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Velocimetry

Velociimetry is the measurement and analysis of fluid velocities, often using non-invasive optical techniques such as particle image velocimetry (PIV) and laser Doppler velocimetry (LDV).
This field of study is crucial for understanding fluid dynamics, turbulence, and the behavior of complex systems across a wide range of scientific and engineering applications, including aerodynamics, hydrodynamics, and biofluid mechanics.
Researchers in velociimetry leverage advanced instrumentation and computational methods to quantify velocity fields with high spatial and temporal resolution, enabling detailed investigations of flow phenomena.
Effective velociimetry research requires the identification and application of robust, reproducible measurement protocols, which can be facilitated by AI-driven comparisons of published methods as offered by the PubCompare.ai tool.

Most cited protocols related to «Velocimetry»

Self-reported maternal characteristics (e.g. demographics, medical, and obstetric history), and dietary and psychosocial (i.e. depression, resilience, traumatic and threatening experiences, anxiety, and perceived stress) information, are collected at the earliest prenatal visit. Anthropometry, self-reported exposure (e.g. alcohol, tobacco, marijuana, methamphetamines), and fetal physiology [e.g. heart rate (HR), heart rate variability (HRV), movement, HR-movement coupling] are collected at each prenatal visit. Biometry and Doppler ultrasound velocimetry of uterine and fetal vessels are performed for embedded study participants. Postnatal newborn and/or 1 month visits include autonomic, cardiorespiratory, cortical activity, and auditory assessments, self-reported exposure, infant care practices, infant anthropometrics, facial dysmorphology photographs, and the Amiel-Tison Neurologic Assessment at term.21 (link) At the 1 year visit, the Mullen Scales of Early Learning22 is administered to assess cognitive ability and motor development (embedded study), and infant anthropometrics and facial dysmorphology photographs are collected. Maternal (pregnancy through delivery) and infant (newborn to 1 year) charts are abstracted to obtain information regarding growth, physical exam/fetal structure, laboratory testing, medications and interventions, clinical events, co-morbidities, and diagnoses. Serious adverse events, unanticipated problems, and concomitant services are collected at each participant visit, contact, or event, and are reported according to regulatory guidelines.
Publication 2014
Anxiety Auditory Perception Blood Vessel Cannabis sativa Care, Prenatal Cognition Cortex, Cerebral Diagnosis Diet Ethanol Face Fetal Structures Infant Infant, Newborn Methamphetamine Mothers Movement Nervous System, Autonomic Neurologic Examination Obstetric Delivery Pharmaceutical Preparations Physical Examination physiology Pregnancy Rate, Heart Tobacco Products Ultrasounds, Doppler Uterus Velocimetry Verbascum
The first quantitative measurements of blood pressure were performed in animals by Hales in 1733 [24 , 25 (link)]. Early reports of intra-arterial pressure measurement in the human are from 1912, when Bleichröder [26 ] cannulated his own radial artery. It is unlikely that he recorded his BP although it would have been possible at that time: Frank developed accurate and fast manometers that could measure pulsatile pressure in 1903 [27 ]. Invasive measurement of BP was confined to the physiology labs for quite some time [28 (link), 29 (link)]. However in the 1950s and 1960s, with the development of refined insertion techniques [30 (link)] and Teflon catheters it became standard clinical practice. High fidelity catheter-tip manometers, such as used to measure pressure gradients across a coronary stenosis, were introduced by Murgo and Millar in 1972 [31 ]. Table 1 gives an overview of BP methods.

