1
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Chen Z, Peng B, Zhou Y, Hao Y, Xie X. Interpretable and accurate curve-fitting method for arterial pulse wave modeling and decomposition. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2023; 39:e3775. [PMID: 37740645 DOI: 10.1002/cnm.3775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 09/08/2023] [Accepted: 09/10/2023] [Indexed: 09/24/2023]
Abstract
Arterial pulse waveforms contain a wealth of information about the cardiovascular system. There is a lack of physical meaning in the mathematical model of arterial pulse waves, while the physical model fails to offer individuality as too many assumptions are involved. In this article, we focus on promoting the interpretability of the arterial pulse mathematical model. The proposed method is based on newly developed 3-term fitting functions individualized by the physiological parameter assignment, which are the peak times of the reflected and dicrotic waves in a pulse. In this manner, the model allows decomposition of the pulse into sub-signals with clear physiological significance. With nearly 10,000 pulse fitting experiments, it is demonstrated that the proposed method outperforms the standard methods in fitting accuracy while providing parameters linked to hemodynamic characteristics and common clinical indices such as the peripheral augmentation index (pAI). The proposed method innovatively maintains the individuality and accuracy of mathematical models while improving the interpretability of their parameters. The applications of this newly developed method, which explicitly incorporates hemodynamic characteristics, are expected to be particularly valuable in future pulse wave decomposition studies.
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Affiliation(s)
- Zhendong Chen
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
| | - Bo Peng
- Department of Musical Instrument Engineering, Xinghai Conservatory of Music, Guangzhou, China
- Sniow Research and Development Laboratory, Foshan, China
| | - Yuqi Zhou
- Department of Pulmonary and Critical Care Medicine, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yinan Hao
- Department of Musical Instrument Engineering, Xinghai Conservatory of Music, Guangzhou, China
| | - Xiaohua Xie
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
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2
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Kang X, Huang L, Zhang Y, Yun S, Jiao B, Liu X, Zhang J, Li Z, Zhang H. Wearable Multi-Channel Pulse Signal Acquisition System Based on Flexible MEMS Sensor Arrays with TSV Structure. Biomimetics (Basel) 2023; 8:biomimetics8020207. [PMID: 37218793 DOI: 10.3390/biomimetics8020207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/12/2023] [Accepted: 05/13/2023] [Indexed: 05/24/2023] Open
Abstract
Micro-electro-mechanical system (MEMS) pressure sensors play a significant role in pulse wave acquisition. However, existing MEMS pulse pressure sensors bound with a flexible substrate by gold wire are vulnerable to crush fractures, leading to sensor failure. Additionally, establishing an effective mapping between the array sensor signal and pulse width remains a challenge. To solve the above problems, we propose a 24-channel pulse signal acquisition system based on a novel MEMS pressure sensor with a through-silicon-via (TSV) structure, which connects directly to a flexible substrate without gold wire bonding. Firstly, based on the MEMS sensor, we designed a 24-channel pressure sensor flexible array to collect the pulse waves and static pressure. Secondly, we developed a customized pulse preprocessing chip to process the signals. Finally, we built an algorithm to reconstruct the three-dimensional pulse wave from the array signal and calculate the pulse width. The experiments verify the high sensitivity and effectiveness of the sensor array. In particular, the measurement results of pulse width are highly positively correlated with those obtained via infrared images. The small-size sensor and custom-designed acquisition chip meet the needs of wearability and portability, meaning that it has significant research value and commercial prospects.
