Processing and characterization of alpha-elastin electrospun membranes

Elastin isolated from fresh bovine ligaments was dissolved in a mixture of 1,1,1,3,3,3-Hexafluoro-2-propanol and water and electrospun into fiber membranes under different processing conditions. Fiber mats of randomly and aligned fibers were obtained with fixed and rotating ground collectors and fibrils were composed by thin ribbons whose width depends on electrospinning conditions; fibrils with 721 nm up to 2.12 m width were achieved. After cross-linking with glutaraldehyde, -elastin can uptake as much as 1700 % of PBS solution and a slight increase on fiber thickness was observed. The glass transition temperature of electrospun fiber mats was found to occur at ~ 80 ºC. Moreover, -Elastin showed to be a perfect elastomeric material, and no mechanical hysteresis was found in cycle mechanical measurements. The elastic modulus obtained for oriented and random fibers mats in a PBS solution was 330 ± 10 kPa and 732 ± 165 kPa, respectively. Finally, the electrospinning and cross-linking process does not inhibit MC-3T3-E1 cell adhesion. Cell culture results showed good cell adhesion and proliferation in the cross-linked elastin fiber mats.

A Wireless EEG Acquisition Platform based on Embedded Systems

This paper proposes a wireless EEG acquisition platform based on Open Multimedia Architecture Platform (OMAP) embedded system. A high-impedance active dry electrode was tested for improving the scalp- electrode interface. It was used the sigma-delta ADS1298 analog-to-digital converter, and developed a “kernelspace” character driver to manage the communications between the converter unit and the OMAP’s ARM core. The acquired EEG signal data is processed by a “userspace” application, which accesses the driver’s memory, saves the data to a SD-card and transmits them through a wireless TCP/IP-socket to a PC. The electrodes were tested through the alpha wave replacement phenomenon. The experimental results presented the expected alpha rhythm (8-13 Hz) reactiveness to the eyes opening task. The driver spends about 725 μs to acquire and store the data samples. The application takes about 244 μs to get the data from the driver and 1.4 ms to save it in the SD-card. A WiFi throughput of 12.8Mbps was measured which results in a transmission time of 5 ms for 512 kb of data. The embedded system consumes about 200 mAh when wireless off and 400 mAh when it is on. The system exhibits a reliable performance to record EEG signals and transmit them wirelessly. Besides the microcontroller-based architectures, the proposed platform demonstrates that powerful ARM processors running embedded operating systems can be programmed with real-time constrains at the kernel level in order to control hardware, while maintaining their parallel processing abilities in high level software applications.