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Physiological Measurement

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https://www.readbyqxmd.com/read/28737503/directional-connectivity-in-the-eeg-is-able-to-discriminate-wakefulness-from-nrem-sleep
#1
Giulia Lioi, Steven L Bell, David C Smith, David M Simpson
A reliable measure of consciousness is of great interest for various clinical applications including sleep studies and the assessment of depth of anaesthesia. A number of measures of consciousness based on the EEG have been proposed in the literature and tested in studies of dreamless sleep, general anaesthesia and disorders of consciousness. However, reliability has remained a persistent challenge. Despite considerable theoretical and experimental effort, the neural mechanisms underlying consciousness remain unclear, but connectivity between brain regions is thought to be disrupted, impairing information flow...
July 24, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28721951/recording-characteristics-of-electrical-impedance-myography-needle-electrodes
#2
Hyeuknam Kwon, Seward B Rutkove, Benjamin Sanchez
OBJECTIVE: The neurology and physiatry community need improved tools for the evaluation of skeletal muscle condition. Here, we evaluate needle electrical impedance myography (EIM), a new minimally invasive approach to determine muscle status that could ultimately become a bedside tool for the assessment of neuromuscular disorders. APPROACH: We design and study the recording characteristics of tetrapolar EIM needle electrodes combining theory and finite element model simulations...
July 19, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28714853/unveiling-the-development-of-intracranial-injury-using-dynamic-brain-eit-an-evaluation-of-current-reconstruction-algorithms
#3
Haoting Li, Rongqing Chen, Canhua Xu, Benyuan Liu, Mengxing Tang, Lin Yang, Xiuzhen Dong, Feng Fu
Dynamic brain EIT is a promising technique for continuous monitoring the development of cerebral injury. While there are many reconstruction algorithms available to brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address the problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution were developed...
July 17, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28696334/recent-advances-in-heart-sound-analysis
#4
Gari D Clifford, Chengyu Liu, Benjamin E Moody, José Millet Roig, Samuel E Schmidt, Qiao Li, Ikaro Silva, Roger G Mark
Heart sounds have been widely studied and have been demonstrated to have value for detecting pathologies in clinical applications. Over the last few decades, the use of heart sound signals has become increasingly uncommon and its practice in modern medicine somewhat diminished, although research into automated analysis has continued. Unfortunately, a comparative analyses of algorithms in the literature have been hindered by the lack of high-quality, rigorously validated, and standardized open databases of heart sound recordings...
July 11, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28671872/camera-based-assessment-of-arterial-stiffness-and-wave-reflection-parameters-from-neck-micro-motion
#5
Andreia Vieira Moço, Luis Albert Zavala Mondragon, Wenjin Wang, Sander Stuijk, Gerard de Haan
The feasibility of camera-based extraction of the carotid distension waveforms offers the prospect of a user-friendly alternative to Laser Doppler Velocimetry (LDV) or accelerometry-based systems. Upon supplementary calibration of vessel wall displacement to arterial pressure, our system may also be an appealing alternative to applanation tonometry for extracting cardiac-related features from the central pulse pressure waveform. This paper describes the application of camera-based micro-motion imaging to extract health-related features from the contour of the carotid displacement waveform...
July 3, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28671554/a-machine-learning-based-analysis-for-the-recognition-of-progressive-central-hypovolemia
#6
Frank Cornelis Bennis, Björn Van der Ster, Johannes Van Lieshout, Peter Andriessen, Tammo Delhaas
Traditional patient monitoring during surgery include heart rate (HR), blood pressure (BP) and peripheral oxygen saturation. However, their use as predictors for central hypovolemia is limited, which may lead to cerebral hypoperfusion. The aim of this study was to develop a monitoring model that can indicate a decrease in central blood volume (CBV) in an early stage. Approach: Twenty-eight healthy subjects (age 18-50 yr) were included. Lower body negative pressure (-50 mmHg) was applied to induce central hypovolemia until onset of pre-syncope...
July 3, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28665293/an-original-piecewise-model-for-computing-energy-expenditure-from-accelerometer-and-heart-rate-signals
#7
Hector Manuel Romero-Ugalde, Mael Garnotel, Maeva Doron, Pierre Jallon, Guillaume Charpentier, Sylvia Franc, Erik Huneker, Chantal Simon, Stephane Bonnet
Activity Energy Expenditure (EE) plays an important role in healthcare, therefore, accurate EE measures are required. Currently available reference EE acquisition methods, such as doubly labeled water and indirect calorimetry, are complex, expensive, uncomfortable, and/or difficult to apply on real time. To overcome these drawbacks, the goal of this paper is to propose a model for computing EE in real time (minute-by-minute) from heart rate and accelerometer signals. Approach: The proposed model, which consists of an original branched model, uses heart rate signals for computing EE on moderate to vigorous physical activities and a linear combination of heart rate and counts per minute for computing EE on light to moderate physical activities...