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Affiliation(s)
- Xiaoxiao Kang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Lin Huang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Yitao Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Shichang Yun
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
| | - Binbin Jiao
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Liu
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Jun Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Zhiqiang Li
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Haiying Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
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3
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Sološenko A, Paliakaitė B, Marozas V, Sörnmo L. Training Convolutional Neural Networks on Simulated Photoplethysmography Data: Application to Bradycardia and Tachycardia Detection. Front Physiol 2022; 13:928098. [PMID: 35923223 PMCID: PMC9339964 DOI: 10.3389/fphys.2022.928098] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 06/15/2022] [Indexed: 11/23/2022] Open
Abstract
Objective: To develop a method for detection of bradycardia and ventricular tachycardia using the photoplethysmogram (PPG). Approach: The detector is based on a dual-branch convolutional neural network (CNN), whose input is the scalograms of the continuous wavelet transform computed in 5-s segments. Training and validation of the CNN is accomplished using simulated PPG signals generated from RR interval series extracted from public ECG databases. Manually annotated real PPG signals from the PhysioNet/CinC 2015 Challenge Database are used for performance evaluation. The performance is compared to that of a pulse-based reference detector. Results: The sensitivity/specificity were found to be 98.1%/97.9 and 76.6%/96.8% for the CNN-based detector, respectively, whereas the corresponding results for the pulse-based detector were 94.7%/99.8 and 67.1%/93.8%, respectively. Significance: The proposed detector may be useful for continuous, long-term monitoring of bradycardia and tachycardia using wearable devices, e.g., wrist-worn devices, especially in situations where sensitivity is favored over specificity. The study demonstrates that simulated PPG signals are suitable for training and validation of a CNN.
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Affiliation(s)
- Andrius Sološenko
- Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania
- *Correspondence: Andrius Sološenko ,
| | - Birutė Paliakaitė
- Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania
| | - Vaidotas Marozas
- Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania
- Department of Electronics Engineering, Kaunas University of Technology, Kaunas, Lithuania
| | - Leif Sörnmo
- Department of Biomedical Engineering, Lund University, Lund, Sweden
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4
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Guo C, Jiang Z, He H, Liao Y, Zhang D. Wrist pulse signal acquisition and analysis for disease diagnosis: A review. Comput Biol Med 2022; 143:105312. [PMID: 35203039 DOI: 10.1016/j.compbiomed.2022.105312] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 01/22/2022] [Accepted: 02/07/2022] [Indexed: 11/26/2022]
Abstract
Pulse diagnosis (PD) plays an indispensable role in healthcare in China, India, Korea, and other Orient countries. It requires considerable training and experience to master. The results of pulse diagnosis rely heavily on the practitioner's subjective analysis, which means that the results from different physicians may be inconsistent. To overcome these drawbacks, computational pulse diagnosis (CPD) is used with advanced sensing techniques and analytical methods. Focusing on the main processes of CPD, this paper provides a systematic review of the latest advances in pulse signal acquisition, signal preprocessing, feature extraction, and signal recognition. The most relevant principles and applications are presented along with current progress. Extensive comparisons and analyses are conducted to evaluate the merits of different methods employed in CPD. While much progress has been made, a lack of datasets and benchmarks has limited the development of CPD. To address this gap and facilitate further research, we present a benchmark to evaluate different methods. We conclude with observations of the status and prospects of CPD.
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Affiliation(s)
- Chaoxun Guo
- The Chinese University of Hong Kong(Shenzhen), Shenzhen, 518172, Guangdong, China; Shenzhen Research Institute of Big Data, Shenzhen, 518172, Guangdong, China; Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, 518172, Guangdong, China.
| | - Zhixing Jiang
- The Chinese University of Hong Kong(Shenzhen), Shenzhen, 518172, Guangdong, China; Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, 518172, Guangdong, China.
| | - Haoze He
- New York University, New York, 10012, New York, United States
| | - Yining Liao
- The Chinese University of Hong Kong(Shenzhen), Shenzhen, 518172, Guangdong, China; Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, 518172, Guangdong, China
| | - David Zhang
- The Chinese University of Hong Kong(Shenzhen), Shenzhen, 518172, Guangdong, China; Shenzhen Research Institute of Big Data, Shenzhen, 518172, Guangdong, China; Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, 518172, Guangdong, China.
