A Non-Invasive Hemoglobin Detection Device Based on Multispectral Photoplethysmography

光容积图 计算机科学 皮尔逊积矩相关系数 相关系数 人工智能 公制(单位) 生物医学工程 模式识别(心理学) 医学 计算机视觉 数学 统计 工程类 机器学习 运营管理 滤波器(信号处理)
作者
Jianming Zhu,Ruiyang Sun,Huiling Liu,Tianjiao Wang,Lijuan Cai,Zhencheng Chen,Baoli Heng
出处
期刊:Biosensors [Multidisciplinary Digital Publishing Institute]
卷期号:14 (1): 22-22 被引量:19
标识
DOI:10.3390/bios14010022
摘要

The measurement of hemoglobin is a vital index for diagnosing and monitoring diseases in clinical practice. At present, solutions need to be found for the soreness, high risk of infection, and inconvenient operation associated with invasive detection methods. This paper proposes a method for non-invasively detecting hemoglobin levels based on multi-wavelength photoplethysmography (PPG) signals. AFE4490 and TMUX1109 were used to implement the low-cost collection of an eight-LED transmissive PPG signal. We used seven regular LEDs and one broadband LED (Osram SFH4737) as light sources. Additionally, a finger clip integrating multiple sensors was designed and manufactured via 3D printing to simultaneously monitor the LED-sensor distance and the pressure from the tester's finger during PPG signal acquisition. We used a method to extract features from PPG signals using a sliding-window's variance and an evaluation metric for PPG signals based on the AdaCost classification. Data were gathered from 56 participants from the Nephrology department, including 16 anemic patients. Pearson correlation analysis was conducted on the collected data to remove any data with a weak correlation. The advantage of using a broadband LED as a light source was also demonstrated. Several non-invasive hemoglobin regression models were created by applying AdaBoost, BPNN, and Random Forest models. The study's results indicate that the AdaBoost model produced the best performance, with a mean absolute error (MAE) of 2.67 g/L and a correlation coefficient (R2) of 0.91 The study results show that the device we designed and manufactured can achieve effective non-invasive hemoglobin detection and represents a new methodological approach to obtaining measurements that can be applied in a clinical setting.
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