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Showing papers in "Health technology in 2017"


Journal ArticleDOI
TL;DR: A number of lessons are drawn on the transfer of population-derived datasets to large private prospectors, identifying critical questions for policy-makers, industry and individuals as healthcare moves into an algorithmic age.
Abstract: Data-driven tools and techniques, particularly machine learning methods that underpin artificial intelligence, offer promise in improving healthcare systems and services. One of the companies aspiring to pioneer these advances is DeepMind Technologies Limited, a wholly-owned subsidiary of the Google conglomerate, Alphabet Inc. In 2016, DeepMind announced its first major health project: a collaboration with the Royal Free London NHS Foundation Trust, to assist in the management of acute kidney injury. Initially received with great enthusiasm, the collaboration has suffered from a lack of clarity and openness, with issues of privacy and power emerging as potent challenges as the project has unfolded. Taking the DeepMind-Royal Free case study as its pivot, this article draws a number of lessons on the transfer of population-derived datasets to large private prospectors, identifying critical questions for policy-makers, industry and individuals as healthcare moves into an algorithmic age.

301 citations


Journal ArticleDOI
TL;DR: The software solution for tracking the inspection process of medical devices in public and private healthcare institutions is presented and it is used to facilitate gathering of documents such as Inspection Certificates, Working Orders, Measurement Reports, Calculated Errors, and also to keep track of dates for next inspection.
Abstract: With increased sophistication of electrical medical devices and more dynamic working environment conditions, safety and accuracy requirements are becoming more strict. Healthcare institutions are challenged in keeping their electrical medical devices safe to use, accurate and reliable in terms of measuring and monitoring of vital parameters. In healthcare institutions maintaining overall operating functions at the required level of performance can be achieved through periodical safety performance inspections. International guidelines, such as Directives IEC 60601, ISO 62353 and MDD 93/42, define how healthcare institutions should perform these periodical checks. In countries, where those guidelines are not adopted, medical device safety and performance inspections are conducted in accordance to Directives of new approach. This paper presents the software solution for tracking the inspection process of medical devices in public and private healthcare institutions. The software is implemented in Oracle Application Development Framework Technology (ADF) and it is used to facilitate gathering of documents such as Inspection Certificates, Working Orders, Measurement Reports, Calculated Errors, and also to keep track of dates for next inspection. The software can be accessed online via Inspection Laboratory website, and all clients, as well as professional laboratory staff can login using their own username and password which makes all inspection data confidential. The software solution is validated in private and public healthcare institutions in Bosnia and Herzegovina (BH). Out of 331 public and private health care institutions in BH, software solution was validated in 218 institutions and more than 1800 inspection tests reports were imported in software by the date that this paper was written.

47 citations


Journal ArticleDOI
TL;DR: This article focuses on the Republic of India’s national digital biometric identity system, the Aadhaar, for its development, data protection and privacy policies, and impact.
Abstract: It is important that digital biometric identity systems be used by governments with a Do no Harm mandate, and the establishment of regulatory, enforcement and restorative frameworks ensuring data protection and privacy needs to transpire prior to the implementation of technological programs and services. However, when, and where large government bureaucracies are involved, the proper planning and execution of public service programs very often result in ungainly outcomes, and are often qualitatively not guaranteeable. Several important factors, such as the strength of the political and legal systems, may affect such cases as the implementation of a national digital identity system. Digital identity policy development, as well as technical deployment of biometric technologies and enrollment processes, may all differ markedly, and could depend in some part at least, on the overall economic development of the country in question, or political jurisdiction, among other factors. This article focuses on the Republic of India’s national digital biometric identity system, the Aadhaar, for its development, data protection and privacy policies, and impact. Two additional political jurisdictions, the European Union, and the United States are also situationally analyzed as they may be germane to data protection and privacy policies originated to safeguard biometric identities. Since biometrics are foundational elements in modern digital identity systems, expression of data protection policies that orient and direct how biometrics are to be utilized as unique identifiers are the focus of this analysis. As more of the world’s economies create and elaborate capacities, capabilities and functionalities within their respective digital ambits, it is not enough to simply install suitable digital identity technologies; much, much more - is durably required. For example, both vigorous and descriptive means of data protection should be well situated within any jurisdictionally relevant deployment area, prior to in-field deployment of digital identity technologies. Toxic mixes of knowledge insufficiencies, institutional naivete, political tomfoolery, cloddish logical constructs, and bureaucratic expediency must never overrun fundamental protections for human autonomy, civil liberties, data protection, and privacy.

40 citations


Journal ArticleDOI
TL;DR: An approach to Fetal Heart Rate (FHR) classification using pH is presented that could serve as a benchmark for reporting results on the unique open-access CTU-UHB CTG database, the largest and the only freely available database of this kind.
Abstract: Cardiotocography (CTG) is a standard tool for the assessment of fetal well-being during pregnancy and delivery. However, its interpretation is associated with high inter- and intra-observer variability. Since its introduction there have been numerous attempts to develop computerized systems assisting the evaluation of the CTG recording. Nevertheless these systems are still hardly used in a delivery ward. Two main approaches to computerized evaluation are encountered in the literature; the first one emulates existing guidelines, while the second one is more of a data-driven approach using signal processing and computational methods. The latter employs preprocessing, feature extraction/selection and a classifier that discriminates between two or more classes/conditions. These classes are often formed using the umbilical cord artery pH value measured after delivery. In this work an approach to Fetal Heart Rate (FHR) classification using pH is presented that could serve as a benchmark for reporting results on the unique open-access CTU-UHB CTG database, the largest and the only freely available database of this kind. The overall results using a very small number of features and a Least Squares Support Vector Machine (LS-SVM) classifier, are in accordance to the ones encountered in the literature and outperform the results of a baseline classification scheme proving the utility of using advanced data processing methods. Therefore the achieved results can be used as a benchmark for future research involving more informative features and/or better classification algorithms.

