Strategies for neural networks in ballistocardiography with a view towards hardware implementation

A thesis submitted for the degree of Doctor of Philosophy at the University of LutonThe work described in this thesis is based on the results of a clinical trial conducted by the research team at the Medical Informatics Unit of the University of Cambridge, which show that the Ballistocardiogram (BCG) has prognostic value in detecting impaired left ventricular function before it becomes clinically overt as myocardial infarction leading to sudden death. The objective of this study is to develop and demonstrate a framework for realising an on-line BCG signal classification model in a portable device that would have the potential to find pathological signs as early as possible for home health care. Two new on-line automatic BeG classification models for time domain BeG classification are proposed. Both systems are based on a two stage process: input feature extraction followed by a neural classifier. One system uses a principal component analysis neural network, and the other a discrete wavelet transform, to reduce the input dimensionality. Results of the classification, dimensionality reduction, and comparison are presented. It is indicated that the combined wavelet transform and MLP system has a more reliable performance than the combined neural networks system, in situations where the data available to determine the network parameters is limited. Moreover, the wavelet transfonn requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced. Overall, a methodology for realising an automatic BeG classification system for a portable instrument is presented. A fully paralJel neural network design for a low cost platform using field programmable gate arrays (Xilinx's XC4000 series) is explored. This addresses the potential speed requirements in the biomedical signal processing field. It also demonstrates a flexible hardware design approach so that an instrument's parameters can be updated as data expands with time. To reduce the hardware design complexity and to increase the system performance, a hybrid learning algorithm using random optimisation and the backpropagation rule is developed to achieve an efficient weight update mechanism in low weight precision learning. The simulation results show that the hybrid learning algorithm is effective in solving the network paralysis problem and the convergence is much faster than by the standard backpropagation rule. The hidden and output layer nodes have been mapped on Xilinx FPGAs with automatic placement and routing tools. The static time analysis results suggests that the proposed network implementation could generate 2.7 billion connections per second performance

Parkinson's Disease Management through ICT

Parkinson's Disease (PD) is a neurodegenerative disorder that manifests with motor and non-motor symptoms. PD treatment is symptomatic and tries to alleviate the associated symptoms through an adjustment of the medication. As the disease is evolving and this evolution is patient specific, it could be very difficult to properly manage the disease.The current available technology (electronics, communication, computing, etc.), correctly combined with wearables, can be of great use for obtaining and processing useful information for both clinicians and patients allowing them to become actively involved in their condition.Parkinson's Disease Management through ICT: The REMPARK Approach presents the work done, main results and conclusions of the REMPARK project (2011 – 2015) funded by the European Union under contract FP7-ICT-2011-7-287677. REMPARK system was proposed and developed as a real Personal Health Device for the Remote and Autonomous Management of Parkinson’s Disease, composed of different levels of interaction with the patient, clinician and carers, and integrating a set of interconnected sub-systems: sensor, auditory cueing, Smartphone and server. The sensor subsystem, using embedded algorithmics, is able to detect the motor symptoms associated with PD in real time. This information, sent through the Smartphone to the REMPARK server, is used for an efficient management of the disease

Parkinson's Disease Management through ICT

Parkinson's Disease (PD) is a neurodegenerative disorder that manifests with motor and non-motor symptoms. PD treatment is symptomatic and tries to alleviate the associated symptoms through an adjustment of the medication. As the disease is evolving and this evolution is patient specific, it could be very difficult to properly manage the disease.The current available technology (electronics, communication, computing, etc.), correctly combined with wearables, can be of great use for obtaining and processing useful information for both clinicians and patients allowing them to become actively involved in their condition.Parkinson's Disease Management through ICT: The REMPARK Approach presents the work done, main results and conclusions of the REMPARK project (2011 – 2015) funded by the European Union under contract FP7-ICT-2011-7-287677. REMPARK system was proposed and developed as a real Personal Health Device for the Remote and Autonomous Management of Parkinson’s Disease, composed of different levels of interaction with the patient, clinician and carers, and integrating a set of interconnected sub-systems: sensor, auditory cueing, Smartphone and server. The sensor subsystem, using embedded algorithmics, is able to detect the motor symptoms associated with PD in real time. This information, sent through the Smartphone to the REMPARK server, is used for an efficient management of the disease

GSGS'18 ::3rd Gamification & Serious Game Symposium : health and silver technologies, architecture and urbanism, economy and ecology, education and training, social and politics

The GSGS’18 conference is at the interface between industrial needs and original answers by highlighting the playful perspective to tackle technical, training, ecological, management and communication challenges. Bringing together the strengths of our country, this event provides a solid bridge between academia and industry through the intervention of more than 40 national and international actors. In parallel with the 53 presentations and demos, the public will be invited to participate actively through places of exchange and round tables

Space Station Human Factors Research Review. Volume 3: Space Station Habitability and Function: Architectural Research

Articles are presented on a space station architectural elements model study, space station group activities habitability module study, full-scale architectural simulation techniques for space stations, and social factors in space station interiors