June 30, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28654423/daily-wrist-activity-classification-using-a-smart-band
#8
Nhan Duc Nguyen, Phuc Huu Truong, Gu-Min Jeong
In this letter, we propose a novel method for classifying daily wrist activities by using a smart band. Triaxial acceleration data are collected by built-in sensors of the smart band during experiments regarding five activities, i.e., texting, calling, placing a hand in a pocket, carrying a suitcase, and swinging a hand. We analyze patterns in the sensor signals during these activities based on three types of features, i.e., norm, norm-variance, and frequency-domain features. After extracting the significant features, a multi-class support vector machine (SVM) algorithm is applied to classify these activities...
June 27, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28632138/monitoring-lung-contusion-in-a-porcine-polytrauma-model-using-eit-an-application-study
#9
Susana Aguiar Santos, Carlos Castelar Wembers, Klemens Horst, Roman Pfeifer, Tim-Philipp Simon, Hans-Christoph Pape, Frank Hildebrand, Michael Czaplik, Steffen Leonhardt, Daniel Teichmann
Lung contusion is the most common lung injury following blunt chest trauma which, in turn, is associated with high mortality rates (Gavelli et al., 2002). Lung contusion is characterized by hemorrhage and edema with consecutively reduced compliance. In this study, unilateral lung contusion and other traumata were induced in 12 pigs by using a bolt gun machine. To investigate the pathophysiological consequences of lung contusion, information on clinical parameters was collected and monitored regularly while animals were additionally monitored with electrical impedance tomography (EIT) before trauma, and at 4, 24, 48 and 72 h after polytrauma...
June 20, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28613208/ensemble-methods-with-outliers-for-phonocardiogram-classification
#10
Masun Nabhan Homsi, Philip Warrick
Heart sound classification and analysis play an important role in early diagnosis and prevention of cardiovascular disease. To this end, this paper introduces a novel method for automatic classification of normal and abnormal heart sound recordings. Signals are first preprocessed to extract a total of 131 features in time, frequency, wavelet and statistical domains from the entire signal and from the timings of the states. Outlier signals are then detected and separated from those with a standard range using interquartile range algorithm...
June 14, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28607221/vastus-lateralis-and-rectus-femoris-echo-intensity-fail-to-reflect-knee-extensor-specific-tension-in-middle-school-boys
#11
Jacob Mota, Matt S Stock, Brennan Thompson
The potential dissociation between muscle strength and size has led to interest in the ability to assess muscle quality across the lifespan. We examined the association between echo intensity and specific tension in middle-school boys. Twenty-five boys participated in this study. Sixteen (mean ± SD age = 12 ± 1 years) engaged in a 16-week after-school strength and conditioning program. Nine boys (12 ± 1 years) served as controls. The program involved two, 90 minute sessions per week of lower-body speed, power, and resistance training...
June 13, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28604356/ocular-surface-temperature-in-patients-with-evaporative-and-aqueous-deficient-dry-eyes-a-thermographic-approach
#12
Sara Matteoli, Eleonora Favuzza, Lucrezia Mazzantini, Pasquale Aragona, Stefania Cappelli, Andrea Corvi, Rita Mencucci
In recent decades infrared thermography (IR) has allowed accurate and quantitative measurements of the ocular surface temperature (OST), applying a non-invasive procedure. The objective of this work was to develop a procedure based on IR, which allows characterizing the cooling of the ocular surface of patients suffering from dry eye syndrome, and distinguishing among patients suffering from aqueous deficient dry eye (ADDE) and evaporative dry eyes (EDE). Approach: All patients examined (34F/4M, 23-84 years) were divided into two groups according to their Schirmer I result (≤7 mm for ADDE and >7 mm for EDE), and the OST was recorded for 7 s at 30Hz...
June 12, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28594641/detection-of-pathological-heart-sounds
#13
Mostafa Abdollahpur, Ali Ghaffari, Shadi Ghiasi, Mohammad Javad Mollakazemi
Heart sound analysis has been a major topic of research during the past few decades. However, necessity for a large reliable and database has been a major concern in these studies. Noting that the current heart sound classification methods do not work properly for noisy signals, the PhysioNet/CinC Challenge 2016 aims at developing the heart sound classification algorithms by providing a global open database for challengers. This paper addresses the problem of heart sound classification methods within noisy real-world phonocardiogram (PCG) recordings by implementing an innovative approach...
