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Physiological Measurement

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https://www.readbyqxmd.com/read/30215614/effect-of-abdominal-aortic-endoprostheses-on-arterial-pulse-wave-velocity-in-an-in-vitro-abdominal-aortic-flow-model
#1
Kim van Noort, Suzanne Holewijn, Richte C L Schuurmann, Johannes T Boersen, Simon P Overeem, Erik Groot Jebbink, Jenske J M Vermeulen, Michel M P J Reijnen, Cornelis H Slump, Jean-Paul P M de Vries
Aortic pulse-wave-velocity (aPWV) is a measure for arterial stiffness, which is associated with increased cardiovascular risk. Recent evidence suggests aPWV increases after endograft-placement for aortic aneurysms. The aim of this study was to investigate the influence of different aortic endoprostheses on aPWV and structural stiffness in vitro. 
 Approach: Three different abdominal aortic endoprostheses (AFX, Endurant II, and Nellix) were implanted in identical silicone aneurysm models. One model was left untreated, and another model contained an aortic tube graft (Gelweave)...
September 14, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30211696/an-investigation-into-setting-the-blood-flow-restriction-pressure-based-on-perception-of-tightness
#2
Zachary W Bell, Scott J Dankel, Kevin T Mattocks, Samuel L Buckner, Matthew B Jessee, J Grant Mouser, Takashi Abe, Jeremy P Loenneke
OBJECTIVE: To determine whether the perceived tightness scale could be used to set sub-occlusive blood flow restriction pressures. A secondary aim was to determine variables that may impact individual ratings. APPROACH: One hundred and twenty participants completed three separate conditions in one limb within the upper and lower body. Participants were asked to rate their perceived tightness for two of the three conditions, regarded as moderate pressure without pain (7/10) and intense pressure with pain (10/10)...
September 13, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30211688/cardiac-anomaly-detection-based-on-time-and-frequency-domain-features-using-tree-based-classifiers
#3
Martin Kropf, Dieter Hayn, Daniel-Armando Morris, Aravind-Kumar Radhakrishnan, Evgeny Belyavskiy, Athanasios Frydas, Elisabeth Pieske-Kraigher, Burkert Pieske, Günter Schreier

 Recent advantages in mHealth-enabled ECG recorders boosted the demand for algorithms, which are able to automatically detect cardiac anomalies with high accuracy. 
 Approach:
 We present a combined method of classical signal analysis and machine learning which has been developed during the Computing in Cardiology Challenge (CinC) 2017. Almost 400 hand-crafted features have been developed to reflect the complex physiology of cardiac arrhythmias and their appearance in single-channel ECG recordings...
September 13, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30207986/comparison-between-probabilistic-and-wiener-granger-causality-in-assessing-modifications-of-the-cardiac-baroreflex-control-with-age
#4
Alberto Porta, Vlasta Bari, Beatrice De Maria, Beatrice Cairo, Emanuele Vaini, Natália Maria Perseguini, Juliana Milan-Mattos, Patricia Rehder-Santos, Vinícius Minatel, Anielle C M Takahashi, Aparecida Maria Catai
BACKGROUND: Probabilistic causality (PC) is a framework checking that the occurrence of a cause raises the probability of the effect by comparing the probability of the effect conditioned and unconditioned to the cause. Even though less frequently utilized with respect to the more traditional model-based Wiener-Granger causality (WGC) based on the predictability improvement of an effect resulting from the inclusion of the presumed cause in the multivariate linear regression model, PC has the advantage to be model-free...
September 12, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30207983/threshold-based-fall-detection-using-the-hybrid-of-tri-axial-accelerometer-and-gyroscope
#5
Fu-Tai Wang, Hsiao-Lung Chan, Ming-Hung Hsu, Cheng-Kuan Lin, Pei-Kuang Chao, Ya-Ju Chang
OBJECTIVE: Falling is an important health maintenance issue for the elderly and people with movement disorders, strokes and multiple sclerosis. With the development of light, low-cost wearable technology, inertia-based fall detection has gained much attention. However, some large movements, such as jumping and postural changes, are frequently confounded with falls. For example, commonly used fall detection methods based on acceleration amplitude produce a large number of false alerts unless they are combined with post-fall posture identification...
September 12, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30207981/machine-learning-for-intraoperative-prediction-of-viability-in-ischemic-small-intestine
#6
Runar James Strand-Amundsen, Christian Tronstad, Henrik Mikael Reims, Finn P Reinholt, Jan Olav Hogetveit, Tor Inge Tønnessen
OBJECTIVE: Evaluation of intestinal viability is essential in surgical decision-making in patients with acute intestinal ischemia. There has been no substantial change in the mortality rate (30-93%) of patients with acute mesenteric ischemia (AMI) since the 1980's. As the accuracy from the first laparotomy alone is 50%, the gold standard is a second-look laparotomy, increasing the accuracy to 87-89%. This study investigates the use of machine learning to classify intestinal viability and histological grading in pig jejunum, based on multivariate time-series of bioimpedance sensor data...
September 12, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30199376/an-open-source-benchmarked-toolbox-for-cardiovascular-waveform-and-interval-analysis
#7
Adriana Nicholson Vest, Qiao Li, Chengyu Liu, Shamim Nemati, Giulia Da Poian, Amit J Shah, Gari D Clifford
Variability metrics hold promise as potential indicators for autonomic function, prediction of adverse cardiovascular outcomes, psychophysiological status, and general wellness. Although the investigation of heart rate variability (HRV) has been prevalent for several decades, the methods used for preprocessing, windowing, and choosing appropriate parameters lacks consensus among academic and clinical investigators. Moreover, many of the important steps are omitted from publications, preventing reproducibility...
September 10, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30192235/wave-intensity-analysis-in-the-internal-carotid-artery-of-hypertensive-subjects-using-phase-contrast-mr-angiography-and-preliminary-assessment-of-the-effect-of-vessel-morphology-on-wave-dynamics
#8
Sandra Neumann, Froso Sophocleous, Matthew D Kobetić, Emma C Hart, Angus K Nightingale, Kim H Parker, Mark K Hamilton, Giovanni Biglino
Objective
 Hypertension is associated with reduced cerebral blood flow, but it is not known how this impacts on wave dynamics or potentially relates to arterial morphology. Given the location of the internal carotid artery (ICA) and risks associated with invasive measurements, wave dynamics in this artery have not been extensively assessed in vivo. This study explores the feasibility of studying wave dynamics in the internal carotid artery non-invasively. 
 
