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https://www.readbyqxmd.com/read/28325033/user-intent-prediction-with-a-scaled-conjugate-gradient-trained-artificial-neural-network-for-lower-limb-amputees-using-a-powered-prosthesis
#1
Richard B Woodward, John A Spanias, Levi J Hargrove
Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees struggle with when using non-powered limbs. Previous literature has shown how pattern classification can allow seamless transitions between modes with a high accuracy and without any user interaction. Although accurate, training and testing each subject with their own dependent data is time consuming...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28325032/limb-position-robust-classification-of-myoelectric-signals-for-prosthesis-control-using-sparse-representations
#2
Joseph L Betthauser, Christopher L Hunt, Luke E Osborn, Rahul R Kaliki, Nitish V Thakor
The fundamental objective in non-invasive myoelectric prosthesis control is to determine the user's intended movements from corresponding skin-surface recorded electromyographic (sEMG) activation signals as quickly and accurately as possible. Linear Discriminant Analysis (LDA) has emerged as the de facto standard for real-time movement classification due to its ease of use, calculation speed, and remarkable classification accuracy under controlled training conditions. However, performance of cluster-based methods like LDA for sEMG pattern recognition degrades significantly when real-world testing conditions do not resemble the trained conditions, limiting the utility of myoelectrically controlled prosthesis devices...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28325028/tracking-intrinsic-connectivity-brain-network-features-during-successive-pseudo-resting-states-and-interoceptive-task-fmri
#3
Behnaz Jarrahi, Dante Mantini
Advanced multivariate analyses of functional magnetic resonance imaging (fMRI) data based on blood oxygen level-dependent (BOLD) contras have revealed that the human brain organizes its activities into multiple intrinsic connectivity networks (ICNs). Several fMRI studies have evaluated the modulations of these networks during different cognitive or emotional tasks using blind source separation techniques particularly the independent component analysis (ICA). In this exploratory study, we applied ICA methodology to examine ICN modulations under different interoceptive conditions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28325027/identifying-the-effects-of-visceral-interoception-on-human-brain-connectome-a-multivariate-analysis-of-covariance-of-fmri-data
#4
Behnaz Jarrahi, Dante Mantini
Sources of variations in the neural circuitry of the human brain and interrelationship between intrinsic connectivity networks (ICNs) are still a matter of debate and ongoing research. Here, we applied a multivariate analysis of covariance (MANCOVA) based on high-dimensional independent component analysis (ICA) to identify the effects of interoception and related variables on human brain connectome. Fifteen healthy right-handed subjects (all females, age range 21 - 48 years; mean age = 30.3, SD = 8.7 years) underwent a blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) that included continuous intravesical saline infusion and drainage...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28325025/comparison-between-users-of-a-new-methodology-for-heart-sound-auscultation
#5
Ana Castro, Pedro Gomes, Sandra S Mattos, Miguel T Coimbra
Auscultation is a routine exam and the first line of screening in heart pathologies. The objective of this study was to assess if using a new data collection system, the DigiScope Collector, with a guided and automatic annotation of heart auscultation, different levels of expertise/experience users could collect similar digital auscultations. Data were collected within the Heart Caravan Initiative (Paraíba, Brasil). Patients were divided into two study groups: Group 1 evaluated by a third year medical student (User 1), and an experienced nurse (User 2); Group 2 evaluated by User 2 and an Information Technology professional (User 3)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28325022/comparing-glucose-and-insulin-data-from-the-two-hour-oral-glucose-tolerance-test-in-metabolic-syndrome-subjects-and-marathon-runners
#6
Miguel Altuve, Gilberto Perpinan, Erika Severeyn, Sara Wong
Glucose is the main energy source of the body's cells and is essential for normal metabolism. Two pancreatic hormones, insulin and glucagon, are involved in glucose home-ostasis. Alteration in the plasma glucose and insulin concentrations could lead to distinct symptoms and diseases, ranging from mental function impairment to coma and even death. Type 2 diabetes, insulin resistance and metabolic syndrome are typical examples of abnormal glucose metabolism that increase the risk for cardiovascular disease and mortality...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28325010/step-length-and-width-variability-while-walking-on-a-motion-simulator-mounted-treadmill
#7
Timothy Boerger, Jacob Van Dehy, Tanya Onushko, Brian Schmit, Allison Hyngstrom
While devices which allow scientists to perturb normal walking are becoming increasingly common, postural adaptations to these perturbations have not been fully quantified. One way to quantify postural responses to perturbations are through the assessment of variability of step length and width. In the present study we determined variability of both step length and width while subjects walked under perturbations of varying amplitude in roll, pitch, yaw, anteroposterior, lateral, and combined roll, pitch, yaw directions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28325008/feasibility-of-an-ultra-low-power-digital-signal-processor-platform-as-a-basis-for-a-fully-implantable-brain-computer-interface-system
