BACKGROUND:In recent years, monitoring the pressure in the human body, especial y esophageal variceal pressure, becomes a hot spot. A lot of progress has been achieved regarding fiber optical sensors for measurement of the pressure in the human body.
OBJECTIVE:To briefly review the fiber optical sensor applications in the human body.
METHODS:A computer-based online retrieval was performed to search papers in CNKI periodical ful-text database and PubMed database (from January 1983 to March 2013) using the key words of“fiber optical sensor, pressure, measurement”in Chinese and English, respectively. After excluding objective-independent and repetitive papers, 40 papers were included for further analysis.
RESULTS AND CONCLUSION:Compared with traditional sensors, fiber optical sensors, which have advantages in high sensitivity, large dynamic range, fast response, tolerance to electronic interference, explosion proofing, fireproofing and corrosion protection, have been used to measure esophageal variceal pressure, intracranial pressure, pharyngeal pressure, pediatric airway pressure, cardiovascular&blood pressure, intervertebral disc pressure, intrauterin pressure in childbirth, pressure in the colon, plantar pressure and shear force as wel as other pressures in the human body. Fiber optical sensors have been used more widely in pressure monitoring. With the development of production technology and device performance, fiber optical sensors wil further promote the rapid development of medical science in the near future.

Objective : To develop an endoscopic automatic detection system in early gastric cancer (EGC) based on a region-based convolutional neural network ( Mask R-CNN) ． Methods : A total of 3 579 and 892 white light images (WLI) of EGC were obtained from the First Affiliated Hospital of Anhui Medical University for training and testing，respectively．Then，10 WLI videos were obtained prospectively to test dynamic performance of the RCNN system．In addition，400 WLI images were randomly selected for comparison with the Mask R-CNN system and endoscopists．Diagnostic ability was assessed by accuracy，sensitivity，specificity，positive predictive value ( PPV) ， and negative predictive value (NPV) . Results : The accuracy，sensitivity and specificity of the Mask R-CNN system in diagnosing EGC in WLI images were 90. 25% ，91. 06% and 89. 01% ，respectively，and there was no significant statistical difference with the results of pathological diagnosis．Among WLI real-time videos，the diagnostic accuracy was 90. 27%．The speed of test videos was up to 35 frames / s in real time．In the controlled experiment， the sensitivity of Maks R-CNN system was higher than that of the experts (93. 00% vs 80. 20% ，χ2 = 7. 059，P < 0. 001) ，and the specificity was higher than that of the juniors (82. 67% vs 71. 87% ，χ2 = 9. 955，P＜0. 001) ， and the overall accuracy rate was higher than that of the seniors (85. 25% vs 78. 00% ，χ2 = 7. 009，P＜0. 001) . Conclusion The Mask R-CNN system has excellent performance for detection of EGC under WLI，which has great potential for practical clinical application.