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https://www.readbyqxmd.com/read/28227976/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, Richard B Woodward, John A Spanias, Levi J Hargrove, John A Spanias, Richard B Woodward, 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/28227876/a-dynamic-data-source-selection-system-for-smartwatch-platform
#2
Ebrahim Nemati, Konstantinos Sideris, Haik Kalantarian, Majid Sarrafzadeh, Ebrahim Nemati, Konstantinos Sideris, Haik Kalantarian, Majid Sarrafzadeh, Haik Kalantarian, Majid Sarrafzadeh, Konstantinos Sideris, Ebrahim Nemati
A novel data source selection algorithm is proposed for ambulatory activity tracking of elderly people. The algorithm introduces the concept of dynamic switching between the data collection modules (a smartwatch and a smartphone) to improve accuracy and battery life using contextual information. We show that by making offloading decisions as a function of activity, the proposed algorithm improves power consumption and accuracy of the previous work by 7 hours and 5% respectively compared to the baseline.
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227830/an-adaptive-model-approach-for-quantitative-wrist-rigidity-evaluation-during-deep-brain-stimulation-surgery
#3
Sofia Assis, Pedro Costa, Maria Jose Rosas, Rui Vaz, Joao Paulo Silva Cunha, Sofia Assis, Pedro Costa, Maria Jose Rosas, Rui Vaz, Joao Paulo Silva Cunha, Maria Jose Rosas, Joao Paulo Silva Cunha, Sofia Assis, Rui Vaz, Pedro Costa
Intraoperative evaluation of the efficacy of Deep Brain Stimulation includes evaluation of the effect on rigidity. A subjective semi-quantitative scale is used, dependent on the examiner perception and experience. A system was proposed previously, aiming to tackle this subjectivity, using quantitative data and providing real-time feedback of the computed rigidity reduction, hence supporting the physician decision. This system comprised of a gyroscope-based motion sensor in a textile band, placed in the patients hand, which communicated its measurements to a laptop...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227788/lessons-learnt-from-a-mooc-about-social-media-for-digital-health-literacy
#4
Suleman Atique, Mowafa Hosueh, Luis Fernandez-Luque, Elia Gabarron, Marian Wan, Onkar Singh, Vicente Traver Salcedo, Yu-Chuan Jack Li, Syed-Abdul Shabbir, Suleman Atique, Mowafa Hosueh, Luis Fernandez-Luque, Elia Gabarron, Marian Wan, Onkar Singh, Vicente Traver Salcedo, Yu-Chuan Jack Li, Syed-Abdul Shabbir, Elia Gabarron, Marian Wan, Mowafa Hosueh, Luis Fernandez-Luque, Onkar Singh, Syed-Abdul Shabbir, Yu-Chuan Jack Li, Vicente Traver Salcedo, Suleman Atique
Nowadays, the Internet and social media represent prime channels for health information seeking and peer support. However, benefits of health social media can be reduced by low digital health literacy. We designed a massive open online course (MOOC) course about health social media to increase the students' digital health literacy. In this course, we wanted to explore the difficulties confronted by the MOOC users in relation to accessing quality online health information and to propose methods to overcome the issues...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227780/impact-of-prostate-biopsy-tumor-amount-on-imaging-based-prognostics-employing-transductive-semi-supervised-regression
#5
Faisal M Khan, Casimir A Kulikowski, Faisal M Khan, Casimir A Kulikowski, Casimir A Kulikowski, Faisal M Khan
For newly diagnosed prostate cancer patients with a positive biopsy, there are a variety of treatment options to consider. To aid physicians and patients in their decision making, a variety of predictive assays have emerged within the last decade, many of them imaging based. These assays build predictive models for survival analysis to provide personalized risk assessments for the patients. However, there have rarely been any published studies on how the amount of tumor in the positive prostate biopsy affects the predictive power of these imaging based assays...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227563/a-study-on-the-effect-of-multisensory-stimulation-in-behaving-rats
#6
Marianna Semprini, Fabio Boi, Valter Tucci, Alessandro Vato, Marianna Semprini, Fabio Boi, Valter Tucci, Alessandro Vato, Fabio Boi, Valter Tucci, Marianna Semprini, Alessandro Vato
