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A correlation study of beat-to-beat R-R intervals and pulse arrival time under natural state and cold stimulation. Sci Rep 2021; 11:11215. [PMID: 34045498 PMCID: PMC8159926 DOI: 10.1038/s41598-021-90056-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 05/06/2021] [Indexed: 11/08/2022] Open
Abstract
Beat-to-beat R-R intervals (RRI) and pulse arrival time (PAT) provide pivotal information to evaluate cardiac autonomic functions for predicting arrhythmias and cardiovascular morbidity. However, their relationship has not been clearly understood. In this study, we simultaneously recorded electrocardiograms and photoplethysmograms on 34 subjects in the natural state, and on 55 subjects under the cold stimulation. The RRI and the PAT were calculated and then analyzed using Pearson correlation coefficient. The results showed that the RRI and the PAT were strongly correlated (r = 0.562) and the RRI series were 2.18 ± 0.40 beats advanced to the PAT series. After smoothing, the RRI and the PAT were more correlated in the low frequency than in the high frequency. Furthermore, when involving RRI with the phase effect, the proposed PAT based model showed better performance for blood pressure estimation. We think these results are helpful to understand the underlying regulatory mechanisms of the two cardiovascular factors, and would provide useful suggestions for non-invasive cuffless blood pressure estimation.
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Chen YH, Sawan M. Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction. SENSORS (BASEL, SWITZERLAND) 2021; 21:E460. [PMID: 33440697 PMCID: PMC7827415 DOI: 10.3390/s21020460] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 02/07/2023]
Abstract
We review in this paper the wearable-based technologies intended for real-time monitoring of stroke-related physiological parameters. These measurements are undertaken to prevent death and disability due to stroke. We compare the various characteristics, such as weight, accessibility, frequency of use, data continuity, and response time of these wearables. It was found that the most user-friendly wearables can have limitations in reporting high-precision prediction outcomes. Therefore, we report also the trend of integrating these wearables into the internet of things (IoT) and combining electronic health records (EHRs) and machine learning (ML) algorithms to establish a stroke risk prediction system. Due to different characteristics, such as accessibility, time, and spatial resolution of various wearable-based technologies, strategies of applying different types of wearables to maximize the efficacy of stroke risk prediction are also reported. In addition, based on the various applications of multimodal electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) on stroke patients, the perspective of using this technique to improve the prediction performance is elaborated. Expected prediction has to be dynamically delivered with high-precision outcomes. There is a need for stroke risk stratification and management to reduce the resulting social and economic burden.
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Affiliation(s)
- Yun-Hsuan Chen
- CenBRAIN Lab., School of Engineering, Westlake University, Hangzhou 310024, China
- Institute of Advanced Study, Westlake Institute for Advanced Study, Hangzhou 310024, China
| | - Mohamad Sawan
- CenBRAIN Lab., School of Engineering, Westlake University, Hangzhou 310024, China
- Institute of Advanced Study, Westlake Institute for Advanced Study, Hangzhou 310024, China
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Mahmud MS, Fang H, Carreiro S, Wang H, Boyer EW. Wearables technology for drug abuse detection: A survey of recent advancement. ACTA ACUST UNITED AC 2019. [DOI: 10.1016/j.smhl.2018.09.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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Davidson S, Pretty C, Balmer J, Desaive T, Chase JG. Blood pressure waveform contour analysis for assessing peripheral resistance changes in sepsis. Biomed Eng Online 2018; 17:171. [PMID: 30458800 PMCID: PMC6245924 DOI: 10.1186/s12938-018-0603-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 11/09/2018] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND This paper proposes a methodology for helping bridge the gap between the complex waveform information frequently available in an intensive care unit and the simple, lumped values favoured for rapid clinical diagnosis and management. This methodology employs a simple waveform contour analysis approach to compare aortic, femoral and central venous pressure waveforms on a beat-by-beat basis and extract lumped metrics pertaining to the pressure drop and pressure-pulse amplitude attenuation as blood passes through the various sections of systemic circulation. RESULTS Validation encompasses a comparison between novel metrics and well-known, analogous clinical metrics such as mean arterial and venous pressures, across an animal model of induced sepsis. The novel metric Ofe → vc, the direct pressure offset between the femoral artery and vena cava, and the clinical metric, ΔMP, the difference between mean arterial and venous pressure, performed well. However, Ofe → vc reduced the optimal average time to sepsis detection after endotoxin infusion from 46.2 min for ΔMP to 11.6 min, for a slight increase in false positive rate from 1.8 to 6.2%. Thus, the novel Ofe → vc provided the best combination of specificity and sensitivity, assuming an equal weighting to both, of the metrics assessed. CONCLUSIONS Overall, the potential of these novel metrics in the detection of diagnostic shifts in physiological behaviour, here driven by sepsis, is demonstrated.
