1 上海大学 机电工程与自动化学院, 上海 200072
2 中国科学院 苏州生物医学工程技术研究所, 江苏 苏州 215163
3 苏州大学 电子信息学院, 江苏 苏州 215006
为实现卧床病员生命状态的无感实时监测, 设计了一种非接触式呼吸率与心率监测系统。首先, 根据心脏射血收缩过程的力学特性, 选择灵敏度高、稳定性好的压电陶瓷传感器采集心冲击力学信号。对信号进行去噪, 滤波放大等处理, 通过数字化采集得到心冲击图(Ballistocardiogram, BCG)。其次, 通过对心冲击图进行平滑滤波提取呼吸信号, 利用快速傅氏变换(FFT)获取呼吸信号频率。采用带通滤波器去除BCG信号的呼吸包络以及高频干扰, 获取BCG信号的单位时间J波波峰数, 推算出心率值。最后, 为验证系统的准确性与一致性, 与 BIOPAC采集的呼吸及心电图(Electrocardiogram, ECG)信号进行比对, 结果表明本系统呼吸误差率小于4.5%, 心率误差率小于9.7%。通过Bland-Altman分析, 表明监测系统的心率测算准确度与BIOPAC具有较好的一致性。
非接触式 心率检测 呼吸率检测 Bland-Altman分析 non-contact heart rate detection respiratory rate detection bland-altman analysis
Author Affiliations
Abstract
1 School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
2 Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200072, China
3 Mechanical and Electrical Engineering School, Shenzhen Polytechnic, Shenzhen 518055, China
Depth from focus (DFF) is a technique for estimating the depth and three-dimensional (3D) shape of an object from a multi-focus image sequence. At present, focus evaluation algorithms based on DFF technology will always cause inaccuracies in deep map recovery from image focus. There are two main reasons behind this issue. The first is that the window size of the focus evaluation operator has been fixed. Therefore, for some pixels, enough neighbor information cannot be covered in a fixed window and is easily disturbed by noise, which results in distortion of the model. For other pixels, the fixed window is too large, which increases the computational burden. The second is the level of difficulty to get the full focus pixels, even though the focus evaluation calculation in the actual calculation process has been completed. In order to overcome these problems, an adaptive window iteration algorithm is proposed to enhance image focus for accurate depth estimation. This algorithm will automatically adjust the window size based on gray differences in a window that aims to solve the fixed window problem. Besides that, it will also iterate evaluation values to enhance the focus evaluation of each pixel. Comparative analysis of the evaluation indicators and model quality has shown the effectiveness of the proposed adaptive window iteration algorithm.
100.6890 Three-dimensional image processing 100.3010 Image reconstruction techniques 100.2980 Image enhancement Chinese Optics Letters
2019, 17(6): 061001
上海大学机电工程与自动化学院, 上海 200070
为提高照明光源质量， 采用三基色的混光方法，实现了白光动态相关色温精确可调。根据色度学光色设计，建立了RGB三基色混光数学模型。选取合适光色参数的三基色光源进行3000~7500 K不同相关色温的白光混光实验分析，实验结果与理论白光色温偏差较大。分析可知，结温是影响色温偏差的主要因素。通过调节占空比来修正三基色光通量的输出，从而确定了占空比和目标相关色温的关系。实验结果表明，修正后的色温偏差在50 K以内，合成白光光源的参数与理论白光的性能指标参数吻合，实现了不同相关色温变化的白光光源，并通过调节三基色光通量实现了温度补偿。
视觉光学 动态色温 三基色混光 脉冲宽度调制 占空比