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5
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Cui H, Wang Z, Yu B, Jiang F, Geng N, Li Y, Xu L, Zheng D, Zhang B, Lu P, Greenwald SE. Statistical Analysis of the Consistency of HRV Analysis Using BCG or Pulse Wave Signals. SENSORS (BASEL, SWITZERLAND) 2022; 22:2423. [PMID: 35336592 PMCID: PMC8951337 DOI: 10.3390/s22062423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/22/2022] [Accepted: 02/28/2022] [Indexed: 05/06/2023]
Abstract
Ballistocardiography (BCG) is considered a good alternative to HRV analysis with its non-contact and unobtrusive acquisition characteristics. However, consensus about its validity has not yet been established. In this study, 50 healthy subjects (26.2 ± 5.5 years old, 22 females, 28 males) were invited. Comprehensive statistical analysis, including Coefficients of Variation (CV), Lin’s Concordance Correlation Coefficient (LCCC), and Bland-Altman analysis (BA ratio), were utilized to analyze the consistency of BCG and ECG signals in HRV analysis. If the methods gave different answers, the worst case was taken as the result. Measures of consistency such as Mean, SDNN, LF gave good agreement (the absolute value of CV difference < 2%, LCCC > 0.99, BA ratio < 0.1) between J-J (BCG) and R-R intervals (ECG). pNN50 showed moderate agreement (the absolute value of CV difference < 5%, LCCC > 0.95, BA ratio < 0.2), while RMSSD, HF, LF/HF indicated poor agreement (the absolute value of CV difference ≥ 5% or LCCC ≤ 0.95 or BA ratio ≥ 0.2). Additionally, the R-R intervals were compared with P-P intervals extracted from the pulse wave (PW). Except for pNN50, which exhibited poor agreement in this comparison, the performances of the HRV indices estimated from the PW and the BCG signals were similar.
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Affiliation(s)
- Huiying Cui
- College of Medicine and Biological and Information Engineering, Northeastern University, Shenyang 110167, China; (H.C.); (Z.W.); (F.J.)
| | - Zhongyi Wang
- College of Medicine and Biological and Information Engineering, Northeastern University, Shenyang 110167, China; (H.C.); (Z.W.); (F.J.)
| | - Bin Yu
- Philips Design, 5611 AZ Eindhoven, The Netherlands;
| | - Fangfang Jiang
- College of Medicine and Biological and Information Engineering, Northeastern University, Shenyang 110167, China; (H.C.); (Z.W.); (F.J.)
| | - Ning Geng
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang 110819, China;
| | - Yongchun Li
- Shenyang Contain Electronic Technology Co., Ltd., Shenyang 110167, China;
| | - Lisheng Xu
- College of Medicine and Biological and Information Engineering, Northeastern University, Shenyang 110167, China; (H.C.); (Z.W.); (F.J.)
- Neusoft Research of Intelligent Healthcare Technology, Co., Ltd., Shenyang 110167, China
| | - Dingchang Zheng
- Research Centre for Intelligent Healthcare, Coventry University, Coventry CV1 5RW, UK;
| | - Biyong Zhang
- BOBO Technology, Hangzhou 310000, China;
- User System Interaction Group, Industrial Design, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
| | - Peilin Lu
- Neuroscience Center, Department of Neurology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310000, China;
| | - Stephen E. Greenwald
- Blizard Institute, Barts & The London School of Medicine & Dentistry, Queen Mary University of London, London E1 4NS, UK
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Kang X, Zhang J, Shao Z, Wang G, Geng X, Zhang Y, Zhang H. A Wearable and Real-Time Pulse Wave Monitoring System Based on a Flexible Compound Sensor. BIOSENSORS 2022; 12:bios12020133. [PMID: 35200393 PMCID: PMC8870208 DOI: 10.3390/bios12020133] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 02/09/2022] [Accepted: 02/18/2022] [Indexed: 12/30/2022]
Abstract
Continuous monitoring of pulse waves plays a significant role in reflecting physical conditions and disease diagnosis. However, the current collection equipment cannot simultaneously achieve wearable and continuous monitoring under varying pressure and provide personalized pulse wave monitoring targeted different human bodies. To solve the above problems, this paper proposed a novel wearable and real-time pulse wave monitoring system based on a novel flexible compound sensor. Firstly, a custom-packaged pressure sensor, a signal stabilization structure, and a micro pressurization system make up the flexible compound sensor to complete the stable acquisition of pulse wave signals under continuously varying pressure. Secondly, a real-time algorithm completes the analysis of the trend of the pulse wave peak, which can quickly and accurately locate the best pulse wave for different individuals. Finally, the experimental results show that the wearable system can both realize continuous monitoring and reflecting trend differences and quickly locate the best pulse wave for different individuals with the 95% accuracy. The weight of the whole system is only 52.775 g, the working current is 46 mA, and the power consumption is 160 mW. Its small size and low power consumption meet wearable and portable scenarios, which has significant research value and commercialization prospects.
