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学者姓名：樊明辉
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Abstract ：
Prehypertension is difficult to diagnose early because of its hidden nature. Long-term monitoring of blood pressure (BP) can help in the early detection and timely treatment of this condition. This study proposes an innovative and efficient BP detection platform that combines portable electrocardiography (ECG) and photoplethysmogram (PPG) signals simultaneous acquisition equipment and BP detection algorithm to obtain real-time BP values conveniently and accurately for a long time. In this study, nine kinds of feature parameters and classification algorithm are used to build multiple linear regression (MLR) models. It not only adopts the multiparameter intelligent monitoring in intensive care units (MIMIC-II) database to train and validate the model but also uses self-developed equipment for acquisition and verification in long-term health monitoring. According to the experimental results, the mean absolute error (MAE) and standard deviation (SD) of systolic BP (SBP) have estimated values of 4.46 and 3.20 mmHg, respectively, and simultaneously, the MAE and SD of diastolic BP (DBP) are 4.20 and 3.28 mmHg, respectively. Moreover, both SBP and DBP experimental results conform to the Advancement of Medical Instrumentation (AAMI) BP standard. The proposed BP acquisition platform is proven to be capable of easily acquiring ECG and PPG signals with the proposed sensor device, and the MLR algorithm can also effectively and accurately monitor BP values for a long time.
Keyword ：
Biomedical monitoring Biomedical monitoring Electrocardiography Electrocardiography Electrocardiography (ECG) Electrocardiography (ECG) Feature extraction Feature extraction Monitoring Monitoring multiple linear regression (MLR) multiple linear regression (MLR) noninvasive continuous blood pressure (BP) measurement noninvasive continuous blood pressure (BP) measurement photoplethysmogram (PPG) photoplethysmogram (PPG) Physiology Physiology Predictive models Predictive models pulse wave arrival time (PAT) pulse wave arrival time (PAT) Sensors Sensors
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| GB/T 7714 | Wang, Liang-Hung , Sun, Kun-Kun , Xie, Chao-Xin et al. Cuffless Blood Pressure Estimation Using Dual Physiological Signal and Its Morphological Features [J]. | IEEE SENSORS JOURNAL , 2023 , 23 (11) : 11956-11967 . |
| MLA | Wang, Liang-Hung et al. "Cuffless Blood Pressure Estimation Using Dual Physiological Signal and Its Morphological Features" . | IEEE SENSORS JOURNAL 23 . 11 (2023) : 11956-11967 . |
| APA | Wang, Liang-Hung , Sun, Kun-Kun , Xie, Chao-Xin , Fan, Ming-Hui , Abu, Patricia Angela R. , Huang, Pao-Cheng . Cuffless Blood Pressure Estimation Using Dual Physiological Signal and Its Morphological Features . | IEEE SENSORS JOURNAL , 2023 , 23 (11) , 11956-11967 . |
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Abstract ：
This study presents the design of a PPG and ECG synchronous acquisition system based on NRF52832. The synchronous acquisition of pulse wave signal and ECG signal is achieved by designing PPG circuit and ECG circuit, while data integration and Bluetooth transmission are realized by NRF52832. Finally, the collected data are input into the trained classification model for BP prediction, and the device achieves wearable, synchronous and real-time acquisition. The experimental results show that the signals acquired by the device can be used for noninvasive continuous BP prediction. © 2023 IEEE.