Methods for measurement of blood pressure and cardiac output

SystemMethodCompanyCOBP
NexfinFinger cuff technology/pulse contour analysisBMEYE+___+___
FinometerFinger cuff technology/pulse contour analysisFMS+___+___
LIFEGARD® ICGThoracic electrical bioimpedanceCAS Medical Systems, Inc.+___+
BioZ MonitorImpedance cardiographyCardioDynamics International Corporation+___+
Cheetah reliant“Bioreactance”Cheetah Medical+___+
Cardioscreen/NiccomoImpedance cardiography and impedance plethysmographyMedis Medizinische Messtechnik GmbH+___+
AESCULONElectrical “velocimetry”Osypka Medical GmbH+___+
HIC-4000Impedance cardiographyMicrotronics Corp Bio Imp Tech, Inc.+___
NICaSRegional impedanceNImedical+___
IQ23-dimensional impedanceNoninvasive Medical Technologies+___
ICONElectrical “velocimetry”Osypka Medical GmbH+___
PHYSIO FLOWThoracic electrical bioimpedanceManatec biomedical+___
AcQtracThoracic impedanceVäsamed+___
esCCOPulse wave transit timeNihon Kohden+___
TEBCOThoracic electrical bioimpedanceHEMO SAPIENS INC.+___
NCCOM 3Impedance cardiographyBomed Medical Manufacturing Ltd+___
RheoCardioMonitorImpedance cardiographyRheo-Graphic PTE+___
HemoSonic™ 100transesophageal DopplerArrow Critical Care Products+___
ECOMEndotracheal bioimpedanceConMed Corporation+___
CardioQ-ODM™Oesophageal DopplerDeltex+___
TECOTransesophageal DopplerMedicina+___
ODM IITransesophageal DopplerAbbott+___
HDI/PulseWave™ CR-2000Pressure waveform analysisHypertension Diagnostics, Inc+_ _+_ _
USCOM 1ATransthoracic DopplerUscom+_ _
NICORebreathing FickPhilips Respironics+
InnocorRebreathing FickInnovision A/S+
Vigileo/FloTracPulse contour analysisEdwards Lifesciences______
LiDCOplus PulseCOTranspulmonary lithium dilution/pulse contour analysisLiDCO Ltd______
PiCCO2Transpulmonary thermodilution/pulse contour analysisPULSION Medical Systems AG______
MOSTCARE PRAMPulse contour analysisVytech______
VigilancePulmonary artery catheter thermodilutionEdwards Lifesciences___
DDGDye-densitogram analyzerNihon Kohden
TruccomPulmonary artery catheter thermodilutionOmega Critical Care
COstatusUltrasound dilutionTransonic Systems Inc.+
CNAP Monitor 500Finger cuff technologyCNSystems Medizintechnik AG+___
SphygmoCor® CPV SystemApplanation tonometryAtCor Medical+_ _
TL-200 T-LINEApplanation tonometryTensys Medical, Inc.+_ _