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Affiliation(s)
- Xiaoxiao Kang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (X.K.); (J.Z.); (Z.S.); (G.W.); (X.G.); (Y.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Jun Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (X.K.); (J.Z.); (Z.S.); (G.W.); (X.G.); (Y.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Zheming Shao
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (X.K.); (J.Z.); (Z.S.); (G.W.); (X.G.); (Y.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Guotai Wang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (X.K.); (J.Z.); (Z.S.); (G.W.); (X.G.); (Y.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Xingguang Geng
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (X.K.); (J.Z.); (Z.S.); (G.W.); (X.G.); (Y.Z.)
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Yitao Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (X.K.); (J.Z.); (Z.S.); (G.W.); (X.G.); (Y.Z.)
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Haiying Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (X.K.); (J.Z.); (Z.S.); (G.W.); (X.G.); (Y.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
- Correspondence:
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7
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Cortical thinning is associated with brain pulsatility in older adults: An MRI and NIRS study. Neurobiol Aging 2021; 106:103-118. [PMID: 34274697 DOI: 10.1016/j.neurobiolaging.2021.05.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 03/29/2021] [Accepted: 05/03/2021] [Indexed: 11/21/2022]
Abstract
Aging is accompanied by global brain atrophy occurring unequally across the brain. Cortical thinning is seen with aging with a larger loss in the frontal and temporal subregions. We explored the link between regional cortical thickness and regional cerebral pulsatility. Sixty healthy individuals were divided into two age groups, young (aged 19-31) and older (aged 65-75) adults. Each participant underwent a near-infrared spectroscopy (NIRS) scan to index regional brain pulsatility from cerebral pulse-transit-time-to-the peak-of-the-pulse (PTTp), an anatomical magnetic resonance imaging (MRI) and a phase-contrast MRI (PC-MRI) scan to measure arterial and cerebrospinal fluid (CSF) pulsatility. In older adults, the greatest association between cerebral pulsatility and cortical thickness was found in superior and middle temporal and superior, middle and inferior frontal areas, which are the regions perfused first by the internal carotid arteries. This association dropped in the postcentral and superior parietal regions. These findings suggest higher brain pulsatility as a potential risk factor contributing to cortical thinning for some brain regions more than others.
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8
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Black RA, Houston G. 40th Anniversary Issue: Reflections on papers from the archive on "Cardiovascular devices and modelling". Med Eng Phys 2020; 72:74-75. [PMID: 31554581 DOI: 10.1016/j.medengphy.2019.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Richard A Black
- Department of Biomedical Engineering, University of Strathclyde, Glasgow, Scotland, UK.
| | - Gregor Houston
- Department of Biomedical Engineering, University of Strathclyde, Glasgow, Scotland, UK
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9
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Wang H, Wang L, Sun N, Yao Y, Hao L, Xu L, Greenwald SE. Quantitative Comparison of the Performance of Piezoresistive, Piezoelectric, Acceleration, and Optical Pulse Wave Sensors. Front Physiol 2020; 10:1563. [PMID: 32009976 PMCID: PMC6971205 DOI: 10.3389/fphys.2019.01563] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 12/12/2019] [Indexed: 11/16/2022] Open
Abstract
The accurate measurement of the arterial pulse wave is beneficial to clinical health assessment and is important for the effective diagnosis of many types of cardiovascular disease. A variety of sensors have been developed for the non-invasive detection of these waves, but the type of sensor has an impact on the measurement results. Therefore, it is necessary to compare and analyze the signals obtained under a range of conditions using various pulse sensors to aid in making an informed choice of the appropriate type. From the available types we have selected four: a piezoresistive strain gauge sensor (PESG) and a piezoelectric Millar tonometer (the former with the ability to measure contact force), a circular film acceleration sensor, and an optical reflection sensor. Pulse wave signals were recorded from the left radial, carotid, femoral, and digital arteries of 60 subjects using these four sensors. Their performance was evaluated by analyzing their susceptibilities to external factors (contact force, measuring site, and ambient light intensity) and by comparing their stability and reproducibility. Under medium contact force, the peak-to-peak amplitude of the signals was higher than that at high and low force levels and the variability of signal waveform was small. The optical sensor was susceptible to ambient light. Analysis of the intra-class correlation coefficients (ICCs) of the pulse wave parameters showed that the tonometer and accelerometer had good stability (ICC > 0.80), and the PESG and optical sensor had moderate stability (0.46 < ICC < 0.86). Intra-observer analysis showed that the tonometer and accelerometer had good reproducibility (ICC > 0.75) and the PESG and optical sensor had moderate reproducibility (0.42 < ICC < 0.91). Inter-observer analysis demonstrated that the accelerometer had good reproducibility (ICC > 0.85) and the three other sensors had moderate reproducibility (0.52 < ICC < 0.96). We conclude that the type of sensor and measurement site affect pulse wave characteristics and the careful selection of appropriate sensor and measurement site are required according to the research and clinical need. Moreover, the influence of external factors such as contact pressure and ambient light should be fully taken into account.
