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https://www.readbyqxmd.com/read/28230796/a-sensor-data-fusion-system-based-on-k-nearest-neighbor-pattern-classification-for-structural-health-monitoring-applications
#1
Jaime Vitola, Francesc Pozo, Diego A Tibaduiza, Maribel Anaya
Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis...
February 21, 2017: Sensors
https://www.readbyqxmd.com/read/28230767/an-adaptive-multi-sensor-data-fusion-method-based-on-deep-convolutional-neural-networks-for-fault-diagnosis-of-planetary-gearbox
#2
Luyang Jing, Taiyong Wang, Ming Zhao, Peng Wang
A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections...
February 21, 2017: Sensors
https://www.readbyqxmd.com/read/28230751/the-feasibility-of-embedding-data-collection-into-the-routine-service-delivery-of-a-multi-component-program-for-high-risk-young-people
#3
Alice Knight, Alys Havard, Anthony Shakeshaft, Myfanwy Maple, Mieke Snijder, Bernie Shakeshaft
BACKGROUND: There is little evidence about how to improve outcomes for high-risk young people, of whom Indigenous young people are disproportionately represented, due to few evaluation studies of interventions. One way to increase the evidence is to have researchers and service providers collaborate to embed evaluation into the routine delivery of services, so program delivery and evaluation occur simultaneously. This study aims to demonstrate the feasibility of integrating best-evidence measures into the routine data collection processes of a service for high-risk young people, and identify the number and nature of risk factors experienced by participants...
February 20, 2017: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/28230725/towards-a-semantic-web-of-things-a-hybrid-semantic-annotation-extraction-and-reasoning-framework-for-cyber-physical-system
#4
Zhenyu Wu, Yuan Xu, Yunong Yang, Chunhong Zhang, Xinning Zhu, Yang Ji
Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability...
February 20, 2017: Sensors
https://www.readbyqxmd.com/read/28229247/achieving-population-level-change-through-a-system-contextual-approach-to-supporting-competent-parenting
#5
REVIEW
Matthew R Sanders, Kylie Burke, Ronald J Prinz, Alina Morawska
The quality of parenting children receive affects a diverse range of child and youth outcomes. Addressing the quality of parenting on a broad scale is a critical part of producing a more nurturing society. To achieve a meaningful population-level reduction in the prevalence rates of child maltreatment and social and emotional problems that are directly or indirectly influenced by parenting practices requires the adoption of a broad ecological perspective in supporting families to raise children. We make the case for adopting a multilevel, whole of population approach to enhance competent parenting and describe the essential tasks that must be accomplished for the approach to be successful and its effects measurable...
February 22, 2017: Clinical Child and Family Psychology Review
https://www.readbyqxmd.com/read/28229175/survival-prediction-of-trauma-patients-a-study-on-us-national-trauma-data-bank
#6
I Sefrioui, R Amadini, J Mauro, A El Fallahi, M Gabbrielli
BACKGROUND: Exceptional circumstances like major incidents or natural disasters may cause a huge number of victims that might not be immediately and simultaneously saved. In these cases it is important to define priorities avoiding to waste time and resources for not savable victims. Trauma and Injury Severity Score (TRISS) methodology is the well-known and standard system usually used by practitioners to predict the survival probability of trauma patients. However, practitioners have noted that the accuracy of TRISS predictions is unacceptable especially for severely injured patients...
February 22, 2017: European Journal of Trauma and Emergency Surgery: Official Publication of the European Trauma Society
https://www.readbyqxmd.com/read/28228573/grace-under-pressure-a-drama-based-approach-to-tackling-mistreatment-of-medical-students
#7
Karen M Scott, Špela Berlec, Louise Nash, Claire Hooker, Paul Dwyer, Paul Macneill, Jo River, Kimberley Ivory
A positive and respectful learning environment is fundamental to the development of professional identities in healthcare. Yet medical students report poor behaviour from healthcare professionals that contradict professionalism teaching. An interdisciplinary group designed and implemented a drama-based workshop series, based on applied theatre techniques, to help students develop positive professional qualities and interpersonal skills to deal with challenges in the healthcare setting. We piloted the workshops at the University of Sydney in 2015...