+ noninvasive, – invasive, ___ continuous, _ _ semi-continuous, … intermittent

Practical noninvasive (intermittent) BP measurement became possible when Riva-Rocci presented his air-inflatable arm cuff connected to a manometer in 1896 [32 , 33 (link)]. By deflating the cuff and feeling for the pulse, systolic BP could be determined. In 1905 Korotkoff [34 , 35 (link)] advanced the technique further with the auscultatory method making it possible to determine diastolic pressure as well. In 1903 Cushing recommended BP monitoring using the Riva-Rocci sphygmomanometer for patients under general anesthesia [36 (link)]. Nowadays, automated assessment of BP with oscillometric devices is commonly used. These devices determine BP by analyzing the oscillations measured in the cuff-pressure. The pressure in the cuff is first brought above systolic pressure and then deflated to below diastolic pressure. Oscillations are largest when cuff pressure equals mean arterial pressure. Proprietary algorithms determine systolic and diastolic values from the oscillations. Oscillometers may be inaccurate [37 ], and provided values that are frequently lower than direct BP measurements in critically ill patients, [38 (link), 39 (link)] whereas detection of large BP changes is unreliable [40 (link)]. Due to its intermittent nature hyper- and hypotensive periods may be missed [2 (link)].
“Semi-continuous noninvasive methods” based on radial arterial tonometry require an additional arm cuff to calibrate arterial pressure [41 (link)–43 (link)]. The use of these devices may become problematic under conditions with significant patient motion or surgical manipulation of the limbs [43 (link), 44 (link)]. However, tonometry devices have contributed greatly to the knowledge of the relation between the pressure wave shape and cardiovascular function [45 (link), 46 (link)].
Publication 2012
Animals Arteries Arteries, Radial Auscultation Cardiovascular Physiological Phenomena Catheters Cheetahs Coronary Stenosis Critical Care Critical Illness Determination, Blood Pressure Diagnosis Diastole Electricity Esophagus General Anesthesia Heart Homo sapiens Lithium Manometry Medical Devices Operative Surgical Procedures Oscillometry Patients physiology Pressure Pressure, Diastolic Pulse Rate Reliance resin cement Sphygmomanometers Systole Systolic Pressure Technique, Dilution Teflon Thermodilution Tonometry Velocimetry
Women who agreed to participate were given follow-up appointments at about 20, 28, and 36 weeks' gestation in the National Institute for Health Research Cambridge Clinical Research Facility (Cambridge, UK). All research scans after the dating scan were done with a Voluson i system (GE Healthcare, Fairfield CT, USA) by one of a team of six sonographers, all of whom received standard training. All ultrasound examinations followed the same protocols as those used in the clinical service.13 , 14 (link) At the 20 week research appointment, participants were given a novel questionnaire we created to obtain details about their medical history and demographic characteristics.11 (link) The 20 week scan had both routine (review of fetal anatomy and biometric measurements) and research (uterine and umbilical artery Doppler flow velocimetry) elements. Women were informed about routine elements (any concerns about the fetal anatomy and of the fetal measurements at the 20 week scan), but women and clinicians were masked to the research elements (results of the uterine and umbilical Dopplers). At the 28 and 36 week research appointments, umbilical and uterine artery Doppler flow velocimetry were repeated, and ultrasonographic measurement of fetal biparietal diameter, head circumference, abdominal circumference, and femur length were also done using standard techniques. An estimated fetal weight (EFW) percentile was calculated by use of the Hadlock equations and reference standard.15 (link), 16 (link) Uteroplacental Dopplers, biometry, and EFW results from the research ultrasound scans at 28 and 36 weeks were not reported to the participant or the clinician. However, both were informed about incidental findings, specifically previously undiagnosed placenta praevia, severe oligohydramnios (amniotic fluid index <5), a previously undiagnosed fetal abnormality, or non-cephalic presentation at the time of the 36 week scan.