This study explored the psychophysical effects of intracortical microstimulation (ICMS) coupled to auditory stimulation during a behavioral detection task in rats. ICMS directed to the sensory areas of the cortex can be instrumental in facilitating operant conditioning behavior. Moreover, multisensory stimulation promotes learning by enabling the subject to access multiple information channels. However, the extent to which multisensory information can be used as a cue to make decisions has not been fully understood...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227486/patient-walk-detection-in-hospital-room-using-microsoft-kinect-v2
#7
Liang Liu, Sanjay Mehrotra, Liang Liu, Sanjay Mehrotra, Liang Liu, Sanjay Mehrotra
This paper describes a system using Kinect sensor to detect patient walk automatically in a hospital room setting. The system is especially essential for the case when the patient is alone and the nursing staff is absent. The patient activities are represented by the features extracted from Kinect V2 skeletons. The analysis to the recognized walk could help us to better understand the health situation of the patient and the possible hospital acquired infection (HAI), and provide valuable information to healthcare givers for making a corresponding treatment decision and alteration...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227478/portable-video-oculography-device-for-implementation-in-sideline-concussion-assessments-a-prototype
#8
Joshua D Fischer, Dawie J van den Heever, Joshua D Fischer, Dawie J van den Heever, Dawie J Van den Heever, Joshua D Fischer
Concussion is currently a serious health problem and can lead to severe brain dysfunction. There is a definite need for sensitive and reliable tests to detect and evaluate the subtle changes in brain function caused by concussion. This study details the development of a low cost portable eye tracking device that can aid in the detection of concussions. The device evaluates ocular motor function and can be used on the sidelines of sporting events to give a quick indication of the severity of head trauma. It can further be used to evaluate and monitor mild Traumatic Brain Injuries and aid in the return to play decision making process...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227477/predictive-models-for-diffuse-low-grade-glioma-patients-under-chemotherapy
#9
Meriem Ben Abdallah, Marie Blonski, Sophie Wantz-Mezieres, Yann Gaudeau, Luc Taillandier, Jean-Marie Moureaux, Meriem Ben Abdallah, Marie Blonski, Sophie Wantz-Mezieres, Yann Gaudeau, Luc Taillandier, Jean-Marie Moureaux, Luc Taillandier, Jean-Marie Moureaux, Marie Blonski, Yann Gaudeau, Sophie Wantz-Mezieres, Meriem Ben Abdallah
Diffuse low-grade gliomas are rare primitive cerebral tumours of adults. These tumors progress continuously over time and then turn to a higher grade of malignancy associated with neurological disability, leading ultimately to death. Tumour size is one of the most important prognostic factors. Thus, it is of great importance to be able to assess the volume of the tumor during the patients' monitoring. MRI is nowadays the recommended modality to achieve this. Furthermore, if surgery remains the first option for diffuse low-grade gliomas, chemotherapy is increasingly used (before or after a possible surgery)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227248/the-precuneus-may-encode-irrationality-in-human-gambling
#10
P Sacre, M S D Kerr, S Subramanian, K Kahn, J Gonzalez-Martinez, M A Johnson, S V Sarma, J T Gale, P Sacre, M S D Kerr, S Subramanian, K Kahn, J Gonzalez-Martinez, M A Johnson, S V Sarma, J T Gale, S Subramanian, M S D Kerr, M A Johnson, J T Gale, K Kahn, P Sacre, S V Sarma, J Gonzalez-Martinez
Humans often make irrational decisions, especially psychiatric patients who have dysfunctional cognitive and emotional circuitry. Understanding the neural basis of decision-making is therefore essential towards patient management, yet current studies suffer from several limitations. Functional magnetic resonance imaging (fMRI) studies in humans have dominated decision-making neuroscience, but have poor temporal resolution and the blood oxygenation level-dependent signal is only a proxy for neural activity. On the other hand, lesion studies in humans used to infer functionality in decision-making lack characterization of neural activity altogether...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227144/optimal-medication-dosing-from-suboptimal-clinical-examples-a-deep-reinforcement-learning-approach
#11
Shamim Nemati, Mohammad M Ghassemi, Gari D Clifford, Shamim Nemati, Mohammad M Ghassemi, Gari D Clifford, Gari D Clifford, Mohammad M Ghassemi
