Share Email Print

Proceedings Paper

Biomedical wellness monitoring system based upon molecular markers
Author(s): Whitney Ingram
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

We wish to assist caretakers with a sensor monitoring systems for tracking the physiological changes of homealone patients. One goal is seeking biomarkers and modern imaging sensors like stochastic optical reconstruction microscopy (STORM), which has achieved visible imaging at the nano-scale range. Imaging techniques like STORM can be combined with a fluorescent functional marker in a system to capture the early transformation signs from wellness to illness. By exploiting both microscopic knowledge of genetic pre-disposition and the macroscopic influence of epigenetic factors we hope to target these changes remotely. We adopt dual spectral infrared imaging for blind source separation (BSS) to detect angiogenesis changes and use laser speckle imaging for hypertension blood flow monitoring. Our design hypothesis for the monitoring system is guided by the user-friendly, veteran-preferred "4-Non" principles (noninvasive, non-contact, non-tethered, non-stop-to-measure) and by the NIH's "4Ps" initiatives (predictive, personalized, preemptive, and participatory). We augment the potential storage system with the recent know-how of video Compressive Sampling (CSp) from surveillance cameras. In CSp only major changes are saved, which reduces the manpower cost of caretakers and medical analysts. This CSp algorithm is based on smart associative memory (AM) matrix storage: change features and detailed scenes are written by the outer-product and read by the inner product without the usual Harsh index for image searching. From this approach, we attempt to design an effective household monitoring approach to save healthcare costs and maintain the quality of life of seniors.

Paper Details

Date Published: 10 May 2012
PDF: 13 pages
Proc. SPIE 8401, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X, 84010W (10 May 2012); doi: 10.1117/12.918838
Show Author Affiliations
Whitney Ingram, The Univ. of Georgia (United States)

Published in SPIE Proceedings Vol. 8401:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X
Harold Szu, Editor(s)

© SPIE. Terms of Use
Back to Top