Gestational age was defined on the basis of ultrasonographic estimation at the time of the first scan, as recommended.3 Distributions of all measurements in the research scans were similar to previously reported reference cohorts (appendix). Summary statistics for reproducibility and reliability of research scans (assessed by two sonographers, scanning the same woman twice at the same appointment, each masked to the results of the other's scan) are tabulated for 45 women at 20 weeks' gestation and 44 women at 36 weeks' gestation (appendix). Coefficients of variation were less than 5% for fetal biometry and EFW, and between 5% and 10% for uteroplacental Doppler at both timepoints.
Women were selected for additional, clinically indicated scans in the third trimester of pregnancy as per routine clinical care, using local and national guidelines (eg, the NICE Guidelines on low risk women,3 women with diabetes,17 and women with hypertensive disorders18 ). Women were also screened with serial measurement of the symphyseal-fundal height. All women carried their maternity notes, which included a chart of the normal range of measurements for fetuses in relation to gestational age. Referral for an ultrasound scan was made by the midwife or doctor providing clinical care. Results of all clinically indicated scans were reported and paper copies were filed in both the participant's hand-held notes and hospital case records.
Screening status in relation to EFW was classified on the basis of the last scan before birth (which could be the 28 week scan or the 36 week scan for universal ultrasonography, depending on the gestational age at delivery). Screen positive was defined as an EFW less than the 10th percentile, using an externally derived reference range15 (link), 16 (link) (for both selective and universal ultrasonography). Screen negative was defined as an EFW of the 10th percentile or more (both selective and universal ultrasonography), or if no clinically indicated scan had been done at gestational age of 26 weeks or later (only selective ultrasonography).
Publication 2015
Abdomen ARID1A protein, human Care, Prenatal Childbirth Congenital Abnormality Diabetes Mellitus Femur Fetal Weight Fetus Gestational Age Head Midwife Obstetric Delivery Oligohydramnios Physical Examination Physicians Placenta Previa Pregnancy Radionuclide Imaging Ultrasonography Umbilical Arteries Umbilicus Uterine Arteries Uterus Velocimetry Woman
For traction force measurements, cells seeded on gels were placed on an inverted microscope (Nikon Eclipse Ti). Single cells were tracked for 12 h, while we acquired phase contrast images of the cells and fluorescence images of the embedded nanobeads using a 40x objective. Then, cells were trypsinized and an image of bead position in the relaxed state of the gel was acquired. By comparing bead positions with and without cells, a map of gel deformations caused by cells was first obtained using custom particle imaging velocimetry software15 . Then, after assuming that gel displacements were caused by forces exerted by cells in the cell-gel contact area, the corresponding map of cell forces was calculated using a previously described Fourier transform algorithm16 (link), 29 (link). The average forces per unit area exerted by each cell were then calculated. Force measurements for each cell were taken each hour during the measurement, and the average value for all time measurements was used. Total strain energy exerted by the cells was calculated by performing a scalar product between gel displacement and force for each pixel in the force map, and then adding the result for the entire traction map. Phase contrast images were also used to calculate average cell spreading areas as a function of substrate stiffness.
Publication 2014
Cells Fluorescence Microscopy Microscopy, Phase-Contrast Strains Traction Velocimetry

