Article
Chemistry, Analytical
Tasbiraha Athaya, Sunwoong Choi
Summary: The study proposes a method using deep learning architecture for blood pressure monitoring, estimating non-invasively with fingertip PPG signals. The results demonstrate the effectiveness of directly estimating ABP waveform and achieving blood pressure indicators within acceptable error ranges according to standards.
Article
Engineering, Multidisciplinary
Lirui Xu, Pang Wu, Pan Xia, Fanglin Geng, Saihu Lu, Peng Wang, Xianxiang Chen, Zhenfeng Li, Lidong Du, Shuping Liu, Li Li, Hongbo Chang, Zhen Fang
Summary: This study presents an ultrasound system that can noninvasively measure local pulse pressure and blood pressure waveforms continuously. The system uses a low-computational method to evaluate pulse wave velocity and diameter waveforms, allowing the measurement of PP and blood pressure without calibration. The system has been validated in vitro and in vivo, demonstrating high accuracy and showing promise for diagnosing and preventing cardiovascular diseases.
Article
Geriatrics & Gerontology
Zhao Xu, Hongyang Chen, Hongyu Zhou, Xiaohui Sun, Jun Ren, Hongxia Sun, Chan Chen, Guo Chen
Summary: In this study, it was found that NICAP had poor correlation with arterial lines in elderly patients for the whole surgery or during anesthesia induction, and also showed poor comparability in detecting blood pressure change trends with arterial lines. These findings suggest that more accurate calibration and iteration are needed before NICAP can be clinically applied in elderly patients with comorbidities.
Article
Computer Science, Information Systems
Joohyun Seo, Hae-Seung Lee, Charles G. Sodini
Summary: This work presents a non-invasive method for evaluating carotid arterial blood pressure waveforms during the Valsalva maneuver. Using unfocused wide acoustic beams and a two-element ultrasound scanner, the study shows reliable measurements of arterial flow and distension waveforms even with possible artery displacements. The research demonstrates accurate estimation of pulse pressure and consistent waveform quality across different phases of the maneuver.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Biophysics
Yongan Zhou, Zhi Tan, Yuhong Liu, Haibo Cheng
Summary: This paper proposes an ABP-MultiNet3+ model for blood pressure prediction based on convolutional neural network. The model achieves small prediction error and meets the standards of AAMI and BHS. It has the potential to enable continuous blood pressure monitoring and reduce the harm caused by cardiovascular disease.
PHYSIOLOGICAL MEASUREMENT
(2023)
Article
Physiology
Joao Loureiro, Laura Bogatu, Lars Schmitt, Jorge Henriques, Paulo Carvalho, Gerrit J. Noordergraaf, Igor Paulussen, Jens Muehlsteff
Summary: Blood pressure (BP) surrogates, such as pulse transit time (PTT) or pulse arrival time (PAT), have been extensively studied for cuffless, continuous, and accurate BP inference. Current research focuses on advanced calibration procedures using cuff inflation to improve calibration robustness. A model has been developed to infer the relationship between PAT and BP, but further validation and improvements are needed. This work compares the model's behaviors with clinical data and conducts a sensitivity analysis to identify factors influencing cuff-induced vasculature changes.
FRONTIERS IN PHYSIOLOGY
(2023)
Review
Chemistry, Analytical
Tasbiraha Athaya, Sunwoong Choi
Summary: Accurate estimation of blood pressure waveforms is crucial for patient safety and care in ICUs. This review summarizes the current knowledge about BP waveforms, discusses three noninvasive methodologies for BP waveform estimation, and examines the feasibility of using these strategies at home and in ICUs.
Article
Peripheral Vascular Disease
Tommy Y. Cai, Marjan M. Haghighi, Philip A. Roberts, Jonathan Mervis, Ahmad Qasem, Mark Butlin, David S. Celermajer, Alberto Avolio, Michael R. Skilton, Julian G. Ayer
Summary: The study assessed the accuracy of current techniques against invasive intra-aortic measurements in children. Results showed that currently available radial artery transfer function accurately estimates central systolic blood pressure with invasive pulse pressure calibration, while age-appropriate transfer functions do not provide additional benefit. The accuracy of central augmentation index estimation appears to be transfer function dependent.