June 8, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28594638/recognition-of-normal-abnormal-phonocardiographic-signals-using-deep-convolutional-neural-networks-and-mel-frequency-spectral-coefficients
#14
Vykintas Maknickas, Algirdas Maknickas
Intensive care unit patients are heavily monitored, and several clinically relevant parameters are routinely extracted from high resolution signals. The goal of the 2016 PhysioNet/CinC Challenge was to encourage the creation of an intelligent system that fused information from different phonocardiographic signals to create a robust set of normal/abnormal signal detections. Methods: Deep convolutional neural networks and mel-frequency spectral coefficients were used for recognition of normal-abnormal phonocardiographic signals of the human heart...
June 8, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28573981/at-what-data-length-do-cerebral-autoregulation-measures-stabilise
#15
Adam Mahdi, Dragana Nikolic, Antony Birch, Stephen Payne
Cerebral autoregulation is commonly assessed through mathematical models that use non-invasive measurements of arterial blood pressure and cerebral blood flow velocity. There is no agreement in the literature as to what is the minimum length of data needed for the cerebral autoregulation coefficients to stabilise. We introduce a simple empirical tool for studying the minimum length of time series needed to parameterise three popular cerebral autoregulation coefficients ARI, Mx and Phase (in the low frequency range [0...
June 2, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28569241/atrial-fibrillation-detection-on-compressed-sensed-ecg
#16
Giulia Da Poian, Chengyu Liu, Riccardo Bernardini, Roberto Rinaldo, Gari Clifford
OBJECTIVE: Compressive Sensing (CS) approaches to electrocardiogram (ECG) analysis provide efficient methods for real time encoding of cardiac activity. In doing so, it is important to assess the downstream effect of the compression on any signal processing and classification algorithms. CS is particularly suitable for low power wearable devices, thanks to its low-complex digital or hardware implementation that directly acquires a compressed version of the signal through random projections...
June 1, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28562369/combining-sparse-coding-and-time-domain-features-for-heart-sound-classification
#17
Bradley M Whitaker, Pradyumna Byappanahalli Suresha, Chengyu Liu, Gari Clifford, David Anderson
This paper builds upon work submitted as part of the 2016 PhysioNet/CinC Challenge, which used sparse coding as a feature extraction tool on audio PCG data for heart sound classification. In sparse coding, preprocessed data is decomposed into a dictionary matrix and a sparse coefficient matrix. The dictionary matrix represents statistically important features of the audio segments. The sparse coefficient matrix is a mapping that represents which features are used by each segment. Working in the sparse domain, we train support vector machines (SVMs) for each audio segment (S1, systole, S2, diastole) and a full cardiac cycle...
May 31, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28562368/heart-sounds-analysis-using-probability-assessment
#18
Filip Plesinger, Ivo Viscor, Josef Halamek, Juraj Jurco, Pavel Jurak
This paper describes a method for automated discrimination of heart sounds recordings according to the Physionet Challenge 2016. The goal was to decide if the recording refers to normal or abnormal heart sounds or if it is not possible to decide (i.e. "unsure" recordings). Approach: Heart sounds S1 and S2 are detected using amplitude envelopes in the band 15-90 Hz. The averaged shape of the S1/S2 pair is computed from amplitude envelopes in five different bands (15-90 Hz; 55-150 Hz; 100-250 Hz; 200-450 Hz; 400-800 Hz)...
May 31, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28530209/reproducible-3d-printed-head-tanks-for-electrical-impedance-tomography-with-realistic-shape-and-conductivity-distribution
#19
James Avery, Kirill Aristovich, Barney Low, David Holder
OBJECTIVE: Electrical impedance tomography (EIT) has many promising applications in brain injury monitoring. To evaluate both instrumentation and reconstruction algorithms, experiments are first performed in head tanks. Existing methods, whilst accurate, produce a discontinuous conductivity, and are often made by hand, making it hard for other researchers to replicate. APPROACH: We have developed a method for constructing head tanks directly in a 3D printer. Conductivity was controlled through perforations in the skull surface, which allow for saline to pass through...
May 22, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28530208/eit-imaging-of-admittivities-with-a-d-bar-method-and-spatial-prior-experimental-results-for-absolute-and-difference-imaging
#20
S J Hamilton
Electrical impedance tomography (EIT) is an emerging imaging modality that uses harmless electrical measurements taken on electrodes at a body's surface to recover information about the internal electrical conductivity and or permittivity. The image reconstruction task of EIT is a highly nonlinear inverse problem that is sensitive to noise and modeling errors making the image reconstruction task challenging. D-bar methods solve the nonlinear problem directly, bypassing the need for detailed and time-intensive forward models, to provide absolute (static) as well as time-difference EIT images...
May 22, 2017: Physiological Measurement
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