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Li J, Chu H, Chen Z, Yiu CK, Qu Q, Li Z, Yu X. Recent Advances in Materials, Devices and Algorithms Toward Wearable Continuous Blood Pressure Monitoring. ACS NANO 2024; 18:17407-17438. [PMID: 38923501 DOI: 10.1021/acsnano.4c04291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/28/2024]
Abstract
Continuous blood pressure (BP) tracking provides valuable insights into the health condition and functionality of the heart, arteries, and overall circulatory system of humans. The rapid development in flexible and wearable electronics has significantly accelerated the advancement of wearable BP monitoring technologies. However, several persistent challenges, including limited sensing capabilities and stability of flexible sensors, poor interfacial stability between sensors and skin, and low accuracy in BP estimation, have hindered the progress in wearable BP monitoring. To address these challenges, comprehensive innovations in materials design, device development, system optimization, and modeling have been pursued to improve the overall performance of wearable BP monitoring systems. In this review, we highlight the latest advancements in flexible and wearable systems toward continuous noninvasive BP tracking with a primary focus on materials development, device design, system integration, and theoretical algorithms. Existing challenges, potential solutions, and further research directions are also discussed to provide theoretical and technical guidance for the development of future wearable systems in continuous ambulatory BP measurement with enhanced sensing capability, robustness, and long-term accuracy.
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Affiliation(s)
- Jian Li
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Hongwei Chu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Shenzhen Key Laboratory of Flexible Printed Electronics Technology, School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
| | - Zhenlin Chen
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Chun Ki Yiu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Qing'ao Qu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Zhiyuan Li
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Xinge Yu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
- City University of Hong Kong Shenzhen Research Institute, Shenzhen 518057, China
- Hong Kong Institute for Clean Energy, City University of Hong Kong, Kowloon, Hong Kong, China
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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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Mistri RK, Mahto SK, Singh AK, Sinha R, Al-Gburi AJA, Alghamdi TAH, Alathbah M. Quad Element MIMO Antenna for C, X, Ku, and Ka-Band Applications. SENSORS (BASEL, SWITZERLAND) 2023; 23:8563. [PMID: 37896656 PMCID: PMC10610986 DOI: 10.3390/s23208563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 10/17/2023] [Accepted: 10/17/2023] [Indexed: 10/29/2023]
Abstract
This article presents a quad-element MIMO antenna designed for multiband operation. The prototype of the design is fabricated and utilizes a vector network analyzer (VNA-AV3672D) to measure the S-parameters. The proposed antenna is capable of operating across three broad frequency bands: 3-15.5 GHz, encompassing the C band (4-8 GHz), X band (8-12.4 GHz), and a significant portion of the Ku band (12.4-15.5 GHz). Additionally, it covers two mm-wave bands, specifically 26.4-34.3 GHz and 36.1-48.9 GHz, which corresponds to 86% of the Ka-band (27-40 GHz). To enhance its performance, the design incorporates a partial ground plane and a top patch featuring a dual-sided reverse 3-stage stair and a straight stick symmetrically placed at the bottom. The introduction of a defected ground structure (DGS) on the ground plane serves to provide a wideband response. The DGS on the ground plane plays a crucial role in improving the electromagnetic interaction between the grounding surface and the top patch, contributing to the wideband characteristics of the antenna. The dimensions of the proposed MIMO antenna are 31.7 mm × 31.7 mm × 1.6 mm. Furthermore, the article delves into the assessment of various performance metrics related to antenna diversity, such as ECC, DG, TARC, MEG, CCL, and channel capacity, with corresponding values of 0.11, 8.87 dB, -6.6 dB, ±3 dB, 0.32 bits/sec/Hz, and 18.44 bits/sec/Hz, respectively. Additionally, the equivalent circuit analysis of the MIMO system is explored in the article. It's worth noting that the measured results exhibit a strong level of agreement with the simulated results, indicating the reliability of the proposed design. The MIMO antenna's ability to exhibit multiband response, good diversity performance, and consistent channel capacity across various frequency bands renders it highly suitable for integration into multi-band wireless devices. The developed MIMO system should be applicable on n77/n78/n79 5G NR (3.3-5 GHz); WLAN (4.9-5.725 GHz); Wi-Fi (5.15-5.85 GHz); LTE5537.5 (5.15-5.925 GHz); WiMAX (5.25-5.85 GHz); WLAN (5.725-5.875 GHz); long-distance radio telecommunication (4-8 GHz; C-band); satellite, radar, space communications and terrestrial broadband (8-12 GHz; X-band); and various satellite communications (27-40 GHz; Ka-band).