AMERICAN JOURNAL OF HYPERTENSION
(2021)
Article
Biotechnology & Applied Microbiology
Nicholas Milkovich, Anastasia Gkousioudi, Francesca Seta, Bela Suki, Yanhang Zhang
Summary: The study proposes a new index, harmonic distortion (HD), to characterize blood pressure waveform (BPW) and its relationship with other measures of arterial stiffness. The results show that HD is sensitive to changes in blood pressure and arterial stiffness, suggesting its potential as a noninvasive measure of arterial stiffness.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Hanguang Xiao, Wangwang Song, Chang Liu, Bo Peng, Mi Zhu, Bin Jiang, Zhi Liu
Summary: The study proposes a novel model (CBi-SAN) for the reconstruction of central arterial pressure (CAP) waveforms from radial artery pressure (RAP) waveforms. The CBi-SAN model, which combines convolutional neural networks, bidirectional long-short-term memory networks, and self-attention mechanisms, demonstrates great performance in CAP waveform reconstruction.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Guo-Yang Li, Yuxuan Jiang, Yang Zheng, Weiqiang Xu, Zhaoyi Zhang, Yanping Cao
Summary: The clinical and economic burdens of cardiovascular diseases are a global challenge. This study explores the use of guided axial waves to probe local blood pressures and mechanical properties of common carotid arteries. The results reveal a linear relationship between the square of group velocity and blood pressure, enabling the measurement of blood pressure waveform. Wavelet analysis is used to extract the dispersion relations of the guided axial waves, which helps determine the shear modulus. The findings suggest that guided axial waves can be used noninvasively to probe blood pressure and arterial stiffness, potentially aiding in early diagnosis of cardiovascular diseases.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2022)
Article
Engineering, Biomedical
Jill Stewart, Paul Stewart, Thomas Walker, Daniela Viramontes Horner, Bethany Lucas, Kelly White, Andy Muggleton, Mel Morris, Nicholas M. Selby, Maarten W. Taal
Summary: Intradialytic haemodynamic instability is a significant clinical issue in hemodialysis patients. Continuous non-invasive blood pressure monitoring using pressure sensors in the dialysis circuit could provide a feasible solution, without the need for direct patient contact. The study demonstrates the potential for deriving continuous brachial pressure measurements from arterial and venous line pressures, offering a promising approach for developing a practical continuous blood pressure monitoring device.
IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE
(2021)
Article
Anesthesiology
Karim Kouz, Friederike Weidemann, Ashkan Naebian, Anneke Lohr, Alina Bergholz, Kristen K. Thomsen, Linda Krause, Martin Petzoldt, Parisa Moll-Khosrawi, Daniel I. Sessler, Moritz Flick, Bernd Saugel
Summary: Continuous finger-cuff arterial pressure monitoring helps reduce hypotension within 15 min after starting induction of anesthesia and during noncardiac surgery compared to intermittent oscillometric arterial pressure monitoring.
Article
Computer Science, Information Systems
Chenbin Ma, Peng Zhang, Fan Song, Yangyang Sun, Guangda Fan, Tianyi Zhang, Youdan Feng, Guanglei Zhang
Summary: In this study, a Transformer-based method with knowledge distillation (KD-Informer) is proposed for continuous blood pressure (BP) monitoring using only photoplethysmography (PPG) signals. Experimental results showed that the KD-Informer can accurately estimate systolic BP (SBP) and diastolic BP (DBP) with high reliability and robustness.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Chemistry, Multidisciplinary
Zhiran Yi, Zhaoxu Liu, Wenbo Li, Tao Ruan, Xiang Chen, Jingquan Liu, Bin Yang, Wenming Zhang
Summary: This research investigates the correlation between piezoelectric pulse waves and blood pressure waves and develops a wireless wearable continuous blood pressure monitoring system. This system offers better portability compared to traditional systems and achieves the feasibility of wearable continuous blood pressure monitoring.