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Publication 2017
Heart Heart Valves Hemodynamics physiology Pressure Sinus, Aortic Velocimetry

Most recents protocols related to «Velocimetry»

The flow around healthy Cassiopea sp. was imaged using the Particle Image Velocimetry (PIV) methods from3 (link), such that both the incurrent and excurrent flow of the feeding current could be observed. The imaging setup consisted of a 45 × 45 × 45 cm aquarium, filled with artificial seawater. The water was seeded using 10 μm reflective hollow glass spheres for particle image velocimetry (PIV). An Edgertronic high-speed camera filming at 50 frames per second provided a field of view ca. 30 × 30 cm. Two 2-W continuous wave DPSS lasers (wavelength = 520 nm), spread through cylindrical lenses to produce narrow light sheets, were staggered one above the other to illuminate a single coronal plane across the entire field of view. One jellyfish at a time (n = 9) was placed on the bottom in the center of the aquarium, such that the laser sheet crossed the center of the animal. After allowing it to settle for about 10 min, 30 s of video were recorded at 50 frames per second. Analysis using the LaVision software package produced a PIV time-average over the 30 s. PIV was processed with interrogation windows between 48 and 64 pixels, at 50% overlap.
Publication 2023
Animals Continuous Wave Lasers Lens, Crystalline Light Reading Frames Velocimetry
Time-lapse light microscopic images were taken using established protocols [26 ]. In short, glioblastoma cells were plated on PA gels overnight before imaging, Mayo cells were plated on laminin coated PA gels with media containing 2% serum to promote adhesion, and UCSD cells were plated on Matrigel coated PA gels without serum. Time-lapse phase-contrast images were taken for 10 h to track cell migration using a Nikon Eclipse TE200 microscope with a Plan Fluor 10 × /0.30NA objective. Time-lapse phase-contrast images were taken for 3 min to measure F-actin flow using a Nikon Eclipse TE200 microscope with a Plan Fluor ELWD 40 × /0.60NA objective. Phase-contrast and epifluorescence images were taken before and after glioblastoma cells detached by treating with 0.05% trypsin to determine the cell traction using a Nikon Eclipse TE200 microscope with a Plan Fluor ELWD 40 × /0.60NA objective with a PhotoFluor II light source (89 North) and a mCherry/EGFP filter set.
Random motility coefficients (RMCs) of cell migration and cell area and aspect ratio were determined based on established protocols [26 ]. In short, cell position and region in 10-h time-lapse images were tracked using a custom MATLAB code. The RMC of an individual cell was derived based on the mean squared displacement in the 2D diffusion equation described in Bangasser et al., 2017 [26 ]. The cell area and aspect ratio were calculated based on the recorded cell region. RMCs were measured for Mayo MES (Mayo 16(70), 46(90), 59(90)), PN (Mayo 64(100), 80(150), 85 (100)), CL(Mayo 6(50), 38(50), 76(50), 91 (50), 195 (30)) cells and UCSD MES (380), PN (180) cells on PA gels of 0.7, 4.6, 9.3, 19.5 kPa.
Actin retrograde flow of an individual cell was calculated based on established protocols [26 ]. Briefly, kymographs were made along the axis of moving protrusion features for 3-min time lapse images and actin flow was measured by analyzing the kymograph using a custom MATLAB code. Actin flow was measured for Mayo MES (Mayo 16(80), 46(50), 59(100)), PN (Mayo 64(130), 80(120), 85 (170)), CL(Mayo 6(80), 38(60), 76(60), 91(60), 195 (90)) cells and UCSD MES (250), PN (100) cells on PA gels of 0.7, 4.6, 9.3, 19.5 kPa.
Cell traction strain energy was determined using the established protocols based on the Fourier Transform Traction Cytometry [26 ]. Briefly, epifluorescence images before and after cells were detached were registered, aligned, and transformed using a custom MATLAB code. A gel displacement field was calculated by applying particle image velocimetry to the fluorospheres within the aligned epifluorescence images. The traction stress field was calculated using the Fourier Transform Traction Cytometry, and the total traction strain energy was calculated based on the dot products of the traction vectors and the displacement vectors. Strain energy was measured for Mayo MES (Mayo 16(40), 46(30), 59(40)), PN (Mayo 64(50), 80(30), 85 (50)), CL(Mayo 6(30), 38(30), 76(30), 91 (20), 195 (40)) cells and UCSD MES (100), PN (70) cells on PA gels of 0.7, 4.6, 9.3, 19.5 kPa.
Publication Preprint 2023
Actins Cells Cloning Vectors Cultured Cells Diffusion Epistropheus F-Actin Gels Glioblastoma Kymography Laminin Light Light Microscopy matrigel Microscopy Microscopy, Phase-Contrast Migration, Cell Motility, Cell Serum Strains Temporal Lobe Traction Trypsin Velocimetry
Raw laser speckle images can be analyzed with temporal autocorrelation to find the decorrelation time and the corresponding velocity. According to established mathematical model [40] , the laser speckle intensity autocorrelation function g2τ and the intensity decorrelation time τc can be related directly as g2τ=1+βeτ/τcn2, where β is the correction factor associated with the illumination geometry and n depends on the light scattering regime and motion types of the light scatterers. As the scattered light from the transparent sample was dominated by single scattering, we chose n=1 in this study. The movement velocity can be converted from the decorrelation time τc using the formula v=λπ*NA*τc, where λ is the laser source wavelength, and NA is the numerical aperture of the detection (imaging) objective. Autocorrelation was performed on the image intensity pixel by pixel, with a moving time window [41] that typically covered 20 frames.
Particle Image Velocimetry (PIV) is a velocity measurement technique, which calculates a displacement vector for each interrogation window in the FOV with the aid of autocorrelation or cross-correlation techniques. PIVlab is a user-friendly, graphical user interface (GUI) based digital particle image velocimetry software embedded in Matlab [42] . In this study, we applied PIV analysis on raw speckle images to identify the local moving direction of scatterers. More specifically, we used PIVlab to generate vector velocity maps.