#8
Po T Wang, Keulanna Gandasetiawan, Colin M McCrimmon, Alireza Karimi-Bidhendi, Charles Y Liu, Payam Heydari, Zoran Nenadic, An H Do
A fully implantable brain-computer interface (BCI) can be a practical tool to restore independence to those affected by spinal cord injury. We envision that such a BCI system will invasively acquire brain signals (e.g. electrocorticogram) and translate them into control commands for external prostheses. The feasibility of such a system was tested by implementing its benchtop analogue, centered around a commercial, ultra-low power (ULP) digital signal processor (DSP, TMS320C5517, Texas Instruments). A suite of signal processing and BCI algorithms, including (de)multiplexing, Fast Fourier Transform, power spectral density, principal component analysis, linear discriminant analysis, Bayes rule, and finite state machine was implemented and tested in the DSP...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28325001/reliability-of-a-cortical-surface-based-analysis-with-subcortical-regression-in-the-identification-of-resting-state-functional-networks
#9
R Lopes, P Besson, R Viard, C Bournonville, C Delmaire, X Leclerc
Many methods exist for identifying brain networks in resting-state functional magnetic resonance imaging. During the last decade, there was a growing interest in functional connectivity using surface-based analysis. However, the advantages of this approach against volume-based analysis in a data-driven model are unclear. In this study, we propose an independent component analysis based method to extract the resting-state networks directly on the cortical surface. The components associated with the subcortical regions are identified by multiple linear regressions between the signals in subcortical voxels and independent components time courses...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324995/eeg-based-mental-fatigue-detection-by-spectral-non-negative-matrix-factorization
#10
Lili Li, Guanghua Xu, Jun Xie, Min Li, Sicong Zhang, Ailing Luo
After long time cognitive work, most of people confronted with the mental fatigue, which can decrease the classification accuracy of cognitive, or even cause the traffic accidents for drivers. Therefore, the detection of the fatigue state is very essential. The study aims to explore an effective and novel approach based on electroencephalogram. All participants were instructed to implement the spelling experiments. Data were recorded on the awake condition, on sleep deprivation condition and after two hour spelling experiment...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324993/dynamic-knee-muscle-co-contraction-quantified-during-walking
#11
Annachiara Strazza, Alessandro Mengarelli, Valentina Agostini, Marco Knaflitz, Laura Burattini, Sandro Fioretti, Francesco Di Nardo
The purpose of the present study was the quantification of the co-activation patterns of the knee extensor and flexor muscles during walking at self-selected speed and cadence. To this aim, the Statistical Gait Analysis, a recent methodology providing a statistical characterization of gait, was performed on surface EMG signals from Vastus Lateralis (VL) and Medial Hamstrings (MH) in 14 healthy young adult subjects. Muscular co-contraction was assessed as the overlapping period between activation intervals of agonist and antagonist muscles...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324989/non-contact-real-time-estimation-of-intrapulmonary-pressure-and-tidal-volume-for-chronic-heart-failure-patients
#12
Vinh Phuc Tran, Adel Ali Al-Jumaily
Long-term continuous patient monitoring is required in many health systems for monitoring and analytical diagnosing purposes. It has been recognized that these types of monitoring systems have shortcomings related to patient comfort and/or functionality. Non-contact monitoring systems have been developed to address some of these shortcomings. One of such systems is non-contact physiological vital signs assessments for Chronic Heart Failure (CHF) patients. This paper presents a novel pulmonary ventilation model that defines the relationship between the intrapulmonary pressure and the chest displacement...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324980/effect-of-wearable-sensor-dynamics-on-physical-activity-estimates-a-comparison-between-sci-vs-healthy-individuals
#13
C Jayaraman, C K Mummidisetty, A Jayaraman
Accuracy of physical activity estimates predicted by activity monitoring technologies may be affected by device location, analysis algorithms, type of technology (i.e. wearable/stickable) and population demographics (disability) being studied. Consequently, the main purpose of this investigation was to study such sensor dynamics (i.e. effect of device location, type and population demographics on energy expenditure estimates) of two commercial activity monitors. It was hypothesized that device location, population studied (disability), choice of proprietary algorithm and type of technology used will significantly impact the accuracy of the predicted physical activity metrics...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324977/a-novel-method-to-assess-angle-sensor-performance-for-wearable-exoskeletal-joint-kinematics
#14
Nicholas B Bolus, Geza F Kogler, Omer T Inan