 Approach
 Normotensive, uncontrolled and controlled hypertensive participants were recruited (daytime ambulatory blood pressure <135/85mmHg and >135/85mmHg, respectively; n=38)...
September 7, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30187894/detection-of-atrial-fibrillation-from-ecg-recordings-using-decision-tree-ensemble-with-multi-level-features
#9
Minggang Shao, Guangyu Bin, Shuicai Wu, Guanghong Bin, Jiao Huang, Zhuhuang Zhou
Detecting atrial fibrillation (AF) from electrocardiogram (ECG) recordings remains a challenging task. In this paper, a new AF detection method was proposed to classify the ECG recordings into one of four classes: Normal rhythm, AF, Other rhythm, and Noisy recordings. The proposed method comprised preprocessing, feature extraction, and classification. In preprocessing, R-peaks were detected, and RR intervals and delta RR intervals were extracted. In feature extraction, thirty multi-level features were extracted, including AF features (n=4), morphology features (n=20), RR interval features (n=2), and features of similarity index between beats (n=4)...
September 6, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30187892/an-svm-approach-for-identifying-atrial-fibrillation
#10
Vadim Gliner, Yael Yaniv
We designed an automated algorithm to classify short electrocardiogram (ECG) strips into 4 categories: normal rhythm, atrial fibrillation, noisy segment, or other rhythm disturbances. The algorithm is based on identification of the R peak and recognition of the other ECG waves. Time-frequency domain features, the average and variability of the intra-beat temporal interval, and the average beat morphology were also calculated. These features (61 features at all) were the input to a support vector machine (SVM) with and without a feed-forward 2-layer neural network consisting of 20 neurons trained on an annotated database...
September 6, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30183685/classification-of-short-single-lead-electrocardiograms-ecgs-for-atrial-fibrillation-detection-using-piecewise-linear-spline-and-xgboost
#11
Yao Chen, Xiao Wang, Yonghan Jung, Vida Abedi, Ramin Zand, Marvi Bikak, Mohammad Adibuzzaman
Detection of atrial fibrillation (AF) is important for risk stratification of stroke. We developed a novel methodology to classify the electrocardiograms (ECGs) to normal, atrial fibrillation and other cardiac dysrhythmias as defined by the Physionet Challenge 2017. More specifically, we used piecewise linear splines for the feature selection and a gradient boosting algorithm for the classifier. In the algorithm, the ECG waveform is fitted by a piecewise linear spline, and morphological features related to the piecewise linear spline coefficients are extracted...
September 5, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30183682/reply-to-comment-on-new-photoplethysmogram-indicators-for-improving-cuffless-and-continuous-blood-pressure-estimation-accuracy
#12
Wan-Hua Lin, Oluwarotimi Williams Samuel, Guanglin Li
We appreciated Helmond & Joseph's interests and comments on our previous paper. In the Comment, they discussed in detail the physiology underlying the pulse arrive time (PAT) based methods for blood pressure (BP) measurement, and concluded that there are inherent physiological reasons precluding the development of an accurate continuous cuffless BP measurement using PAT-based methods. We could agree on the comments of Helmond & Joseph about the physiology underlying PAT-based methods for BP measurement...
September 5, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30183680/detection-of-acute-periodontal-pain-from-physiological-signals
#13
Daniel Teichmann, Jan Klopp, Alexander Hallmann, Katharina Andrea Schuett, Stefan Wolfart, Maren Teichmann