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| GB/T 7714 | Chen, H.-D. , Wang, L.-H. , Fan, M.-H. et al. Design of PPG and ECG synchronous acquisition system based on NRF52832 [未知]. |
| MLA | Chen, H.-D. et al. "Design of PPG and ECG synchronous acquisition system based on NRF52832" [未知]. |
| APA | Chen, H.-D. , Wang, L.-H. , Fan, M.-H. , Sun, K.-K. , Chen, C.-H. , Liu, C.-F. et al. Design of PPG and ECG synchronous acquisition system based on NRF52832 [未知]. |
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Abstract ：
随着生活越来越美好，人们对于人体健康情况非常重视。本文结合生物医疗领域的应用背景，设计了一款应用于人体温度监测的RFID电子标签芯片，提出一种适合于无源UHF RFID系统的基准电源电路，并且LDO的反馈网络采用的是二极管连接方式的PMOS有源电阻，相比传统的无源电阻，大大减小了面积以及功耗。张弛振荡器采用不同类型的电阻抵消温度偏差，并且通过一种电流镜阵列校准电路，采用自校准算法对时钟电路工艺角偏差进行校准，大大提高了时钟电路输出频率的精度。ASK解调电路采用反馈分压调节结构，能同时缩小调制信号的高低电平，增大了电子标签的灵活性。本文基于SMIC0.18μm CMOS Mixed Signal工艺，设计了一款应用于人体温度监测的全无源超高频标签。设计的RFID标签功耗小于10μW，时钟电路输出频率的精度为±1%。
Keyword ：
RFID RFID 人体温度 人体温度 时钟校准 时钟校准
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| GB/T 7714 | 樊明辉 , 许晴昊 , 潘拯 et al. UHF RFID标签芯片研究 [J]. | 微纳电子与智能制造 , 2023 , 5 (04) : 29-35 . |
| MLA | 樊明辉 et al. "UHF RFID标签芯片研究" . | 微纳电子与智能制造 5 . 04 (2023) : 29-35 . |
| APA | 樊明辉 , 许晴昊 , 潘拯 , 王量弘 , 赖华玲 , 江浩 . UHF RFID标签芯片研究 . | 微纳电子与智能制造 , 2023 , 5 (04) , 29-35 . |
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Abstract ：
The application of artificial intelligence to the diagnosis of ECG is of great significance. We combine machine learning algorithm with deep learning algorithm to give full play to the advantages of different algorithms by ensemble learning. Finally, we fuse the selected models so that the accuracy of identifying five kinds of arrhythmias can reach 94%. Particularly, the accuracy of class F beat which is difficult to identify has also been improved. © 2022 IEEE.
Keyword ：
Deep learning Deep learning Electrocardiograms Electrocardiograms Learning algorithms Learning algorithms
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| GB/T 7714 | Xie, Chao-Xin , Fan, Ming-Hui , Wang, Liang-Hung et al. An Integration Method for ECG Multi-Classification [C] . 2022 : 559-560 . |
| MLA | Xie, Chao-Xin et al. "An Integration Method for ECG Multi-Classification" . (2022) : 559-560 . |
| APA | Xie, Chao-Xin , Fan, Ming-Hui , Wang, Liang-Hung , Huang, Pao-Cheng . An Integration Method for ECG Multi-Classification . (2022) : 559-560 . |
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Abstract ：
心电监测是临床应用中的常规监测手段,通过观察心电活动、心电波形的变化可诊断心肌损伤、心肌缺血和电解质紊乱,其中,针对心电图QRS波群的检测具有重要的临床意义.本文利用基于窗口最值的自适应阈值法,提出了QRS波群检测算法,包括对心电图中R波形态进行检测,并利用MIT-BIH心律失常数据库验证R波定位的准确率(97.63％).在完成R波检测的基础上,采用最值法并通过斜率限定搜寻Q波和S波.在完成QRS波定位后,根据P波和T波的形态学特征对其进行检测和定位.
Keyword ：
QRS波群检测 QRS波群检测 心电信号 心电信号 心电数据库 心电数据库 算法 算法
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| GB/T 7714 | 樊明辉 , 汪敏 , 陈良基 et al. 一种心电信号QRS波群检测算法研究 [J]. | 实用心电学杂志 , 2022 , 31 (6) : 399-404 . |
| MLA | 樊明辉 et al. "一种心电信号QRS波群检测算法研究" . | 实用心电学杂志 31 . 6 (2022) : 399-404 . |
| APA | 樊明辉 , 汪敏 , 陈良基 , 王量弘 , 黄宝震 , 王新康 . 一种心电信号QRS波群检测算法研究 . | 实用心电学杂志 , 2022 , 31 (6) , 399-404 . |
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In this paper, an eight-layer wavelet decomposition based on the wavelet basis of bior2.6 is designed, and the noise interference on ECG signal is filtered out effectively. In the aspect of R-wave position detection, an improved algorithm of adaptive slope threshold and adaptive high-frequency signal integration threshold is proposed and the precision rate 99.6% has obtained in MIT-BIH database. © 2022 IEEE.