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Affiliation(s)
- Shaun Davidson
- Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
| | - Chris Pretty
- Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Joel Balmer
- Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Thomas Desaive
- GIGA-Cardiovascular Sciences, University of Liège, Liège, Belgium
| | - J Geoffrey Chase
- Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
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Shabani Varaki E, Gargiulo GD, Penkala S, Breen PP. Peripheral vascular disease assessment in the lower limb: a review of current and emerging non-invasive diagnostic methods. Biomed Eng Online 2018; 17:61. [PMID: 29751811 PMCID: PMC5948740 DOI: 10.1186/s12938-018-0494-4] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 05/02/2018] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Worldwide, at least 200 million people are affected by peripheral vascular diseases (PVDs), including peripheral arterial disease (PAD), chronic venous insufficiency (CVI) and deep vein thrombosis (DVT). The high prevalence and serious consequences of PVDs have led to the development of several diagnostic tools and clinical guidelines to assist timely diagnosis and patient management. Given the increasing number of diagnostic methods available, a comprehensive review of available technologies is timely in order to understand their limitations and direct future development effort. MAIN BODY This paper reviews the available diagnostic methods for PAD, CVI, and DVT with a focus on non-invasive modalities. Each method is critically evaluated in terms of sensitivity, specificity, accuracy, ease of use, procedure time duration, and training requirements where applicable. CONCLUSION This review emphasizes the limitations of existing methods, highlighting a latent need for the development of new non-invasive, efficient diagnostic methods. Some newly emerging technologies are identified, in particular wearable sensors, which demonstrate considerable potential to address the need for simple, cost-effective, accurate and timely diagnosis of PVDs.
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Affiliation(s)
- Elham Shabani Varaki
- The MARCS Institute for Brain, Behaviour & Development, Western Sydney University, Penrith, NSW, 2750, Australia.
| | - Gaetano D Gargiulo
- The MARCS Institute for Brain, Behaviour & Development, Western Sydney University, Penrith, NSW, 2750, Australia
| | - Stefania Penkala
- School of Science and Health, Western Sydney University, Penrith, NSW, 2750, Australia
| | - Paul P Breen
- The MARCS Institute for Brain, Behaviour & Development, Western Sydney University, Penrith, NSW, 2750, Australia.,Translational Health Research Institute, Western Sydney University, Penrith, NSW, 2750, Australia
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Gu K, Zhang Z, Gao B, Chang Y, Wan F. Hemodynamic effects of perfusion level of peripheral ECMO on cardiovascular system. Biomed Eng Online 2018; 17:59. [PMID: 29743080 PMCID: PMC5944029 DOI: 10.1186/s12938-018-0493-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 05/02/2018] [Indexed: 02/06/2023] Open
Abstract
Background Peripheral ECMO is an effective cardiopulmonary support in clinical. The perfusion level could directly influence the performances and complications. However, there are few studies on the effects of the perfusion level on hemodynamics of peripheral ECMO. Methods The geometric model of cardiovascular system with peripheral ECMO was established. The blood assist index was used to classify the perfusion level of the ECMO. The flow pattern from the aorta to the femoral artery and their branches, blood flow rate from aorta to brain and limbs, flow interface, harmonic index of blood flow, wall shear stress and oscillatory shear index were chosen to evaluate the hemodynamic effects of peripheral ECMO. Results The results demonstrated that the flow rate of aorta outlets increased and perfusion condition had been improved. And the average flow to the upper limbs and brain has a positive correlation with BAI (r = 0.037, p < 0.05), while there is a negative correlation with lower limbs (r = − 0.054, p < 0.05). The HI has negative correlation with BAI (p < 0.05, r < 0). The blood interface is further from the heart with the BAI decrease. And the average WSS has negative correlation with BAI (p < 0.05, r = − 0.983) at the bifurcation of femoral aorta and has positive correlation with BAI (p < 0.05, r = 0.99) at the inner aorta. The OSI under different BAI is higher (reaching 0.4) at the inner wall of the aortic arch, the descending aorta and the femoral access. Conclusions The pathogenesis of peripheral ECMO with different perfusion levels varies; its further research will be thorough and extensive.