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Affiliation(s)
- Raj Kumar Mistri
- Department of Electronics and Communication Engineering, Indian Institute of Information Technology, Ranchi 834010, Jharkhand, India; (R.K.M.); (A.K.S.)
| | - Santosh Kumar Mahto
- Department of Electronics and Communication Engineering, Indian Institute of Information Technology, Ranchi 834010, Jharkhand, India; (R.K.M.); (A.K.S.)
| | - Ajit Kumar Singh
- Department of Electronics and Communication Engineering, Indian Institute of Information Technology, Ranchi 834010, Jharkhand, India; (R.K.M.); (A.K.S.)
| | - Rashmi Sinha
- Department of Electronics and Communication Engineering, National Institute of Technology, Jamshedpur 831014, Jharkhand, India
| | - Ahmed Jamal Abdullah Al-Gburi
- Center for Telecommunication Research & Innovation (CeTRI), Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK), Universiti Teknikal Malaysia Melaka (UTeM), Jalan Hang Tuah Jaya, Durian Tunggal, Melaka 76100, Malaysia
| | - Thamer A. H. Alghamdi
- Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
| | - Moath Alathbah
- Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh 11451, Saudi Arabia
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Kong L, Li G, Wang Y, Cheng L, Lin L. Non-contact cardiopulmonary signal monitoring based on magnetic eddy current induction. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2023; 94:074101. [PMID: 37466408 DOI: 10.1063/5.0148820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 06/30/2023] [Indexed: 07/20/2023]
Abstract
The magnetic eddy current induction method has become an excellent solution for building home cardiopulmonary monitoring systems because of its non-contact and unobtrusive characteristics, but it has problems such as low precision and complex extraction of cardiopulmonary signals. Therefore, this paper designs a magnetic eddy current sensing system based on a Field Programmable Gate Array that can realize simultaneous real-time monitoring of cardiopulmonary signals. This system adopts a magnetic eddy current sensor design scheme that can improve the amount of cardiopulmonary information in the sensing signal. In addition, it uses a signal acquisition scheme that combines an inductance-to-digital converter (LDC) and oversampling technology to improve the resolution and signal-to-noise ratio of the sensing signal. Moreover, an optimized adaptive discrete wavelet transform algorithm is proposed in this system, which can realize the effective separation and extraction of cardiopulmonary signals in different respiration states. Comparing this system with the medical monitor, the cardiopulmonary signals obtained by the two have good consistency in the time-frequency domain. Under low motion, respiration rate and heart rate detected by this system are within the confidence interval of the 95% limit of agreement; the relative errors are less than 2.63% and 1.37%, respectively; and the accuracy rates are greater than 99.30% and 99.60%, respectively. In addition, an experiment with an asthmatic patient showed that the system still has good detection performance under pathological conditions and can monitor abnormal conditions such as coughing.
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Affiliation(s)
- Li Kong
- State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China
| | - Gang Li
- State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China
| | - Yunyi Wang
- State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China
| | - Leiyang Cheng
- State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China
| | - Ling Lin
- State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China
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Vysotskaya N, Will C, Servadei L, Maul N, Mandl C, Nau M, Harnisch J, Maier A. Continuous Non-Invasive Blood Pressure Measurement Using 60 GHz-Radar-A Feasibility Study. SENSORS (BASEL, SWITZERLAND) 2023; 23:4111. [PMID: 37112454 PMCID: PMC10145629 DOI: 10.3390/s23084111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 06/19/2023]
Abstract
Blood pressure monitoring is of paramount importance in the assessment of a human's cardiovascular health. The state-of-the-art method remains the usage of an upper-arm cuff sphygmomanometer. However, this device suffers from severe limitations-it only provides a static blood pressure value pair, is incapable of capturing blood pressure variations over time, is inaccurate, and causes discomfort upon use. This work presents a radar-based approach that utilizes the movement of the skin due to artery pulsation to extract pressure waves. From those waves, a set of 21 features was collected and used-together with the calibration parameters of age, gender, height, and weight-as input for a neural network-based regression model. After collecting data from 55 subjects from radar and a blood pressure reference device, we trained 126 networks to analyze the developed approach's predictive power. As a result, a very shallow network with just two hidden layers produced a systolic error of 9.2±8.3 mmHg (mean error ± standard deviation) and a diastolic error of 7.7±5.7 mmHg. While the trained model did not reach the requirements of the AAMI and BHS blood pressure measuring standards, optimizing network performance was not the goal of the proposed work. Still, the approach has displayed great potential in capturing blood pressure variation with the proposed features. The presented approach therefore shows great potential to be incorporated into wearable devices for continuous blood pressure monitoring for home use or screening applications, after improving this approach even further.
