School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China.
Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin 541004, China.
Biosensors (Basel). 2023 Dec 30;14(1):0. doi: 10.3390/bios14010022.
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 (R) 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.
血红蛋白的测量是临床实践中诊断和监测疾病的重要指标。目前，需要找到解决方法来应对侵入性检测方法带来的疼痛、高感染风险和操作不便等问题。本文提出了一种基于多波长光电容积脉搏波（PPG）信号的非侵入式血红蛋白检测方法。使用 AFE4490 和 TMUX1109 实现了低成本的八通道 LED 透射式 PPG 信号采集。我们使用了七个常规 LED 和一个宽带 LED（欧司朗 SFH4737）作为光源。此外，我们设计并制造了一个集成多个传感器的手指夹，通过 3D 打印实现了同时监测 PPG 信号采集过程中 LED-传感器距离和测试者手指压力的功能。我们使用了一种基于滑动窗口方差的 PPG 信号特征提取方法和基于 AdaCost 分类的 PPG 信号评估指标。从肾脏病科的 56 名参与者中收集了数据，其中包括 16 名贫血患者。对收集的数据进行了 Pearson 相关性分析，以去除相关性较弱的数据。还展示了使用宽带 LED 作为光源的优势。通过应用 AdaBoost、BPNN 和随机森林模型，创建了几个非侵入式血红蛋白回归模型。研究结果表明，AdaBoost 模型表现最佳，平均绝对误差（MAE）为 2.67g/L，相关系数（R）为 0.91。研究结果表明，我们设计和制造的设备可以实现有效的非侵入式血红蛋白检测，为在临床环境中获得可应用的测量方法提供了一种新的方法。
