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作 者:赵荣荣 陈彬[1] 王玉[1] 周娜 赵莹莹[1] ZHAO Rong-rong;CHEN Bin;WANG Yu;ZHOU Na;ZHAO Ying-ying(Department of Neurology,Beijing Friendship Hospital Affiliated to the Capital Medical University,Beijing 100050,China)
机构地区:[1]首都医科大学附属北京友谊医院神经内科,北京100050
出 处:《神经损伤与功能重建》2022年第12期739-741,共3页Neural Injury and Functional Reconstruction
摘 要:目的:应用一款集成多波长光谱传感器和机器学习算法的无创装置检测血红蛋白浓度,并验证其检测准确度。方法:连续入选80例缺血性脑卒中患者,抽取静脉血获取有创血红蛋白浓度,同时使用集成3个发光二极管(LED)传感器(发光波长分别为660 nm、810 nm和1300 nm)的手指夹装置原型获取光电容积脉搏波(PPG)数据并提取相关特征。随机选择40例的特征数据集用于机器学习算法训练,其余40例的特征数据集用于算法准确度验证。结果:入选患者的血红蛋白为74~177 g/L。在验证集中,算法预测的血红蛋白浓度与参考值之差为(-3.2±12.95)g/L,RMSD为13.19 g/L;Pearson相关系数为0.69。结论:此款集成多个LED传感器和机器学习算法的无创装置,作为持续监测血红蛋白水平的方法具有一定可行性。Objective:To design a sensor prototype that emits multiple-wavelength lights and uses machine learning algorithms to measure hemoglobin noninvasively,and to assess the accuracy of its measurements.Methods:Eighty patients with ischemic stroke were enrolled consecutively.Venous blood was extracted to obtain the invasive hemoglobin concentration.Photoplethysmography(PPG)data were obtained simultaneously using a prototype finger clip device with three light-emitting diode(LED)sensors,and relevant features of the PPG signal were extracted.The emission wavelengths of the three LED sensors were 660 nm,810 nm,and 1300 nm respectively.The features data sets of 40 patients were randomly selected for use in machine learning algorithm training,and the data sets of the other 40 patients were used for algorithm accuracy verification.Results:The hemoglobin concentration of patients ranged from 74 g/L to 177 g/L.The Pearson correlation coefficient between the hemoglobin concentration predicted by the non-invasive device and the results of invasive hemoglobin was 0.69,and the root mean square error was 13.19 g/L.The mean difference was(-3.2±12.95)g/L.Conclu⁃sion:The non-invasive device combined with multiple LED sensors and machine learning algorithm is feasible as a method for continuous hemoglobin level monitoring.
分 类 号:R741[医药卫生—神经病学与精神病学] R741.04[医药卫生—临床医学]
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