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Affiliation(s)
- Nastassia Vysotskaya
- Infineon Technologies AG, Am Campeon 1-15, 85579 Neubiberg, Germany
- Department for Computer Science 5 (Pattern Recognition), Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Martensstrasse 3, 91058 Erlangen, Germany
| | - Christoph Will
- Infineon Technologies AG, Am Campeon 1-15, 85579 Neubiberg, Germany
| | - Lorenzo Servadei
- Department of Electrical and Computer Engineering, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany
| | - Noah Maul
- Department for Computer Science 5 (Pattern Recognition), Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Martensstrasse 3, 91058 Erlangen, Germany
| | - Christian Mandl
- Infineon Technologies AG, Am Campeon 1-15, 85579 Neubiberg, Germany
| | - Merlin Nau
- Department for Computer Science 5 (Pattern Recognition), Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Martensstrasse 3, 91058 Erlangen, Germany
| | - Jens Harnisch
- Infineon Technologies AG, Am Campeon 1-15, 85579 Neubiberg, Germany
| | - Andreas Maier
- Department for Computer Science 5 (Pattern Recognition), Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Martensstrasse 3, 91058 Erlangen, Germany
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Planar MIMO antenna for mmWave applications: Evolution, present status & future scope. Heliyon 2023; 9:e13362. [PMID: 36820027 PMCID: PMC9937909 DOI: 10.1016/j.heliyon.2023.e13362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/23/2022] [Accepted: 01/28/2023] [Indexed: 02/04/2023] Open
Abstract
The increased traffic in e-commerce, cloud-based processing, social media, and online video streaming demands higher data rates. The current 4G has reached the bottleneck, due to which it may not be able to fulfill the high data demand, so the focus is drifting toward millimeter wave (mmWave). The mmWave spectrum ranging from 30 to 300 GHz offers wide bandwidth with low latency, which finds its application in various communication fields, including 5G cellular. Despite its atmospheric attenuation and non-line-of-sight (NLOS) propagation, most countries are currently adopting mmWave 5G at the 28/38 GHz band due to less atmospheric attenuation, low path loss exponent, and low signal spread at these bands. The single-element patch antenna is a compact solution for mmWave applications, but its performance is inferior in terms of bandwidth, gain, and radiation efficiency. The array antennas have overcome these demerits, as it has shown a significant increase in bandwidth, gain, and radiation efficiency. Still, it has a limitation on data rate support. As a result, Multiple-Input-Multiple-Output (MIMO) technology can increase the data rate to 1000 times through spatial diversity and multiplexing techniques. So, to refine the performance further, there is a need to comprehend the MIMO antenna structures designed so far at mmWave. This paper presents the planar MIMO antenna structures developed so far, categorized here as slot, coplanar waveguide, defected ground structures, tapered/Vivaldi, meta-surface/metamaterial, dielectric resonator, and flexible antennas. The performance of these designs is compared based on bandwidth, gain, isolation, efficiency, and radiation pattern. This article also discusses the effects of slots, partial ground, and decoupling structures on impedance matching, bandwidth, and isolation levels. Also, a thorough discussion of the design issues and future work to be undertaken is discussed in this here.
