The purpose of our work is to develop a system that can detect and alarm the individual's sitting position of inactive period. Non-wearable sensor system based on FSR includes a H/W device for interfacing between a computer S/W that process sensing data and FSR module as a Sitting Mat. Pressure intensity of each sensing point on computer S/ W can be showned by color change and area expansion and we observe changes in the quantitative and qualitative. Our system has an edge in price competitiveness compared to the existing foreign system by reducing the number of FSR sensor array and improve the sensitivity of Load Measurements with computer S/W algorithm. In the future , it will continue to be developed smartphone apps to check real-time alerts with transmitting data over the bluetooth interface. and we will be expected to develope FSR sensors with durability and ductility by performing clinical trials with Office workers who sit for a long time.

Effective working memory (WM) training is often desired to improve WM. Recent studies have suggested that WM training is more successful when participants monitor scenes in three‐dimensional (3D) environments. Although previous neuroimaging studies have examined visuospatial WM in relation to a 3D scene or object, these studies did not investigate WM using stereoscopic 3D object stimuli. We used functional magnetic resonance imaging (fMRI) to identify brain activation during an N‐back task with 3D object stimuli, and determined the difference in activation pattern between stereoscopic versus shaded 3D objects. We found that the anterior insula, ventral striatum, and posterior orbitofrontal cortex showed greater activation during the 2‐back task with stereoscopic 3D objects than with shaded 3D objects. These regions have previously been associated with a salience network.

While medical equipment and IT technology advances, doctors make medical surgery using input images through cameras. They use an optical microscope or an endoscope equipped with cameras. These systems display expanded images on a monitor for the required surgical sites. It is important to display almost the same color as the actual view, in case of making surgery or observing it. If monitors display wrong color, doctors cannot accurately recognize the surgical site and have difficulty to make a surgery, and surgery observers cannot get accurate information of the surgical site. In this paper, we proposed the characterization method for medical cameras using with the ColorChecker that is commonly used to calibrate cameras and additional color values on actual surgical site. It makes the estimated coefficient through polynomial regression. It can show surgical scenes to users more precisely.

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