◽  
Principal Component ◽  
Component Analysis ◽  
Previous Method ◽  
Independent Component ◽  
Light Transport ◽  
Camera Model ◽  
Constrained Independent Component Analysis

Human skin is made up of two primary chromophores: melanin, the pigment in the epidermis giving skin its color; and hemoglobin, the pigment in the red blood cells of the vascular network within the dermis. The relative concentrations of these chromophores provide a vital indicator for skin health and appearance. We present a technique to automatically estimate chromophore maps from RGB images of human faces captured with mobile devices such as smartphones. The ultimate goal is to provide a diagnostic aid for individuals to monitor and improve the quality of their facial skin. A previous method approaches the problem as one of blind source separation, and applies Independent Component Analysis (ICA) in camera RGB space to estimate the chromophores. We extend this technique in two important ways. First we observe that models for light transport in skin call for source separation to be performed in log spectral reflectance coordinates rather than in RGB. Thus we transform camera RGB to a spectral reflectance space prior to applying ICA. This process involves the use of a linear camera model and Principal Component Analysis to represent skin spectral reflectance as a lowdimensional manifold. The camera model requires knowledge of the incident illuminant, which we obtain via a novel technique that uses the human lip as a calibration object. Second, we address an inherent limitation with ICA that the ordering of the separated signals is random and ambiguous. We incorporate a domain-specific prior model for human chromophore spectra as a constraint in solving ICA. Results on a dataset of mobile camera images show high quality and unambiguous recovery of chromophores.

Exploring Independent Component Analysis for GPR Signal Processing

PIERS Online ◽  
2005 ◽  
Vol 1 (6) ◽  
pp. 750-753 ◽  
Author(s):  
Anxing Zhao ◽  
Yansheng Jiang ◽  
Wenbing Wang
Keyword(s):  
Signal Processing ◽  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component
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