Misdosing medications with sensitive therapeutic windows, such as heparin, can place patients at unnecessary risk, increase length of hospital stay, and lead to wasted hospital resources. In this work, we present a clinician-in-the-loop sequential decision making framework, which provides an individualized dosing policy adapted to each patient's evolving clinical phenotype. We employed retrospective data from the publicly available MIMIC II intensive care unit database, and developed a deep reinforcement learning algorithm that learns an optimal heparin dosing policy from sample dosing trails and their associated outcomes in large electronic medical records...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227143/csdc-a-nationwide-screening-platform-for-stroke-control-and-prevention-in-china
#12
Jinghui Yu, Huajian Mao, Mei Li, Dan Ye, Dongsheng Zhao, Jinghui Yu, Huajian Mao, Mei Li, Dan Ye, Dongsheng Zhao, Dan Ye, Huajian Mao, Mei Li, Dongsheng Zhao, Jinghui Yu
As a leading cause of severe disability and death, stroke places an enormous burden on Chinese society. A nationwide stroke screening platform called CSDC (China Stoke Data Center) has been built to support the national stroke prevention program and stroke clinical research since 2011. This platform is composed of a data integration system and a big data analysis system. The data integration system is used to collect information on risk factors, diagnosis history, treatment, and sociodemographic characteristics and stroke patients' EMR...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227048/anticoagulation-manager-development-of-a-clinical-decision-support-mobile-application-for-management-of-anticoagulants
#13
Chih-Wen Cheng, Hang Wu, Pamela J Thompson, Julie R Taylor, Barbara A Zehnbauer, Karlyn K Wilson, May D Wang, Chih-Wen Cheng, Hang Wu, Pamela J Thompson, Julie R Taylor, Barbara A Zehnbauer, Karlyn K Wilson, May D Wang, Karlyn K Wilson, Pamela J Thompson, Barbara A Zehnbauer, Hang Wu, Julie R Taylor, Chih-Wen Cheng, May D Wang
Patients with certain clotting disorders or conditions have a greater risk of developing arterial or venous clots and downstream embolisms, strokes, and arterial insufficiency. These patients need prescription anticoagulant drugs to reduce the possibility of clot formation. However, historically, the clinical decision making workflow in determining the correct type and dosage of anticoagulant(s) is part science and part art. To address this problem, we developed Anticoagulation Manager, an intelligent clinical decision workflow management system on iOS-based mobile devices to help clinicians effectively choose the most appropriate and helpful follow-up clotting tests for patients with a common clotting profile...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226971/personalized-sleep-staging-system-using-evolutionary-algorithm-and-symbolic-fusion
#14
Chen Chen, Adrien Ugon, Xun Zhang, Amara Amara, Patrick Garda, Jean-Gabriel Ganascia, Carole Philippe, Andrea Pinna, Chen Chen, Adrien Ugon, Xun Zhang, Amara Amara, Patrick Garda, Jean-Gabriel Ganascia, Carole Philippe, Andrea Pinna, Adrien Ugon, Carole Philippe, Patrick Garda, Amara Amara, Chen Chen, Andrea Pinna, Jean-Gabriel Ganascia, Xun Zhang
This paper presents a novel system for automatic sleep staging based on evolutionary technique and symbolic intelligence. Proposed system mimics decision making process of clinical sleep staging using Symbolic Fusion and considers personal singularity with an adaptive thresholds setting up system using Evolutionary Algorithm. It proved to be an effective and promising system in personalizing sleep staging. This system can also be integrated with other medical systems to realize remote sleep monitoring or home-care...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226966/measuring-the-quality-of-exercises
#15
Paritosh Parmar, Brendan Tran Morris, Paritosh Parmar, Brendan Tran Morris, Paritosh Parmar, Brendan Tran Morris
This work explores the problem of exercise quality measurement since it is essential for effective management of diseases like cerebral palsy (CP). This work examines the assessment of quality of large amplitude movement (LAM) exercises designed to treat CP in an automated fashion. Exercise data was collected by trained participants to generate ideal examples to use as a positive samples for machine learning. Following that, subjects were asked to deliberately make subtle errors during the exercise, such as restricting movements, as is commonly seen in cases of patients suffering from CP...