March 2017: Medical Humanities
https://www.readbyqxmd.com/read/28227970/combining-a-hybrid-robotic-system-with-a-bain-machine-interface-for-the-rehabilitation-of-reaching-movements-a-case-study-with-a-stroke-patient
#8
F Resquin, J Ibanez, J Gonzalez-Vargas, F Brunetti, I Dimbwadyo, S Alves, L Carrasco, L Torres, Jose Luis Pons, F Resquin, J Ibañez, J Gonzalez-Vargas, F Brunetti, I Dimbwadyo, S Alves, L Carrasco, L Torres, Jose Luis Pons, S Alves, Jose Luis Pons, F Brunetti, J Gonzalez-Vargas, F Resquin, I Dimbwadyo, L Carrasco, L Torres, J Ibanez
Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation with Robotic devices have been proposed in the literature to improve rehabilitation outcomes. In this work, we present the combined use of a hybrid robotic system with an EEG-based Brain-Machine Interface to detect the user's movement intentions to trigger the assistance. The platform has been tested in a single session with a stroke patient. The results show how the patient could successfully interact with the BMI and command the assistance of the hybrid system with low latencies...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227877/a-wearable-computing-platform-for-developing-cloud-based-machine-learning-models-for-health-monitoring-applications
#9
Shyamal Patel, Ryan S McGinnis, Ikaro Silva, Steve DiCristofaro, Nikhil Mahadevan, Elise Jortberg, Jaime Franco, Albert Martin, Joseph Lust, Milan Raj, Bryan McGrane, Paolo DePetrillo, A J Aranyosi, Melissa Ceruolo, Jesus Pindado, Roozbeh Ghaffari, Shyamal Patel, Ryan S McGinnis, Ikaro Silva, Steve DiCristofaro, Nikhil Mahadevan, Elise Jortberg, Jaime Franco, Albert Martin, Joseph Lust, Milan Raj, Bryan McGrane, Paolo DePetrillo, A J Aranyosi, Melissa Ceruolo, Jesus Pindado, Roozbeh Ghaffari
Wearable sensors have the potential to enable clinical-grade ambulatory health monitoring outside the clinic. Technological advances have enabled development of devices that can measure vital signs with great precision and significant progress has been made towards extracting clinically meaningful information from these devices in research studies. However, translating measurement accuracies achieved in the controlled settings such as the lab and clinic to unconstrained environments such as the home remains a challenge...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227720/can-we-make-a-carpet-smart-enough-to-detect-falls
#10
Fadi Muheidat, Harry W Tyrer, Fadi Muheidat, Harry W Tyrer, Harry W Tyrer, Fadi Muheidat
In this paper, we have enhanced smart carpet, which is a floor based personnel detector system, to detect falls using a faster but low cost processor. Our hardware front end reads 128 sensors, with sensors output a voltage due to a person walking or falling on the carpet. The processor is Jetson TK1, which provides more computing power than before. We generated a dataset with volunteers who walked and fell to test our algorithms. Data obtained allowed examining data frames (a frame is a single scan of the carpet sensors) read from the data acquisition system...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227711/detection-of-fetal-kicks-using-body-worn-accelerometers-during-pregnancy-trade-offs-between-sensors-number-and-positioning
#11
Marco Altini, Patrick Mullan, Michiel Rooijakkers, Stefan Gradl, Julien Penders, Nele Geusens, Lars Grieten, Bjoern Eskofier, Marco Altini, Patrick Mullan, Michiel Rooijakkers, Stefan Gradl, Julien Penders, Nele Geusens, Lars Grieten, Bjoern Eskofier, Julien Penders, Michiel Rooijakkers, Nele Geusens, Stefan Gradl, Patrick Mullan, Lars Grieten, Bjoern Eskofier, Marco Altini
Monitoring fetal wellbeing is key in modern obstetrics. While fetal movement is routinely used as a proxy to fetal wellbeing, accurate, noninvasive, long-term monitoring of fetal movement is challenging. A few accelerometer-based systems have been developed in the past few years, to tackle common issues in ultrasound measurement and enable remote, self-administrated monitoring of fetal movement during pregnancy. However, many questions remain unanswered to date on the optimal setup in terms of body-worn accelerometers as well as signal processing and machine learning techniques used to detect fetal movement...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227651/adaptive-control-of-powered-transfemoral-prostheses-based-on-adaptive-dynamic-programming
#12
Yue Wen, Ming Liu, Jennie Si, He Helen Huang, Yue Wen, Ming Liu, Jennie Si, He Huang, He Helen Huang, Yue Wen, Ming Liu, Jennie Si
In this study, we developed and tested a novel adaptive controller for powered transfemoral prostheses. Adaptive dynamic programming (ADP) was implemented within the prosthesis control to complement the existing finite state impedance control (FS-IC) in a prototypic active-transfemoral prosthesis (ATP). The ADP controller interacts with the human user-prosthesis system, observes the prosthesis user's dynamic states during walking, and learns to personalize user performance properties via online adaptation to meet the individual user's objectives...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227335/a-noise-assisted-data-analysis-method-for-automatic-eog-based-sleep-stage-classification-using-ensemble-learning
#13
Alexander Neergaard Olesen, Julie A E Christensen, Helge B D Sorensen, Poul J Jennum, Alexander Neergaard Olesen, Julie A E Christensen, Helge B D Sorensen, Poul J Jennum, Julie A E Christensen, Helge B D Sorensen, Alexander Neergaard Olesen, Poul J Jennum