ADVANCED MATERIALS
(2022)
Review
Multidisciplinary Sciences
Serghei Mangul, Lana S. Martin, Brian L. Hill, Angela Ka-Mei Lam, Margaret G. Distler, Alex Zelikovsky, Eleazar Eskin, Jonathan Flint
NATURE COMMUNICATIONS
(2019)
Article
Biochemistry & Molecular Biology
Serghei Mangul, Thiago Mosqueiro, Richard J. Abdill, Dat Duong, Keith Mitchell, Varuni Sarwal, Brian Hill, Jaqueline Brito, Russell Jared Littman, Benjamin Statz, Angela Ka-Mei Lam, Gargi Dayama, Laura Grieneisen, Lana S. Martin, Jonathan Flint, Eleazar Eskin, Ran Blekhman
Article
Anesthesiology
Brian L. Hill, Robert Brown, Eilon Gabel, Nadav Rakocz, Christine Lee, Maxime Cannesson, Pierre Baldi, Loes Olde Loohuis, Ruth Johnson, Brandon Jew, Uri Maoz, Aman Mahajan, Sriram Sankararaman, Ira Hofer, Eran Halperin
BRITISH JOURNAL OF ANAESTHESIA
(2019)
Article
Multidisciplinary Sciences
Jaclyn M. Smith, Melvin Lathara, Hollis Wright, Brian Hill, Nalini Ganapati, Ganapati Srinivasa, Christopher T. Denny
Article
Multidisciplinary Sciences
Igor Mandric, Brian L. Hill, Malika K. Freund, Michael Thompson, Eran Halperin
Article
Multidisciplinary Sciences
David Goodman-Meza, Akos Rudas, Jeffrey N. Chiang, Paul C. Adamson, Joseph Ebinger, Nancy Sun, Patrick Botting, Jennifer A. Fulcher, Faysal G. Saab, Rachel Brook, Eleazar Eskin, Ulzee An, Misagh Kordi, Brandon Jew, Brunilda Balliu, Zeyuan Chen, Brian L. Hill, Elior Rahmani, Eran Halperin, Vladimir Manuel
Article
Multidisciplinary Sciences
Timothy S. Chang, Yi Ding, Malika K. Freund, Ruth Johnson, Tommer Schwarz, Julie M. Yabu, Chad Hazlett, Jeffrey N. Chiang, David A. Wulf, Daniel H. Geschwind, Manish J. Butte, Bogdan Pasaniuc
Summary: This study investigated COVID-19 risk factors in Hispanic/Latinx individuals using individual-level, electronic health records in a Los Angeles health system. Risk factors identified in Hispanic/Latinx were similar to those in non-Hispanic/Latinx whites, suggesting the importance of studying COVID-19 risk factors for Hispanic/Latinx individuals to guide equitable government policies and identify at-risk populations.
Article
Immunology
Danielle Klinger, Brian L. Hill, Noam Barda, Eran Halperin, Ofer N. Gofrit, Charles L. Greenblatt, Nadav Rappoport, Michal Linial, Herve Bercovier
Summary: BCG treatment in bladder cancer patients is associated with a significantly reduced risk of developing Alzheimer's disease and Parkinson's disease, especially in the elderly population aged 75 years or older. This beneficial effect may be attributed to the activation of long-term nonspecific immune effects.
Article
Multidisciplinary Sciences
Carlos Cinelli, Nathan LaPierre, Brian L. Hill, Sriram Sankararaman, Eleazar Eskin
Summary: The authors developed MR-SENSEMAKR, a software tool that quantifies the robustness of Mendelian Randomization (MR) study findings, and proposed sensitivity analysis tools to assess the validity threats to the results. They demonstrated how these tools can help researchers differentiate between robust and fragile findings using examples of the effect of body mass index on diastolic blood pressure and Townsend deprivation index.
NATURE COMMUNICATIONS
(2022)
Article
Health Care Sciences & Services
Nadav Rakocz, Jeffrey N. Chiang, Muneeswar G. Nittala, Giulia Corradetti, Liran Tiosano, Swetha Velaga, Michael Thompson, Brian L. Hill, Sriram Sankararaman, Jonathan L. Haines, Margaret A. Pericak-Vance, Dwight Stambolian, Srinivas R. Sadda, Eran Halperin
Summary: The core challenge of applying machine learning and artificial intelligence to medicine lies in the limited availability of annotated medical data, requiring manual work by expert clinicians. SLIVER-net, a new deep learning technique based on transfer learning, demonstrates superior performance in predicting clinical features from medical images with limited annotations. Utilizing a novel method to account for 3D structure, SLIVER-net outperforms standard deep learning techniques for medical volumes and shows generalizable performance across different datasets.
NPJ DIGITAL MEDICINE
(2021)
Article
Biotechnology & Applied Microbiology
Keith Mitchell, Jaqueline J. Brito, Igor Mandric, Qiaozhen Wu, Sergey Knyazev, Sei Chang, Lana S. Martin, Aaron Karlsberg, Ekaterina Gerasimov, Russell Littman, Brian L. Hill, Nicholas C. Wu, Harry Taegyun Yang, Kevin Hsieh, Linus Chen, Eli Littman, Taylor Shabani, German Enik, Douglas Yao, Ren Sun, Jan Schroeder, Eleazar Eskin, Alex Zelikovsky, Pavel Skums, Mihai Pop, Serghei Mangul