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Affiliation(s)
- Kaiyun Gu
- Peking University Third Hospital, 49 North Garden Rd., Haidian District, Beijing, 100191, China.,Peking University Health Science Center, Xueyuan Rd, Haidian District, Beijing, 100083, China
| | - Zhe Zhang
- Peking University Third Hospital, 49 North Garden Rd., Haidian District, Beijing, 100191, China.
| | - Bin Gao
- College of Life Science & Bio-Engineering, Beijing University of Technology, Beijing, 100124, China
| | - Yu Chang
- College of Life Science & Bio-Engineering, Beijing University of Technology, Beijing, 100124, China.
| | - Feng Wan
- Peking University Third Hospital, 49 North Garden Rd., Haidian District, Beijing, 100191, China.,Peking University Health Science Center, Xueyuan Rd, Haidian District, Beijing, 100083, China
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Kones R, Rumana U. Cultural primer for cardiometabolic health: health disparities, structural factors, community, pathways to improvement, and clinical applications. Postgrad Med 2018; 130:200-221. [PMID: 29291669 DOI: 10.1080/00325481.2018.1421395] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The quest to optimize cardiometabolic health has created great interest in nonmedical health variables in the population, community-based research and coordination, and addressing social, ethnic, and cultural barriers. All of these may be of equal or even greater importance than classical health care delivery in achieving individual well-being. One dominant issue is health disparity - causes, methods of reduction, and community versus other levels of solutions. This communication summarizes some major views regarding social structures, followed by amplification and synthesis of central ideas in the literature. The role of community involvement, tools, and partnerships is also presented in this Primer. Recent views of how these approaches could be incorporated into cardiometabolic initiatives and strategies follow, with implications for research. Two examples comparing selected aspects of community leverage and interventions in relation to individual approaches to health care equity are examined in depth: overall performance in reducing cardiovascular risk and mortality, and the recent National Diabetes Prevention Program, both touching upon healthy diets and adherence. Finally, the potential that precision medicine offers, and possible effects on disparities are also discussed.
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Affiliation(s)
- Richard Kones
- a The Cardiometabolic Research Institute , Houston , TX , USA
| | - Umme Rumana
- a The Cardiometabolic Research Institute , Houston , TX , USA.,b University of Texas Health Science Center , Houston , TX , USA
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Silva CT, Zorkoltseva IV, Amin N, Demirkan A, van Leeuwen EM, Kors JA, van den Berg M, Stricker BH, Uitterlinden AG, Kirichenko AV, Witteman JCM, Willemsen R, Oostra BA, Axenovich TI, van Duijn CM, Isaacs A. A Combined Linkage and Exome Sequencing Analysis for Electrocardiogram Parameters in the Erasmus Rucphen Family Study. Front Genet 2016; 7:190. [PMID: 27877193 PMCID: PMC5099142 DOI: 10.3389/fgene.2016.00190] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2016] [Accepted: 10/11/2016] [Indexed: 12/30/2022] Open
Abstract
Electrocardiogram (ECG) measurements play a key role in the diagnosis and prediction of cardiac arrhythmias and sudden cardiac death. ECG parameters, such as the PR, QRS, and QT intervals, are known to be heritable and genome-wide association studies of these phenotypes have been successful in identifying common variants; however, a large proportion of the genetic variability of these traits remains to be elucidated. The aim of this study was to discover loci potentially harboring rare variants utilizing variance component linkage analysis in 1547 individuals from a large family-based study, the Erasmus Rucphen Family Study (ERF). Linked regions were further explored using exome sequencing. Five suggestive linkage peaks were identified: two for QT interval (1q24, LOD = 2.63; 2q34, LOD = 2.05), one for QRS interval (1p35, LOD = 2.52) and two for PR interval (9p22, LOD = 2.20; 14q11, LOD = 2.29). Fine-mapping using exome sequence data identified a C > G missense variant (c.713C > G, p.Ser238Cys) in the FCRL2 gene associated with QT (rs74608430; P = 2.8 × 10-4, minor allele frequency = 0.019). Heritability analysis demonstrated that the SNP explained 2.42% of the trait’s genetic variability in ERF (P = 0.02). Pathway analysis suggested that the gene is involved in cytosolic Ca2+ levels (P = 3.3 × 10-3) and AMPK stimulated fatty acid oxidation in muscle (P = 4.1 × 10-3). Look-ups in bioinformatics resources showed that expression of FCRL2 is associated with ARHGAP24 and SETBP1 expression. This finding was not replicated in the Rotterdam study. Combining the bioinformatics information with the association and linkage analyses, FCRL2 emerges as a strong candidate gene for QT interval.