Keyword ：
Electrocardiography Electrocardiography Wavelet decomposition Wavelet decomposition
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| GB/T 7714 | Sun, Kun-Kun , Xie, Chao-Xin , Kuo, I-Chun et al. A Method for ECG R-wave Denoising and Detecting [C] . 2022 : 557-558 . |
| MLA | Sun, Kun-Kun et al. "A Method for ECG R-wave Denoising and Detecting" . (2022) : 557-558 . |
| APA | Sun, Kun-Kun , Xie, Chao-Xin , Kuo, I-Chun , Fan, Ming-Hui , Huang, Pao-Cheng , Wang, Liang-Hung . A Method for ECG R-wave Denoising and Detecting . (2022) : 557-558 . |
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随着高血压患者的日益增多,全天候血压监护的需求日渐增长,做到能够快速、及时、方便地进行血压监测成为了当下热门的研究课题.基于脉搏波速法的无创连续血压监测系统提供了一个很好的研究方向,通过便携式的可穿戴设备采集人体生理信号,借由多元线性回归建立一个生理信号的特征参数与血压的模型,可以实现实时无创连续血压监测,打造了一个无创连续血压监测的系统平台.
Keyword ：
nRF52832 nRF52832 可穿戴式设计 可穿戴式设计 多元线性回归 多元线性回归 无创连续 无创连续 血压监测 血压监测
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| GB/T 7714 | 岳铭楷 , 黄宝震 , 樊明辉 et al. 基于脉搏波速法的无创连续血压系统设计 [J]. | 单片机与嵌入式系统应用 , 2021 , 21 (9) : 78-82 . |
| MLA | 岳铭楷 et al. "基于脉搏波速法的无创连续血压系统设计" . | 单片机与嵌入式系统应用 21 . 9 (2021) : 78-82 . |
| APA | 岳铭楷 , 黄宝震 , 樊明辉 , 王量弘 . 基于脉搏波速法的无创连续血压系统设计 . | 单片机与嵌入式系统应用 , 2021 , 21 (9) , 78-82 . |
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An interpatient classification method using the second lead for the Association for the Advancement of Medical Instrumentation (AAMI) standard is introduced. This study includes three parts. In the first part, the fuzzy matching algorithm is used to locate the key waveform points of Electrocardiogram (ECG) data. In the second part, the feature engineering algorithm is used to filter the extracted data sets. In the third part, the random forest model is carried out to realize the five classifications of heart disease by the selected features. The final precision, recall, and F1-score are 91%, 89%, and 90%, respectively. © 2021 IEEE.
