Finite Element Modeling of scattered electromagnetic waves for stroke analysis.

Stroke has become one of the leading causes of mortality worldwide and about 800 in every 100,000 people suffer from stroke each year. The occurrence of stroke is ranked third among the causes of acute death and first among the causes for neurological dysfunction. Currently, Neurological examinations followed by medical imaging with CT, MRI or Angiography are used to provide better identification of the location and the type of the stroke, however they are neither fast, cost-effective nor portable. Microwave technology has emerged to complement these modalities to diagnose stroke as it is sensitive to the differences between the distinct dielectric properties of the brain tissues and blood. This paper investigates the possibility of diagnosing the type of stroke using Finite Element Analysis (FEA). The object of interest is a simulated head phantom with stroke, created with its specifying material characteristics like electrical conductivity and relative permittivity. The phantom is then placed in an electromagnetic field generated by a dipole antenna radiating at 1 GHz. The FEM forward model solver computes the scattered electromagnetic field by finding the solution for the Maxwell's wave equation in the head volume. Subsequently the inverse scattering problem is solved using the Contrast Source Inversion (CSI) method to reconstruct the dielectric profile of the head phantom.

Development of an autonomic portable single-board computer based high resolution NIRS device for microcirculation analysis.

Near Infrared Spectroscopy (NIRS) is a wellestablished non-invasive technique for measuring metabolic changes in biological tissue. In this paper we describe the design and development of an autonomic portable single board computer based high resolution NIRS device, which allows quantification of these changes. The sensor-patch consisting of 8LEDs and 2photo-detectorsprovides8 channels for each detector, offering increased depth resolution for monitoring microcirculatory activity..NIRS data is acquired with a sampling rate of about 2Hz per channel using the data acquisition board which consists of a 16 bit ADC, a LED driver and programmable gain amplifiers. The components on the data acquisition board are controlled via the Advantech's PCM-3355L SBC based on Windows XP platform. The software was created using Visual Basic 6.0 and Microsoft Visual C++ 6.0. It offers optionally a real time 'monitoring' and a static data (offline) visualization mode. The most unique feature of the system is its ability to auto-calibrate itself i.e. Adopt the intensity of the LEDs output light to different experimental conditions, e.g. local melanin content, density of the tissue, and emitter-detector distances. To validate the device various experiments have been carried out such as measurements on resting and working gastrocnemius and biceps muscle in ambulatory situations. The achieved results confirmed adequate performance and reliability of the device.