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Affiliation(s)
- Claudia T Silva
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Doctoral Program in Biomedical Sciences, Universidad del RosarioBogotá, Colombia; GENIUROS Group, Genetics and Genomics Research Center CIGGUR, School of Medicine and Health Sciences, Universidad del RosarioBogotá, Colombia
| | - Irina V Zorkoltseva
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences Novosibirsk, Russia
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center Rotterdam, Netherlands
| | - Ayşe Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Department of Human Genetics, Leiden University Medical CenterLeiden, Netherlands
| | - Elisabeth M van Leeuwen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center Rotterdam, Netherlands
| | - Jan A Kors
- Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Netherlands
| | - Marten van den Berg
- Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Netherlands
| | - Bruno H Stricker
- Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Department of Internal Medicine, Erasmus University Medical CenterRotterdam, Netherlands; Inspectorate of Health CareThe Hague, Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Netherlands
| | - Anatoly V Kirichenko
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences Novosibirsk, Russia
| | | | - Rob Willemsen
- Department of Clinical Genetics, Erasmus University Medical Center Rotterdam, Netherlands
| | - Ben A Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Center for Medical Systems BiologyLeiden, Netherlands
| | - Tatiana I Axenovich
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences Novosibirsk, Russia
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Center for Medical Systems BiologyLeiden, Netherlands
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Center for Medical Systems BiologyLeiden, Netherlands
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Manivel R, Ravanan P, Meenakshisundram C, Dhanaprakasam N, Sundramoorthy SAS, Sreekumar S, Alagarsamy J, Amaladass A. Study to Predict Vascular Dysfunctions in High Risk Young Adults- An Immediate Non-Invasive Investigation to Prevent Early Vascular Ageing. J Clin Diagn Res 2015; 9:CC01-3. [PMID: 26393120 DOI: 10.7860/jcdr/2015/12358.6146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Accepted: 05/05/2015] [Indexed: 11/24/2022]
Abstract
INTRODUCTION Normal vascular is associated with gradual change of vascular structure and function, resulting in increased arterial stiffening and decreased arterial compliance. Arterial stiffness is a marker of vascular ageing and a predictor of cardiovascular events. Premature or early vascular ageing is measured by pulse wave velocity or the arterial augmentation index based on pulse wave analysis. AIM To study the predictor of vascular dysfunctions in high risk young adult offsprings of type 2 diabetes mellitus and hypertensive parents. MATERIALS AND METHODS The analytical cross-sectional studies were carried out in 90 subjects (45 males and 45 females), aged 18-25 years. They were divided into three groups based on their family history, known case of type 2 DM or hypertension in their parents. Group 1- control, Group 2- DM, Group 3-Hypertensive. In all subjects, anthropometrical data, blood pressure and peripheral pulse wave velocity were measured. One-way ANOVA was applied to determine the predictor factors of pulse wave velocity within and between groups. The following parameters were included in these analyses: age, gender, body mass index, hip waist index, heart rate, blood pressure and pulse wave velocity. RESULTS A post-test analysis revealed that peripheral pulse wave velocity (PWV), early part of systolic phase (P1) was increased significantly than later part systolic phase (P2), p-value in both diabetic and hypertensive groups were compared with control group. (p≤0.001, ANOVA) Augmentation index (P2/P1) was also increased significantly in both diabetic and hypertensive groups than control group (p≤0.001, ANOVA). CONCLUSION The findings of present study suggest that, although related, peripheral augmentation index AIx and PWV provide early identification of high risk groups. Implication of life style modification is the first intervention to consider in adults followed by drug therapy to control risk factors. Specifically, AIx might provide a more sensitive marker of arterial aging in younger individuals.
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Affiliation(s)
- Rajajeyakumar Manivel
- Assistant Professor, Department of Physiology, Chennai Medical College Hospital & Research Centre , Irungalur, Trichy, Tamil Nadu, India
| | - Pirabhu Ravanan
- Assistant Professor, Department of PSM, Government Dharmapuri Medical College , Dharmapuri, Tamil Nadu, India
| | - Chenniappan Meenakshisundram
- Consultant Cardiologist, Department of Cardiology, Ramakrishna Hospitals & Adjunct Professor, Dr.MGR. Medical University , Trichy, Tamil Nadu, India
| | - Niranjana Dhanaprakasam
- Tutor, Department of Physiology, Chennai Medical College Hospital & Research Centre , Irungalur, Trichy, Tamil Nadu, India
| | - Sivan Arul Selvan Sundramoorthy
- Assistant Professor, Department of Medicine, Chennai Medical College Hospital & Research Centre , Irungalur, Trichy, Tamil Nadu, India
| | - Sushmita Sreekumar
- Student, Department of Physiology, Chennai Medical College Hospital & Research Centre , Irungalur, Trichy, Tamil Nadu, India
| | - Janitha Alagarsamy
- Senior Medical Officer, Bharat Heavy Electricals Limited , Trichy, Tamil Nadu, India
| | - Arun Amaladass
- Tutor, Department of PSM, Chennai Medical College Hospital & Research Centre , Irungalur, Trichy, Tamil Nadu, India
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