 To investigate the feasibility of the detection of brief orofacial pain sensations from easily recordable physiological signals by means of machine learning techniques. 
 Approach:
 A total of 47 subjects underwent periodontal probing and indicated each instance of pain perception by means of a push button. Simultaneously, physiological signals were recorded and subsequently, autonomic indices were computed. By using the autonomic indices as input features of a classifier, a pain indicator based on fusion of the various autonomic mechanisms was achieved...
September 5, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30183678/characterization-and-reduction-of-exercise-based-motion-influence-on-heart-rate-variability-using-accelerator-signals-and-channel-decoding-in-the-time-frequency-domain
#14
Iman Alikhani, Kai Noponen, Arto Hautala, Tapio Seppänen
Heart rate variability (HRV) is defined as the variation of heart's beat to beat time intervals. Although HRV has been studied for decades, its response to stress tests and off-rest measurements is still open to controversy. In this paper, we studied the influence of motion on HRV throughout different exercise tests, including a maximal running of healthy recreational runners, cycling and walking tests of healthy subjects. In our proposed method, we utilize the motion trajectory (which is known to exist partially in HRV) measured by a three-channel accelerator (ACC) and estimate their share in HRV, derived from a wearable electrocardiography (ECG), in an error correcting problem formulation...
September 5, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30183676/changes-in-f-wave-characteristics-during-cryoballoon-catheter-ablation
#15
Mikael Henriksson, Arcadi Garcıa-Alberola, Rebeca Goya, Alba Vadillo, Francisco-Manuel Melgarejo-Meseguer, Frida Sandberg, Leif Sörnmo
Changes in ECG-derived parameters are studied in atrial fibrillation (AF) patients undergoing cryoballoon catheter ablation. 
 Approach: Parameters characterizing f-wave frequency, morphology by phase dispersion, and amplitude are estimated using a model-based statistical approach. These parameters are studied before, during, and after ablation, as well as for AF type (paroxysmal/persistent). Seventy-seven (49/28 paroxysmal/persistent) AF patients undergoing de novo catheter ablation are included in the study, out of which 31 (16/15 paroxysmal/persistent) were in AF during the whole procedure...
September 5, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30183675/adaptive-template-matching-of-photoplethysmogram-pulses-to-detect-motion-artefact
#16
Pooi Khoon Lim, Siew-Cheok Ng, Nigel H Lovell, Yong Poh Yu, Maw Pin Tan, Devin McCombie, Einly Lim, Stephen J Redmond
The photoplethysmography (PPG) signal, commonly used in the health care settings, is easily affected by movement artifact leading to errors in the extracted heart rate and SpO2 estimates. This study aims to develop an online artifact detection system based on adaptive (dynamic) template matching, suitable for continuous PPG monitoring during daily living activities and in the intensive care units (ICU). 
 
 Approach: Several master templates are initially generated by applying principal component analysis to data obtained from the Physionet MIMIC II database...
September 5, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30183673/dynamic-signal-quality-index-for-electrocardiograms
#17
Negin Yaghmaie, Mohammad Ali Maddah-Ali, Herbert F Jelinek, Faezeh Marzbanrad
The advent of telehealth applications and remote patient monitoring has led to an increasing need for continuous signal quality monitoring to ensure high diagnostic accuracy of the recordings. Cardiovascular diseases often manifest electrophysiological anomalies, therefore the Electrocardiogram (ECG) is one of the most used signals for diagnostic applications. Various types of noise and artifacts are not uncommon in ECG recordings and assessing the quality of the signal is essential prior to any clinical interpretation...
September 5, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30183671/comment-on-new-photoplethysmogram-indicators-for-improving-cuffless-and-continuous-blood-pressure-estimation-accuracy
#18
Noud van Helmond, Jeffrey I Joseph
N/A.
September 5, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30129925/chromatic-techniques-for-in-vivo-monitoring-jaundice-in-neonate-tissues
#19
Amr T Sufian, Gordon R Jones, Hameed M Shabeer, Ezzaldeen Y Elzagzoug, Joseph W Spencer
A chromatic method is described for providing a preliminary indication of unacceptable bilirubin levels in a newly born baby in order to avoid the development of serious mental deficiencies. The aim was to investigate the reliability of a new chromatic approach using a novel template unit for a preliminary, non-invasive monitoring of the skin tissue of newly born babies with jaundice and its capability for use with different mobile phone cameras. A description of the monitoring system is given along with an explanation of the monitoring technique used...
August 21, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30117811/prediction-of-obstructive-sleep-apnea-using-facial-landmarks
#20
Asghar Tabatabaei Balaei, Kate Sutherland, Peter Cistulli, Philip de Chazal
Collapsibility of the upper airway has a known anatomical basis that is mediated by an interaction of obesity and craniofacial abnormalities. The pattern of these abnormalities, if detected in a subject's facial image, can help predict the presence of obstructive sleep apnea (OSA). 
 We utilized facial photographs (front and profile) from 376 patients who had undergone an overnight polysomnogram to identify those with and without OSA. 
 Processing the images had 3 steps: landmark identification, feature generation, and automatic classification...
August 17, 2018: Physiological Measurement
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