There has been ongoing progress in the new technique and equipment in vitreoretinal surgery in recent years, contributing to the improvement of treatment of various vitreoretinal diseases. The application of 3D heads-up display viewing system (3D viewing system) has been one of the most fascinating breakthroughs in vitreoretinal surgery. Unlike the traditional method in which the surgeons have to look through the microscope eyepieces, this system allows them to turn their heads up and operate with their eyes on a high-definition 3D monitor. It provides the surgeons with superior visualization and stereoscopic sensation. And increasing studies have revealed it to be as safe and effective as the traditional microscopic system. Furthermore, the surgeons can keep a heads-up position in a more comfortable posture and lesson the pressure on cervical spine. Meanwhile, 3D viewing system makes it easier for the teaching and learning process among surgeons and assistants. However, there are still potential disadvantages including the latency between surgeon maneuver and visualization on the display, learning curves and cost. We hope that the 3D viewing system will be widely used and become a useful new tool for various vitreoretinal diseases in the near future with rapid development in the technology and constant upgrade of the system.
In order to solve the saturation distortion phenomenon of R component in fingertip video image, this paper proposes an iterative threshold segmentation algorithm, which adaptively generates the region to be detected for the R component, and extracts the human pulse signal by calculating the gray mean value of the region to be detected. The original pulse signal has baseline drift and high frequency noise. Combining with the characteristics of pulse signal, a zero phase digital filter is designed to filter out noise interference. Fingertip video images are collected on different smartphones, and the region to be detected is extracted by the algorithm proposed in this paper. Considering that the fingertip’s pressure will be different during each measurement, this paper makes a comparative analysis of pulse signals extracted under different pressures. In order to verify the accuracy of the algorithm proposed in this paper in heart rate detection, a comparative experiment of heart rate detection was conducted. The results show that the algorithm proposed in this paper can accurately extract human heart rate information and has certain portability, which provides certain theoretical help for further development of physiological monitoring application on smartphone platform.