Reducing the number of recording modalities for sleep staging research can benefit both researchers and patients, under the condition that they provide as accurate results as conventional systems. This paper investigates the possibility of exploiting the multisource nature of the electrooculography (EOG) signals by presenting a method for automatic sleep staging using the complete ensemble empirical mode decomposition with adaptive noise algorithm, and a random forest classifier. It achieves a high overall accuracy of 82% and a Cohen's kappa of 0...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227212/classification-of-large-scale-fundus-image-data-sets-a-cloud-computing-framework
#14
Sohini Roychowdhury, Sohini Roychowdhury, Sohini Roychowdhury
Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226882/development-of-a-real-time-activity-monitoring-android-application-utilizing-smartstep
#15
Nagaraj Hegde, Edward Melanson, Edward Sazonov, Nagaraj Hegde, Edward Melanson, Edward Sazonov, Nagaraj Hegde, Edward Melanson, Edward Sazonov
Footwear based activity monitoring systems are becoming popular in academic research as well as consumer industry segments. In our previous work, we had presented developmental aspects of an insole based activity and gait monitoring system-SmartStep, which is a socially acceptable, fully wireless and versatile insole. The present work describes the development of an Android application that captures the SmartStep data wirelessly over Bluetooth Low energy (BLE), computes features on the received data, runs activity classification algorithms and provides real time feedback...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226811/day-to-day-variability-in-hybrid-passive-brain-computer-interfaces-comparing-two-studies-assessing-cognitive-workload
#16
Samantha L Klosterman, Justin R Estepp, Jason W Monnin, James C Christensen, Samantha L Klosterman, Justin R Estepp, Jason W Monnin, James C Christensen, Jason W Monnin, Samantha L Klosterman, Justin R Estepp, James C Christensen
As hybrid, passive brain-computer interface systems become more advanced, it is important to grow our understanding of how to produce generalizable pattern classifiers of physiological data. One of the most difficult problems in applying machine learning algorithms to these data types is nonstationarity, which can evolve over the course of hours and days, and is more susceptible to changes resulting from complex cognitive function in comparison to simple, stimulus-based processes. This nonstationarity, referenced as day-to-day variability, results in the inability of many learning algorithms to generalize to new data...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226742/a-cnn-based-neurobiology-inspired-approach-for-retinal-image-quality-assessment
#17
Dwarikanath Mahapatra, Pallab K Roy, Suman Sedai, Rahil Garnavi, Dwarikanath Mahapatra, Pallab K Roy, Suman Sedai, Rahil Garnavi, Suman Sedai, Pallab K Roy, Rahil Garnavi, Dwarikanath Mahapatra
Retinal image quality assessment (IQA) algorithms use different hand crafted features for training classifiers without considering the working of the human visual system (HVS) which plays an important role in IQA. We propose a convolutional neural network (CNN) based approach that determines image quality using the underlying principles behind the working of the HVS. CNNs provide a principled approach to feature learning and hence higher accuracy in decision making. Experimental results demonstrate the superior performance of our proposed algorithm over competing methods...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226674/a-multiple-kernel-learning-approach-for-human-behavioral-task-classification-using-stn-lfp-signal
#18
Hosein M Golshan, Adam O Hebb, Sara J Hanrahan, Joshua Nedrud, Mohammad H Mahoor, Hosein M Golshan, Adam O Hebb, Sara J Hanrahan, Joshua Nedrud, Mohammad H Mahoor, Joshua Nedrud, Adam O Hebb, Sara J Hanrahan, Mohammad H Mahoor, Hosein M Golshan
Deep Brain Stimulation (DBS) has gained increasing attention as an effective method to mitigate Parkinson's disease (PD) disorders. Existing DBS systems are open-loop such that the system parameters are not adjusted automatically based on patient's behavior. Classification of human behavior is an important step in the design of the next generation of DBS systems that are closed-loop. This paper presents a classification approach to recognize such behavioral tasks using the subthalamic nucleus (STN) Local Field Potential (LFP) signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226667/automatic-seizure-detection-using-correlation-integral-with-nonlinear-adaptive-denoising-and-kalman-filter
#19
Hongda Wang, Chiu-Sing Choy, Hongda Wang, Chiu-Sing Choy, Hongda Wang, Chiu-Sing Choy
The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising and Kalman filter have been adopted for pre-processing and post-processing. The three-stage algorithm has achieved 84.6% sensitivity and 0.087/h false detection rate, which are comparable to many machine learning based methods, but at much lower computational cost...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226630/gaussian-process-dynamical-models-for-multimodal-affect-recognition
#20
Hernan F Garcia, Mauricio A Alvarez, Alvaro A Orozco, Hernan F Garcia, Mauricio A Alvarez, Alvaro A Orozco, Mauricio A Alvarez, Alvaro A Orozco, Hernan F Garcia
Affective computing systems has a great potential in applications for biofeedback systems and cognitive conductual therapies. Here, by analyzing the physiological behavior of a given subject, we can infer the affective state of an emotional process. Since, emotions can be modeled as dynamic manifestations of these signals, a continuous analysis in the valence/arousal space, brings more information of the affective state related to an emotional process. In this paper we propose a method for dynamic affect recognition from multimodal physiological signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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