Publication 2023
Cloning Vectors Light Microtubule-Associated Proteins Movement Reading Frames Velocimetry
The subjects enrolled in this study were recruited from the endocrinology department of Wuhan Union Hospital from January 2019 to December 2019. This study has been approved by the Institutional Research Ethics Committee of Union Hospital, Huazhong University of Science and Technology. A prior written informed consent was obtained from each participant in this study. The subjects were dividedinto three groups: normal control (NC group, n=43), diabetes without cardiovascular diseases (DM group, n=60), and diabetes with cardiovascular diseases (CVD group, n=51). The inclusion criteria of subjects in the NC group were: no history of diabetes or cardiovascular diseases, normal glucose tolerance in OGTT, normal coronary angiography, no history of carotid artery disease or peripheral arterial disease. Diabetes were diagnosed according to the World Health Organization (WHO, 1999) (18 (link)). Data on vital signs, anthropometric factors, medical history and behaviors as well as physical activity were collected. Additional data, including weight, height, BMI, waist circumference, hip circumference, glycemia and glycated hemoglobin were obtained for each individual. Diabetes patients in CVD group were evidenced as follows: ischemic heart disease defined by clinical history, and/or ischemic electrocardiographic alterations; peripheral vascular disease including atherosclerosis obliterans and cerebrovascular disease based on history, physical examinations and Doppler velocimetry.
Publication 2023
Atherosclerosis Cardiovascular Diseases Carotid Artery Diseases Cerebrovascular Disorders Coronary Angiography Coronary Arteriosclerosis Diabetes Mellitus Electrocardiography Glucose Hemoglobin, Glycosylated Immune Tolerance Institutional Ethics Committees Oral Glucose Tolerance Test Patients Peripheral Arterial Diseases Peripheral Vascular Diseases Physical Examination Signs, Vital System, Endocrine Velocimetry Waist Circumference
Image sequences taken by the time-lapse method are used for migration analysis. To determine the velocity and direction of migration in each cell, we need to determine the center coordinate of the cell. The way to determine the center coordinate in the previous study is to calculate the best-fit ellipsis or center of gravity from the cell contour [30 (link),31 (link),32 (link)]. However, there are two difficulties in yielding the cell contour automatically using a DIC image. One is setting the contour in the unclear part of the cell, and the other is setting the border of the connected cell. To overcome these obstacles, the gravity center of the nucleus fluorescent area was used as the center coordinate of the cell in this study.
The custom algorithm was developed by written python for cell tracing. First, the fluorescence image of the nucleus was binarized, and the noise was removed by filtering the area of fluorescence. To link the cell in each image, a particle tracking velocimetry (PTV) method, one of the velocity vector analysis methods, was applied. In the PTV method, when the flame rate of the camera is high enough compared with a particle velocity in the fluid, a velocity vector of a luminescent particle can be obtained by only linking the closest luminescent particle. In this study, the position of the center of gravity of the fluorescent region of the nucleus was treated in the same way as the luminescent particles in the PTV method, and the vector data of the cells were analyzed and used to explain cell migration (Figure 8a). The flame rate of the cell migration in this study was four images/hour, which was high enough compared with the scale of cell migration.
The vector data of cells were sorted in four directions as shown in Figure 8b, and then, the numbers of cells in each direction and the total number of cells were counted. The migration ratio of cells was obtained by dividing the cell count in one direction by the total cell count in all directions. The average velocity in each direction was also calculated from vector data of cells. Migration direction and the average velocity of cells were regarded to be the characteristics of cell migration.
To ensure the accuracy of the PTV method, vector data of cells were also obtained by manually tracing the coordinate of the nucleus gravity center and were used as a comparison target. This manual analysis method is called a manual method in this study.
Publication 2023
Cell Nucleus Cells Cerebellar Nuclei Cloning Vectors Fluorescence Gravity Luminescence Luminescent Measurements Migration, Cell Python Velocimetry

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More about "Velocimetry"

Velocimetry is the measurement and analysis of fluid velocities, often utilizing non-invasive optical techniques such as particle image velocimetry (PIV) and laser Doppler velocimetry (LDV).
This field of study, also known as flow visualization or fluid dynamics analysis, is crucial for understanding the behavior of complex systems across a wide range of scientific and engineering applications, including aerodynamics, hydrodynamics, and biofluid mechanics.
Researchers in this field leverage advanced instrumentation, such as MATLAB, DaVis 7.2, Zetasizer Nano ZS, Vevo 770, Fastcam SA3, Eclipse Ti, and TransFluoSpheres, as well as computational methods, to quantify velocity fields with high spatial and temporal resolution, enabling detailed investigations of flow phenomena.
Effective velocimetry research requires the identification and application of robust, reproducible measurement protocols, which can be facilitated by AI-driven comparisons of published methods, as offered by the PubCompare.ai tool.
This powerful tool can help researchers improve their research outcomes by easily locating the best protocols from literature, pre-prints, and patents, while leveraging AI to identify the most reproducible and accurate methods.