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Long-term stability of over-the-counter cuffless blood pressure monitors: a proposal. HEALTH AND TECHNOLOGY 2023; 13:53-63. [PMID: 36713070 PMCID: PMC9870659 DOI: 10.1007/s12553-023-00726-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 10/17/2022] [Accepted: 01/04/2023] [Indexed: 01/25/2023]
Abstract
Blood pressure is an important cardiovascular parameter. Currently, the cuff-based sphygmomanometer is a popular, reliable, measurement method, but blood pressure monitors without cuffs have become popular and are now available without a prescription. Blood pressure monitors must be approved by regulatory authorities. Current cuffless blood pressure (CL-BP) monitors are not suitable for at-home management and prevention of hypertension. This paper proposes simple criteria for over-the-counter CL-BP monitoring. First, the history of the sphygmomanometer and current standard blood pressure protocol are reviewed. The main components of CL-BP monitoring are accuracy during the resting condition, accuracy during dynamic blood pressure changes, and long-term stability. In this proposal we recommend intermittent measurement to ensure that active measurement accuracy mirrors resting condition accuracy. A new experimental protocol is proposed to maintain long-term stability. A medically approved automated sphygmomanometer was used as the standard device in this study. The long-term accuracy of the test device is based on the definition of propagation error, i.e., for an oscillometric automated sphygmomanometer (5 ± 8 mmHg) ± the error for the test device static accuracy (-0.12 ± 5.49 mmHg for systolic blood pressure and - 1.17 ± 5.06 mmHg for diastolic blood pressure). Thus, the long-term stabilities were - 3.38 ± 7.1 mmHg and - 1.38 ± 5.4 mmHg, which satisfied propagation error. Further research and discussion are necessary to create standards for use by manufacturers; such standards should be readily evaluated and ensure high-quality evidence. Supplementary information The online version contains supplementary material available at 10.1007/s12553-023-00726-6.
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Wu LW, OuYoung T, Chiu YC, Hsieh HF, Hsiu H. Discrimination between possible sarcopenia and metabolic syndrome using the arterial pulse spectrum and machine-learning analysis. Sci Rep 2022; 12:21452. [PMID: 36509825 PMCID: PMC9744729 DOI: 10.1038/s41598-022-26074-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 12/08/2022] [Indexed: 12/14/2022] Open
Abstract
Sarcopenia is defined as decreased skeletal muscle mass and function, and is an important cause of frailty in the elderly, also being associated with vascular lesions and poor microcirculation. The present study aimed to combine noninvasive pulse measurements, frequency-domain analysis, and machine learning (ML) analysis (1) to determine the effects on the pulse waveform induced by sarcopenia and (2) to develop discriminating models for patients with possible sarcopenia. Radial blood pressure waveform (BPW) signals were measured noninvasively for 1 min in 133 subjects who visited Tri-Service General Hospital for geriatric health checkups. They were assigned to a robust group and a possible-sarcopenia group that combined dynapenia, presarcopenia, and sarcopenia. Two classification methods were used: ML analysis and a self-developed scoring system that used 40 harmonic pulse indices as features: amplitude proportions and their coefficients of variation, and phase angles and their standard deviations. Significant differences were found in several spectral indices of the BPW between possible-sarcopenia and robust subjects. Threefold cross-validation results indicated excellent discrimination performance, with AUC equaling 0.77 when using LDA and 0.83 when using our scoring system. The present noninvasive and easy-to-use measurement and analysis method for detecting sarcopenia-induced changes in the arterial pulse transmission condition could aid the discrimination of possible sarcopenia.
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Affiliation(s)
- Li-Wei Wu
- grid.260565.20000 0004 0634 0356Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan ,grid.260565.20000 0004 0634 0356Health Management Center, Department of Family and Community Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Te OuYoung
- grid.260565.20000 0004 0634 0356Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan ,grid.260565.20000 0004 0634 0356Health Management Center, Department of Family and Community Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Yu-Chih Chiu
- grid.45907.3f0000 0000 9744 5137Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, No.43, Section 4, Keelung Road, Taipei, 10607 Taiwan
| | - Ho-Feng Hsieh
- grid.45907.3f0000 0000 9744 5137Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, No.43, Section 4, Keelung Road, Taipei, 10607 Taiwan
| | - Hsin Hsiu
- grid.45907.3f0000 0000 9744 5137Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, No.43, Section 4, Keelung Road, Taipei, 10607 Taiwan ,grid.260565.20000 0004 0634 0356Biomedical Engineering Research Center, National Defense Medical Center, Taipei, Taiwan
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Ouyoung T, Weng WL, Hu TY, Lee CC, Wu LW, Hsiu H. Machine-Learning Classification of Pulse Waveform Quality. SENSORS (BASEL, SWITZERLAND) 2022; 22:8607. [PMID: 36433203 PMCID: PMC9698948 DOI: 10.3390/s22228607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/01/2022] [Accepted: 11/07/2022] [Indexed: 06/16/2023]
Abstract
Pulse measurements made using wearable devices can aid the monitoring of human physiological condition. Accurate estimation of waveforms is often difficult for nonexperts; motion artifacts may occur during tonometry measurements when the skin-sensor contact pressure is insufficient. An alternative approach is to extract only high-quality pulses for use in index calculations. The present study aimed to determine the effectiveness of using machine-learning analysis in discriminating between high-quality and low-quality pulse waveforms induced by applying different contact pressures. Radial blood pressure waveform (BPW) signals were measured noninvasively in healthy young subjects using a strain-gauge transducer. One-minute-long trains of pulse data were measured when applying the appropriate contact pressure (67.80 ± 1.55 mmHg) and a higher contact pressure (151.80 ± 3.19 mmHg). Eight machine-learning algorithms were employed to evaluate the following 40 harmonic pulse indices: amplitude proportions and their coefficients of variation and phase angles and their standard deviations. Significant differences were noted in BPW indices between applying appropriate and higher skin-surface contact pressures. The present appropriate contact pressure could not only provide a suitable holding force for the wearable device but also helped to maintain the physiological stability of the underlying tissues. Machine-learning analysis provides an effective method for distinguishing between the high-quality and low-quality pulses with excellent discrimination performance (leave-one-subject-out test: random-forest AUC = 0.96). This approach will aid the development of an automatic screening method for waveform quality and thereby improve the noninvasive acquisition reliability. Other possible interfering factors in practical applications can also be systematically studied using a similar procedure.