Full range of motion (ROM) at a joint is necessary for efficient and adaptive movement; as such, it is an essential clinical evaluation measure for assessing an individual's motor function, which can be affected by any number of musculoskeletal injuries and neuropathies. Measurement of joint ROM in the clinic has classically been accomplished statically through the use of a manual goniometer. More recent efforts in the fields of prosthetics and orthotics have demonstrated the potential utility of wearable systems (e...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324970/development-of-data-acquisition-components-for-simultaneous-recording-of-3d-epicardial-and-surface-ecg-signals-in-the-langendorff-perfusion-apparatus
#15
Ryan Wade Selby, Anup Jonchhe, Chen Kaplan, Coeli M Lopes, Behnaz Ghoraani
Sudden Cardiac Death (SCD) claims 7 million lives per year. The importance of myocardial electrogram (EGM) repolarization alternans and surface electrocardiogram (ECG) T-wave alternans is gaining traction for understanding the underlying SCD mechanisms. However, the relationship between the 3D spatial distribution of myocardial EGMs and surface ECG with respect to SCD has yet to be investigated. To make this happen, a modified data acquisition system has been developed and fabricated in conjunction with the Langendorff perfusion system to enable simultaneous recording and analysis of the 3D spatial distribution of myocardial EGMs and the surface ECG...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324968/improving-cardiopulmonary-resuscitation-cpr-outcomes-using-model-based-optimization
#16
Dieter Bender, Ali Jalali, C Nataraj
Cardiopulmonary Resuscitation (CPR) outcomes are far from optimal as practiced today, and prior work has documented that among probable reasons is the fact that the procedure remains to be fully understood. In an attempt to gain a broader understanding of the CPR physiology and the elemental principles underlying the CPR outcomes, this study proposes a novel approach. The analysis is carried out in three major steps. First, an appropriate cardiovascular system model was adopted and simulated using real CPR data as the input...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324941/3-d-registration-on-carotid-artery-imaging-data-mri-for-different-timesteps
#17
Paschalis A Bizopoulos, Antonis Sakellarios, Lampros K Michalis, Dimitrios D Koutsouris, Dimitrios I Fotiadis
A common problem which is faced by the researchers when dealing with arterial carotid imaging data is the registration of the geometrical structures between different imaging modalities or different timesteps. The use of the "Patient Position" DICOM field is not adequate to achieve accurate results due to the fact that the carotid artery is a relatively small structure and even imperceptible changes in patient position and/or direction make it difficult. While there is a wide range of simple/advanced registration techniques in the literature, there is a considerable number of studies which address the geometrical structure of the carotid artery without using any registration technique...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324940/use-of-local-field-potentials-of-dissociated-cultures-grown-on-multi-electrode-arrays-for-pharmacological-assays
#18
G D C Mendis, E Morrisroe, C A Reid, S K Halgamuge, S Petrou
In vitro Multi-Electrode Arrays (MEA) are an extracellular recording technology that enables the analysis of networks of neurons in vitro. Neurons in culture exhibit a range of behavioral dynamics, which can be measured in terms of individual action potentials, network-wide synchronized firing and a host of other features that characterize network activity. MEA data analysis was historically focused on high frequency spike data forgoing the low frequency content of the signal. In this study, we use local field potentials, which are low frequency components of MEA signals, to differentiate between two types of antiepileptic drugs (p<;0...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324939/visual-transparent-visual-occlusion-an-eeg-and-cop-study
#19
Kwang Leng Goh, Susan Morris, Wee Lih Lee, Alexander Ring, Tele Tan
Electroencephalography (EEG) and centre of pressure (COP) data were recorded in young adults for 60 seconds during standing in visual transparent (VT) and visual occlusion (VO) conditions. In both of these conditions, participants wore VO liquid crystal spectacles which allowed the experimenter to accurately control visual information being presented or occluded to the participant. Alpha band (8-13 Hz) revealed significant differences in channel-averaged power spectrum in these two conditions, but not theta band (4-8 Hz) and beta band (13-30 Hz)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324938/application-of-semi-supervised-deep-learning-to-lung-sound-analysis
#20
Daniel Chamberlain, Rahul Kodgule, Daniela Ganelin, Vivek Miglani, Richard Ribon Fletcher
The analysis of lung sounds, collected through auscultation, is a fundamental component of pulmonary disease diagnostics for primary care and general patient monitoring for telemedicine. Despite advances in computation and algorithms, the goal of automated lung sound identification and classification has remained elusive. Over the past 40 years, published work in this field has demonstrated only limited success in identifying lung sounds, with most published studies using only a small numbers of patients (typically N<;20) and usually limited to a single type of lung sound...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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