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Affiliation(s)
- Hongju Wang
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Lu Wang
- School of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Nannan Sun
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Yang Yao
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Liling Hao
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Lisheng Xu
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
- Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang, China
| | - Stephen E. Greenwald
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
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10
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Chen C, Li Z, Zhang Y, Zhang S, Hou J, Zhang H. A 3D Wrist Pulse Signal Acquisition System for Width Information of Pulse Wave. SENSORS 2019; 20:s20010011. [PMID: 31861412 PMCID: PMC6983233 DOI: 10.3390/s20010011] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 11/16/2022]
Abstract
During pulse signal collection, width information of pulse waves is essential for the diagnosis of disease. However, currently used measuring instruments can only detect the amplitude while can't acquire the width information. This paper proposed a novel wrist pulse signal acquisition system, which could realize simultaneous measurements of the width and amplitude of dynamic pulse waves under different static forces. A tailor-packaged micro-electro-mechanical system (MEMS) sensor array was employed to collect pulse signals, a conditioning circuit was designed to process the signals, and a customized algorithm was developed to compute the width. Experiments were carried out to validate the accuracy of the sensor array and system effectiveness. The results showed the system could acquire not only the amplitude of pulse wave but also the width of it. The system provided more information about pulse waves, which could help doctors make the diagnosis.
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Affiliation(s)
- Chuanglu Chen
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (C.C.); (Y.Z.); (S.Z.); (J.H.); (H.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Zhiqiang Li
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (C.C.); (Y.Z.); (S.Z.); (J.H.); (H.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
- Correspondence:
| | - Yitao Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (C.C.); (Y.Z.); (S.Z.); (J.H.); (H.Z.)
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Shaolong Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (C.C.); (Y.Z.); (S.Z.); (J.H.); (H.Z.)
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Jiena Hou
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (C.C.); (Y.Z.); (S.Z.); (J.H.); (H.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
| | - Haiying Zhang
- Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; (C.C.); (Y.Z.); (S.Z.); (J.H.); (H.Z.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing 100029, China
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11
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A Novel MOGA-SVM Multinomial Classification for Organ Inflammation Detection. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9112284] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Wrist pulse signal (WPS) contains crucial information of humans’ health condition. It can serve as an alternative method for diagnosing of organ inflammation instead of traditional clinical measurement. In this paper, a novel multi-objective genetic algorithm based support vector machine (MOGA-SVM) has been proposed for the multinomial classification of the inflammations of appendix, pancreas, and duodenum. A customized similarity kernel (KCS) has been optimally designed. The performance of multinomial classification using KCS is compared with five types of kernels, linear, radial basis function (RBF), polynomial and sigmoid kernel, as well as mixtures of polynomial and RBF, to verify the effectiveness of KCS. The sensitivity, specificity and accuracy (Acc) of the proposed method are 92%, 91.2%, and 91.6% respectively. The results have demonstrated that KCS improves the accuracy of classification from 8.9% to 59.6%. When compared to related work, the proposed method increases the performance by more than 10%. It is believed that WPS can serve as alternative measures to diagnose organ inflammations.
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12
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Jiang X, Wei S, Ji J, Liu F, Li P, Liu C. Modeling radial artery pressure waveforms using curve fitting: Comparison of four types of fitting functions. Artery Res 2018. [DOI: 10.1016/j.artres.2018.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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