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In this study, we designed, fabricated and demonstrated a compact wavelength detection system based on a gradient grating period guided-mode resonance filter (GGP-GMRF) mounted on a linear charge-coupled device (CCD) camera. The GGPGMRF was first fabricated through nanoreplica molding on a plastic substrate, followed by the deposition of a thin TiO 2 film. The grating periods of the GGP-GMRF vary from 250 to 550 nm with a 2 nm increment in each period consisting of 100 cycles. The results show that a 6 mm long GGP-GMRF has a filtering range of 506 to 915 nm. Upon illumination, the GGP-GMRF reflects a particular wavelength of light resulting in the minimum transmission of that wavelength. Hence, the GGP-GMRF provides a spatially dependent minimum transmission depending on the wavelength of the incident light. The linear CCD underneath the GGP-GMRF measures the transmitted intensity, and the wavelength of the incident light can be correlated with the location of the minimum intensity. For the demonstrated GGP-GMRF and CCD system, a spectral resolution of 1 nm can be achieved.

A polymeric SU8 rib waveguide Bragg grating filterfabricated using reactive ion etching (RIE) and solvent assisted microcontact molding (SAMIM) is presented. SAMIM is one kind of soft lithography. The technique is unique in which that a composite hPDMS/PDMS stamp was used to transfer the grating pattern onto an inverted SU8 rib waveguide system. The composite grating stamp can be used repeatedly several times with degradation. Using this stamp and inverter rib waveguide structure, the Bragg grating filter fabrication can be significantly simplified.

A flexible high-resolution sensor capable of measuring the distribution of both shear and pressure at the plantar interface are needed to study the actual distribution of this force during daily activities, and the role that shear plays in causing plantar ulceration. We have previously developed a novel means of transducing plantar shear and pressure stress via a new microfabricated optical system. However, a force image algorithm is needed to handle the complexity of construction of two-dimensional planar pressure and shear images. Here we have developed a force image algorithm for a micromachined optical bend loss sensor. A neural network is introduced to help identify different load shapes. According to the experimental result, we can conclude that once the neural network has been well trained, it can correctly identify the loading shape. With the neural network, our micromachined optical bend loss Sensor is able to construction the two-dimensional planar force images.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.