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Affiliation(s)
- Te Ouyoung
- Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan
- School of Medicine, National Defense Medical Center, Taipei 114, Taiwan
- Health Management Center, Department of Family and Community Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan
| | - Wan-Ling Weng
- Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
| | - Ting-Yu Hu
- Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
| | - Chia-Chien Lee
- Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
| | - Li-Wei Wu
- Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan
- School of Medicine, National Defense Medical Center, Taipei 114, Taiwan
- Health Management Center, Department of Family and Community Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan
| | - Hsin Hsiu
- Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
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Andreozzi E, Sabbadini R, Centracchio J, Bifulco P, Irace A, Breglio G, Riccio M. Multimodal Finger Pulse Wave Sensing: Comparison of Forcecardiography and Photoplethysmography Sensors. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22197566. [PMID: 36236663 PMCID: PMC9570799 DOI: 10.3390/s22197566] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 09/26/2022] [Accepted: 10/01/2022] [Indexed: 05/31/2023]
Abstract
Pulse waves (PWs) are mechanical waves that propagate from the ventricles through the whole vascular system as brisk enlargements of the blood vessels' lumens, caused by sudden increases in local blood pressure. Photoplethysmography (PPG) is one of the most widespread techniques employed for PW sensing due to its ability to measure blood oxygen saturation. Other sensors and techniques have been proposed to record PWs, and include applanation tonometers, piezoelectric sensors, force sensors of different kinds, and accelerometers. The performances of these sensors have been analyzed individually, and their results have been found not to be in good agreement (e.g., in terms of PW morphology and the physiological parameters extracted). Such a comparison has led to a deeper comprehension of their strengths and weaknesses, and ultimately, to the consideration that a multimodal approach accomplished via sensor fusion would lead to a more robust, reliable, and potentially more informative methodology for PW monitoring. However, apart from various multichannel and multi-site systems proposed in the literature, no true multimodal sensors for PW recording have been proposed yet that acquire PW signals simultaneously from the same measurement site. In this study, a true multimodal PW sensor is presented, which was obtained by integrating a piezoelectric forcecardiography (FCG) sensor and a PPG sensor, thus enabling simultaneous mechanical-optical measurements of PWs from the same site on the body. The novel sensor performance was assessed by measuring the finger PWs of five healthy subjects at rest. The preliminary results of this study showed, for the first time, that a delay exists between the PWs recorded simultaneously by the PPG and FCG sensors. Despite such a delay, the pulse waveforms acquired by the PPG and FCG sensors, along with their first and second derivatives, had very high normalized cross-correlation indices in excess of 0.98. Six well-established morphological parameters of the PWs were compared via linear regression, correlation, and Bland-Altman analyses, which showed that some of these parameters were not in good agreement for all subjects. The preliminary results of this proof-of-concept study must be confirmed in a much larger cohort of subjects. Further investigation is also necessary to shed light on the physical origin of the observed delay between optical and mechanical PW signals. This research paves the way for the development of true multimodal, wearable, integrated sensors and for potential sensor fusion approaches to improve the performance of PW monitoring at various body sites.
