In this contribution, a first prototype for mobile respiratory motion detection using optical fibers embedded into textiles is presented. The developed system consists of a T-shirt with an integrated fiber sensor and a portable monitoring unit with a wireless communication link enabling the data analysis and visualization on a PC. A great effort is done worldwide to develop mobile solutions for health monitoring of vital signs for patients needing continuous medical care. Wearable, comfortable and smart textiles incorporating sensors are good approaches to solve this problem. In most of the cases, electrical sensors are integrated, showing significant limits such as for the monitoring of anaesthetized patients during Magnetic Resonance Imaging (MRI). OFSETH (Optical Fibre Embedded into technical Textile for Healthcare) uses optical sensor technologies to extend the current capabilities of medical technical textiles.
Computational ghost imaging (CGI) has received increasing attention as a single pixel imaging technique. However, the application of the CGI technique to moving objects requires further investigation because it requires a large number of patterns at high speeds. In this study, we propose and experimentally demonstrate optical correlator-based CGI as a step towards high-speed CGI. Our optical correlator plays the role of a spatial light modulator and correlates a target object to known patterns of general computational imaging. We experimentally verified that the RMS error of the reconstructed images is similar to that of the numerical calculations. If one reconstructed image is acquired using 1000 random binary patterns, the imaging frame rate of 133.7 fps will be achieved. This provides high-speed CGI applicable to moving objects and other phenomena.
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