Parkinson's disease management through ICT: the REMPARK approach

Parkinson's Disease (PD) is a neurodegenerative disorder that manifests with motor and non-motor symptoms. PD treatment is symptomatic and tries to alleviate the associated symptoms through an adjustment of the medication. As the disease is evolving and this evolution is patient specific, it could be very difficult to properly manage the disease. The current available technology (electronics, communication, computing, etc.), correctly combined with wearables, can be of great use for obtaining and processing useful information for both clinicians and patients allowing them to become actively involved in their condition. Parkinson's Disease Management through ICT: The REMPARK Approach presents the work done, main results and conclusions of the REMPARK project (2011 - 2015) funded by the European Union under contract FP7-ICT-2011-7-287677. REMPARK system was proposed and developed as a real Personal Health Device for the Remote and Autonomous Management of Parkinson's Disease, composed of different levels of interaction with the patient, clinician and carers, and integrating a set of interconnected sub-systems: sensor, auditory cueing, Smartphone and server. The sensor subsystem, using embedded algorithmics, is able to detect the motor symptoms associated with PD in real time. This information, sent through the Smartphone to the REMPARK server, is used for an efficient management of the disease. Implementation of REMPARK will increase the independence and Quality of Life of patients; and improve their disease management, treatment and rehabilitation.Peer ReviewedPostprint (published version

The Second International Conference on Health Information Technology Advancement

TABLE OF CONTENTS I. Message from the Conference Co-Chairs B. Han and S. Falan …………………………....….……………. 5 II. Message from the Transactions Editor H. Lee …...………..………….......………….……….………….... 7 III. Referred Papers A. Emerging Health Information Technology and Applications The Role of Mobile Technology in Enhancing the Use of Personal Health Records Mohamed Abouzahra and Joseph Tan………………….……………. 9 Mobile Health Information Technology and Patient Care: Methods, Themes, and Research Gaps Bahae Samhan, Majid Dadgar, and K. D. Joshi…………..…. 18 A Balanced Perspective to Perioperative Process Management Jim Ryan, Barbara Doster, Sandra Daily, and Carmen Lewis…..….…………… 30 The Impact of Big Data on the Healthcare Information Systems Kuo Lane Chen and Huei Lee………….…………… 43 B. Health Care Communication, Literacy, and Patient Care Quality Digital Illness Narratives: A New Form of Health Communication Jofen Han and Jo Wiley…..….……..…. 47 Relationships, Caring, and Near Misses: Michael’s Story Sharie Falan and Bernard Han……………….…..…. 53 What is Your Informatics Skills Level? -- The Reliability of an Informatics Competency Measurement Tool Xiaomeng Sun and Sharie Falan.….….….….….….…. 61 C. Health Information Standardization and Interoperability Standardization Needs for Effective Interoperability Marilyn Skrocki…………………….…….………….… 76 Data Interoperability and Information Security in Healthcare Reid Berryman, Nathan Yost, Nicholas Dunn, and Christopher Edwards.…. 84 Michigan Health Information Network (MiHIN) Shared Services vs. the HIE Shared Services in Other States Devon O’Toole, Sean O’Toole, and Logan Steely…..……….…… 94 D. Health information Security and Regulation A Threat Table Based Approach to Telemedicine Security John C. Pendergrass, Karen Heart, C. Ranganathan, and V.N. Venkatakrishnan …. 104 Managing Government Regulatory Requirements for Security and Privacy Using Existing Standard Models Gregory Schymik and Dan Shoemaker…….…….….….… 112 Challenges of Mobile Healthcare Application Security Alan Rea………………………….……………. 118 E. Healthcare Management and Administration Analytical Methods for Planning and Scheduling Daily Work in Inpatient Care Settings: Opportunities for Research and Practice Laila Cure….….……………..….….….….… 121 Predictive Modeling in Post-reform Marketplace Wu-Chyuan Gau, Andrew France, Maria E. Moutinho, Carl D. Smith, and Morgan C. Wang…………...…. 131 A Study on Generic Prescription Substitution Policy as a Cost Containment Approach for Michigan’s Medicaid System Khandaker Nayeemul Islam…….…...……...………………….… 140 F. Health Information Technology Quality Assessment and Medical Service Delivery Theoretical, Methodological and Practical Challenges in Designing Formative Evaluations of Personal eHealth Tools Michael S. Dohan and Joseph Tan……………….……. 150 The Principles of Good Health Care in the U.S. in the 2010s Andrew Targowski…………………….……. 161 Health Information Technology in American Medicine: A Historical Perspective Kenneth A. Fisher………………….……. 171 G. Health Information Technology and Medical Practice Monitoring and Assisting Maternity-Infant Care in Rural Areas (MAMICare) Juan C. Lavariega, Gustavo Córdova, Lorena G Gómez, Alfonso Avila….… 175 An Empirical Study of Home Healthcare Robots Adoption Using the UTUAT Model Ahmad Alaiad, Lina Zhou, and Gunes Koru.…………………….….………. 185 HDQM2: Healthcare Data Quality Maturity Model Javier Mauricio Pinto-Valverde, Miguel Ángel Pérez-Guardado, Lorena Gomez-Martinez, Martha Corrales-Estrada, and Juan Carlos Lavariega-Jarquín.… 199 IV. A List of Reviewers …………………………..…….………………………208 V. WMU – IT Forum 2014 Call for Papers …..…….…………………20