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
#16
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/28226618/eeg-based-driver-fatigue-detection-using-hybrid-deep-generic-model
#17
Phyo Phyo San, Sai Ho Ling, Rifai Chai, Yvonne Tran, Ashley Craig, Hung Nguyen, Phyo Phyo San, Sai Ho Ling, Rifai Chai, Yvonne Tran, Ashley Craig, Hung Nguyen, Ashley Craig, Sai Ho Ling, Hung Nguyen, Phyo Phyo San, Yvonne Tran, Rifai Chai
Classification of electroencephalography (EEG)-based application is one of the important process for biomedical engineering. Driver fatigue is a major case of traffic accidents worldwide and considered as a significant problem in recent decades. In this paper, a hybrid deep generic model (DGM)-based support vector machine is proposed for accurate detection of driver fatigue. Traditionally, a probabilistic DGM with deep architecture is quite good at learning invariant features, but it is not always optimal for classification due to its trainable parameters are in the middle layer...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226494/upper-extremity-prosthesis-user-perspectives-on-unmet-needs-and-innovative-technology
#18
Heather L Benz, Jia Yao, Laura Rose, Okan Olgac, Karen Kreutz, Anindita Saha, Eugene F Civillico, Heather L Benz, Jia Yao, Laura Rose, Okan Olgac, Karen Kreutz, Anindita Saha, Eugene F Civillico, Laura Rose, Heather L Benz, Anindita Saha, Okan Olgac, Eugene F Civillico, Karen Kreutz, Jia Yao
The needs of individuals with upper limb amputation and congenital limb difference are not being fully met by current prostheses, as evidenced by prosthesis rejection, non-wear, and user reports of pain and challenging activities. Emerging technologies such as dexterous sensorized robotic limbs, osseointegrated prostheses, implantable EMG electrodes, and electrical stimulation for sensory feedback have the potential to address unmet needs, but pose additional risks. We plan to assess upper limb prosthesis user needs and perspectives on these new benefits and risks using an extensive quantitative survey...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226433/preliminary-results-of-residual-deficits-observed-in-athletes-with-concussion-history-combined-eeg-and-cognitive-study
#19
Tamanna T K Munia, Jeffrey L Gendreau, Ajay K Verma, Benjamin D Johnson, Mark Romanick, Kouhyar Tavakolian, Reza Fazel-Rezai, Tamanna T K Munia, Jeffrey L Gendreau, Ajay K Verma, Benjamin D Johnson, Mark Romanick, Kouhyar Tavakolian, Reza Fazel-Rezai, Reza Fazel-Rezai, Jeffrey L Gendreau, Benjamin D Johnson, Tamanna T K Munia, Ajay K Verma, Kouhyar Tavakolian, Mark Romanick
Assessment, treatment, and management of sport-related concussions are a widely recognized public health issue. Although several neuropsychological and motor assessment tools have been developed and implemented for sports teams at various levels and ages, the sensitivity of these tests has yet to be validated with more objective measures to make return-to-play (RTP) decisions more confidently. The present study sought to analyze the residual effect of concussions on a sample of adolescent athletes who sustained one or more previous concussions compared to those who had no concussion history...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226351/-significance-and-contemplation-of-clinical-diagnosis-and-therapy-on-the-renewal-of-the-eighth-edition-of-gastric-cancer-tnm-staging-system
#20
Hongqing Xi, Kecheng Zhang, Bo Wei, Lin Chen
TNM staging is essential for clinical decision-making and prognostic prediction for patients with gastric cancer. The 7th TNM staging manual was formulated in 2009 and implemented in 2010. However, it was published that there were some deficiencies of the 7th edition of gastric cancer TNM staging system in clinical application process, and this old staging system could not meet the clinical needs. With the cooperation and promotion of the American Joint Committee on Cancer (AJCC), the International Union for Cancer Control (UICC) and the International Gastric Cancer Association (IGCA), and through the accumulation and analysis of gastric cancer big data, the 8th TNM staging system was published at the end of 2016...
February 25, 2017: Zhonghua Wei Chang Wai Ke za Zhi, Chinese Journal of Gastrointestinal Surgery
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