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High-Speed Continuous Wavelet Transform Processor for Vital Signal Measurement Using Frequency-Modulated Continuous Wave Radar. SENSORS 2022; 22:s22083073. [PMID: 35459058 PMCID: PMC9032614 DOI: 10.3390/s22083073] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 04/08/2022] [Accepted: 04/14/2022] [Indexed: 01/02/2023]
Abstract
This paper proposes a high-speed continuous wavelet transform (CWT) processor to analyze vital signals extracted from a frequency-modulated continuous wave (FMCW) radar sensor. The proposed CWT processor consists of a fast Fourier transform (FFT) module, complex multiplier module, and inverse FFT (IFFT) module. For high-throughput processing, the FFT and IFFT modules are designed with the pipeline FFT architecture of radix-2 single-path delay feedback (R2SDF) and mixed-radix multipath delay commutator (MRMDC) architecture, respectively. In addition, the IFFT module and the complex multiplier module perform a four-channel operation to reduce the processing time from repeated operations. Simultaneously, the MRMDC IFFT module minimizes the circuit area by reducing the number of non-trivial multipliers by using a mixed-radix algorithm. In addition, the proposed CWT processor can support variable lengths of 8, 16, 32, 64, 128, 256, 512, and 1024 to analyze various vital signals. The proposed CWT processor was implemented in a field-programmable gate array (FPGA) device and verified through the measurement of heartbeat and respiration from an FMCW radar sensor. Experimental results showed that the proposed CWT processor can reduce the processing time by 48.4-fold and 40.7-fold compared to MATLAB software with Intel i7 CPU. Moreover, it can be confirmed that the proposed CWT processor can reduce the processing time by 73.3% compared to previous FPGA-based implementations.
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Guo K, Liu C, Zhao S, Lu J, Zhang S, Yang H. Design of a Millimeter-Wave Radar Remote Monitoring System for the Elderly Living Alone Using WIFI Communication. SENSORS 2021; 21:s21237893. [PMID: 34883895 PMCID: PMC8659913 DOI: 10.3390/s21237893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/24/2021] [Accepted: 11/24/2021] [Indexed: 11/20/2022]
Abstract
In response to the current demand for the remote monitoring of older people living alone, a non-contact human vital signs monitoring system based on millimeter wave radar has gradually become the object of research. This paper mainly carried out research regarding the detection method to obtain human breathing and heartbeat signals using a frequency modulated continuous wave system. We completed a portable millimeter-wave radar module for wireless communication. The radar module was a small size and had a WIFI communication interface, so we only needed to provide a power cord for the radar module. The breathing and heartbeat signals were detected and separated by FIR digital filter and the wavelet transform method. By building a cloud computing framework, we realized remote and senseless monitoring of the vital signs for older people living alone. Experiments were also carried out to compare the performance difference between the system and the common contact detection system. The experimental results showed that the life parameter detection system based on the millimeter wave sensor has strong real-time performance and accuracy.
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Affiliation(s)
- Kai Guo
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; (K.G.); (S.Z.)
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China;
| | - Chang Liu
- School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130001, China; (C.L.); (J.L.)
| | - Shasha Zhao
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China;
| | - Jingxin Lu
- School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130001, China; (C.L.); (J.L.)
| | - Senhao Zhang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; (K.G.); (S.Z.)
| | - Hongbo Yang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; (K.G.); (S.Z.)
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China;
- Correspondence:
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Wang H, Wang Z, Wang P, Yu M, Xu J, Zhang G. A novel approach to estimate blood pressure of blood loss continuously based on stacked auto-encoder neural networks. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102853] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Survey of Millimeter-Wave Propagation Measurements and Models in Indoor Environments. ELECTRONICS 2021. [DOI: 10.3390/electronics10141653] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The millimeter-wave (mmWave) is expected to deliver a huge bandwidth to address the future demands for higher data rate transmissions. However, one of the major challenges in the mmWave band is the increase in signal loss as the operating frequency increases. This has attracted several research interests both from academia and the industry for indoor and outdoor mmWave operations. This paper focuses on the works that have been carried out in the study of the mmWave channel measurement in indoor environments. A survey of the measurement techniques, prominent path loss models, analysis of path loss and delay spread for mmWave in different indoor environments is presented. This covers the mmWave frequencies from 28 GHz to 100 GHz that have been considered in the last two decades. In addition, the possible future trends for the mmWave indoor propagation studies and measurements have been discussed. These include the critical indoor environment, the roles of artificial intelligence, channel characterization for indoor devices, reconfigurable intelligent surfaces, and mmWave for 6G systems. This survey can help engineers and researchers to plan, design, and optimize reliable 5G wireless indoor networks. It will also motivate the researchers and engineering communities towards finding a better outcome in the future trends of the mmWave indoor wireless network for 6G systems and beyond.