Keyword ：
Decision trees Decision trees Electrocardiography Electrocardiography
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| GB/T 7714 | Liu, Shuo , Wang, Liang-Hung , Huang, Pao-Cheng et al. Heart Beat Classification Method based on Random Forest Algorithm [C] . 2021 . |
| MLA | Liu, Shuo et al. "Heart Beat Classification Method based on Random Forest Algorithm" . (2021) . |
| APA | Liu, Shuo , Wang, Liang-Hung , Huang, Pao-Cheng , Fan, Ming-Hui . Heart Beat Classification Method based on Random Forest Algorithm . (2021) . |
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基于自适应向量机监测睡眠呼吸暂停综合征(SAS)时可提取出的特征参数较多,筛选这些特征参数中与SAS相关度较大的组合,可以有效降低算法的计算量,具有重要的实践意义。本文基于V2导联心电信号,首先对ECG信号进行去噪和R波提取,得到心率变异性信号(HRV)和心电呼吸导出信号,并从中提取出时域频域特征共22组,利用特征参数与SAS的相关系数对特征参数筛选后进行支持向量机(SVM)分类。对比22组特征参数与筛选后的15组特征参数分类结果,准确率降低不足0.5%,但计算复杂度大大降低,可作为对临床长时间心电图检测的扩展,减少对专业医护人员的依赖,具有良好的经济性和普及性。
Keyword ：
支持向量机 支持向量机 相关系数 相关系数 睡眠呼吸暂停综合征 睡眠呼吸暂停综合征
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| GB/T 7714 | 王新康 , 刘磊 , 王量弘 et al. 基于自适应向量机检测睡眠呼吸暂停综合征的最优特征组合筛选 [J]. | 中国医药导报 , 2019 , 16 (12) : 165-168 . |
| MLA | 王新康 et al. "基于自适应向量机检测睡眠呼吸暂停综合征的最优特征组合筛选" . | 中国医药导报 16 . 12 (2019) : 165-168 . |
| APA | 王新康 , 刘磊 , 王量弘 , 樊明辉 . 基于自适应向量机检测睡眠呼吸暂停综合征的最优特征组合筛选 . | 中国医药导报 , 2019 , 16 (12) , 165-168 . |
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Abstract ：
This study presents a low-power multi-lead wearable electrocardiogram (ECG) signal sensor system design that can simultaneously acquire the electrocardiograms from three leads, I, II, and V1. The sensor system includes two parts, an ECG test clothing with five electrode patches and an acquisition device. Compared with the traditional 12-lead wired ECG detection instrument, which limits patient mobility and needs medical staff assistance to acquire the ECG signal, the proposed vest-type ECG acquisition system is very comfortable and easy to use by patients themselves anytime and anywhere, especially for the elderly. The proposed study incorporates three methods to reduce the power consumption of the system by optimizing the micro control unit (MCU) working mode, adjusting the radio frequency (RF) parameters, and compressing the transmitted data. In addition, Huffman lossless coding is used to compress the transmitted data in order to increase the sampling rate of the acquisition system. It makes the whole system operate continuously for a long period of time and acquire abundant ECG information, which is helpful for clinical diagnosis. Finally, a series of tests were performed on the designed wearable ECG device. The results have demonstrated that the multi-lead wearable ECG device can collect, process, and transmit ECG data through Bluetooth technology. The ECG waveforms collected by the device are clear, complete, and can be displayed in real-time on a mobile phone. The sampling rate of the proposed wearable sensor system is 250 Hz per lead, which is dependent on the lossless compression scheme. The device achieves a compression ratio of 2.31. By implementing a low power design on the device, the resulting overall operational current of the device is reduced by 37.6% to 9.87 mA under a supply voltage of 2.1 V. The proposed vest-type multi-lead ECG acquisition device can be easily employed by medical staff for clinical diagnosis and is a suitable wearable device in monitoring and nursing the off-ward patients.
Keyword ：
Bluetooth Bluetooth Huffman coding Huffman coding low power consumption low power consumption multi-lead multi-lead wearable electrocardiogram (ECG) sensor system wearable electrocardiogram (ECG) sensor system
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| GB/T 7714 | Wang, Liang-Hung , Zhang, Wei , Guan, Ming-Hui et al. A Low-Power High-Data-Transmission Multi-Lead ECG Acquisition Sensor System [J]. | SENSORS , 2019 , 19 (22) . |
| MLA | Wang, Liang-Hung et al. "A Low-Power High-Data-Transmission Multi-Lead ECG Acquisition Sensor System" . | SENSORS 19 . 22 (2019) . |
| APA | Wang, Liang-Hung , Zhang, Wei , Guan, Ming-Hui , Jiang, Su-Ya , Fan, Ming-Hui , Abu, Patricia Angela R. et al. A Low-Power High-Data-Transmission Multi-Lead ECG Acquisition Sensor System . | SENSORS , 2019 , 19 (22) . |
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