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Mynard JP, Kondiboyina A, Kowalski R, Cheung MMH, Smolich JJ. Measurement, Analysis and Interpretation of Pressure/Flow Waves in Blood Vessels. Front Physiol 2020; 11:1085. [PMID: 32973569 PMCID: PMC7481457 DOI: 10.3389/fphys.2020.01085] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 08/06/2020] [Indexed: 01/10/2023] Open
Abstract
The optimal performance of the cardiovascular system, as well as the break-down of this performance with disease, both involve complex biomechanical interactions between the heart, conduit vascular networks and microvascular beds. ‘Wave analysis’ refers to a group of techniques that provide valuable insight into these interactions by scrutinizing the shape of blood pressure and flow/velocity waveforms. The aim of this review paper is to provide a comprehensive introduction to wave analysis, with a focus on key concepts and practical application rather than mathematical derivations. We begin with an overview of invasive and non-invasive measurement techniques that can be used to obtain the signals required for wave analysis. We then review the most widely used wave analysis techniques—pulse wave analysis, wave separation and wave intensity analysis—and associated methods for estimating local wave speed or characteristic impedance that are required for decomposing waveforms into forward and backward wave components. This is followed by a discussion of the biomechanical phenomena that generate waves and the processes that modulate wave amplitude, both of which are critical for interpreting measured wave patterns. Finally, we provide a brief update on several emerging techniques/concepts in the wave analysis field, namely wave potential and the reservoir-excess pressure approach.
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Affiliation(s)
- Jonathan P Mynard
- Heart Research, Murdoch Children's Research Institute, Melbourne, VIC, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, VIC, Australia.,Department of Biomedical Engineering, The University of Melbourne, Melbourne, VIC, Australia.,Department of Cardiology, The Royal Children's Hospital, Parkville, VIC, Australia
| | - Avinash Kondiboyina
- Heart Research, Murdoch Children's Research Institute, Melbourne, VIC, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, VIC, Australia
| | - Remi Kowalski
- Heart Research, Murdoch Children's Research Institute, Melbourne, VIC, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, VIC, Australia.,Department of Cardiology, The Royal Children's Hospital, Parkville, VIC, Australia
| | - Michael M H Cheung
- Heart Research, Murdoch Children's Research Institute, Melbourne, VIC, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, VIC, Australia.,Department of Cardiology, The Royal Children's Hospital, Parkville, VIC, Australia
| | - Joseph J Smolich
- Heart Research, Murdoch Children's Research Institute, Melbourne, VIC, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, VIC, Australia
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Pandit JA, Lores E, Batlle D. Cuffless Blood Pressure Monitoring: Promises and Challenges. Clin J Am Soc Nephrol 2020; 15:1531-1538. [PMID: 32680913 PMCID: PMC7536750 DOI: 10.2215/cjn.03680320] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Current BP measurements are on the basis of traditional BP cuff approaches. Ambulatory BP monitoring, at 15- to 30-minute intervals usually over 24 hours, provides sufficiently continuous readings that are superior to the office-based snapshot, but this system is not suitable for frequent repeated use. A true continuous BP measurement that could collect BP passively and frequently would require a cuffless method that could be worn by the patient, with the data stored electronically much the same way that heart rate and heart rhythm are already done routinely. Ideally, BP should be measured continuously and frequently during diverse activities during both daytime and nighttime in the same subject by means of novel devices. There is increasing excitement for newer methods to measure BP on the basis of sensors and algorithm development. As new devices are refined and their accuracy is improved, it will be possible to better assess masked hypertension, nocturnal hypertension, and the severity and variability of BP. In this review, we discuss the progression in the field, particularly in the last 5 years, ending with sensor-based approaches that incorporate machine learning algorithms to personalized medicine.
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Affiliation(s)
- Jay A Pandit
- Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Enrique Lores
- Division of Nephrology and Hypertension, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Daniel Batlle
- Division of Nephrology and Hypertension, Northwestern University Feinberg School of Medicine, Chicago, Illinois
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