38 citations


Journal ArticleDOI
TL;DR: The Australian Data to Decisions Cooperative Research Centre's Law and Policy program as mentioned in this paper discussed the regulation of Big Data, especially focusing on privacy and data protection strategies, and presented four complementary perspectives stemming from governance, law, ethics, and computer science.
Abstract: This article encapsulates selected themes from the Australian Data to Decisions Cooperative Research Centre’s Law and Policy program. It is the result of a discussion on the regulation of Big Data, especially focusing on privacy and data protection strategies. It presents four complementary perspectives stemming from governance, law, ethics, and computer science. Big, Linked, and Open Data constitute complex phenomena whose economic and political dimensions require a plurality of instruments to enhance and protect citizens’ rights. Some conclusions are offered in the end to foster a more general discussion.

31 citations


Journal ArticleDOI
TL;DR: The experiment investigated the effects of different kinds of reminders on adherence to automated parts of a cognitive behavioural therapy for insomnia (CBT-I) delivered via a mobile device and found both types of reminders improved adherence compared to no reminders.
Abstract: The experiment presented in this paper investigated the effects of different kinds of reminders on adherence to automated parts of a cognitive behavioural therapy for insomnia (CBT-I) delivered via a mobile device. Previous studies report that computerized health interventions can be effective. However, treatment adherence is still an issue. Reminders are a simple technique that could improve adherence. A minimal intervention prototype in the realm of sleep treatment was developed to test the effects of reminders on adherence. Two prominent ways to determine the reminder-time are: a) ask users when they want to be reminded, and b) let an algorithm decide when to remind users. The prototype consisted of a sleep diary, a relaxation exercise and reminders. A within subject design was used in which the effect of reminders and two underlying principles were tested by 45 participants that all received the following three different conditions (in random order): a) event-based reminders b) time-based reminders c) no reminders. Both types of reminders improved adherence compared to no reminders. No differences were found between the two types of reminders. Opportunity and self-empowerment could partly mediate adherence to filling out the sleep diary, but not to the number of relaxation exercises conducted. Although the study focussed on CBT-I, we expect that designers of other computerized health interventions benefit from the tested opportunity and self-empowerment principles for reminders to improve adherence, as well.

27 citations


Journal ArticleDOI
TL;DR: Certain critical choices, context, and events connected to the birth and growth of the Estonian e-society in terms of Privacy are discussed.
Abstract: The Republic of Estonia leads Europe in the provision of public digital services. The national communications and transactions platform allows for twenty-first century governance by allowing for transparency, e-safety (inter alia privacy), e-security, entrepreneurship and, among other things, rising levels of prosperity, and well-being for all its Citizens. However, a series of Information Infrastructure attacks against the Estonian e-society infrastructure in 2007 became one of best known incidents and experiences that fundamentally changed both Estonian and international discussions about Cyber Security and Privacy. Estonian experience shows that an open and transparent attitude provides a good foundation for trust between the Citizen and the State, and gives more control to the real owner of the data - the Citizen. Another important lesson is that the Citizen needs to be confident in the government’s ability to keep their data safe -- in terms of confidentiality, integrity and availability - establishing a strong link between privacy and information security. This paper discusses certain critical choices, context, and events connected to the birth and growth of the Estonian e-society in terms of Privacy.

27 citations


Journal ArticleDOI
TL;DR: The case for privacy and emerging legal principles such as accountability and individual control over data about them are summarized, arguing for a Global Friends of Privacy comprising willing regulators, academics and civil society to patrol more vigilantly and to contest more forcefully attempts to ‘salami-slice’ away precious liberties of populations.
Abstract: Privacy matters because everyone needs some portion of their intimate space - whether it is their bodies, their families and relationships, their property or information about them - to remain hidden and secure from unwanted or unexpected external interferences. Privacy is a prerequisite for the enjoyment of other hard-fought freedoms like free speech and non-discrimination on grounds of sex, race, sexual orientation and political and religious beliefs. This universal truism is being questioned in an age where humans are submitting large quantities of traces of themselves, increasingly unwittingly, and as a by-product or condition of their participation in digital life. However, as participation in digital society and the economy becomes all-pervasive, and in effect compulsory, privacy cannot become the preserve of those who can afford it. As memories of the man-made cataclysms of the twentieth century recede, there has never been a greater need for safeguards against unjustified intrusions into people’s personal space by powerful state actors and corporations. Convergence between political malevolence and technological omnipotence is a ‘real and present‘ danger. This article summarises the case for privacy and emerging legal principles such as accountability and individual control over data about them. It argues for a Global Friends of Privacy comprising willing regulators, academics and civil society to patrol more vigilantly and to contest more forcefully attempts to ‘salami-slice’ away precious liberties of populations.

24 citations


Journal ArticleDOI
TL;DR: The paper describes the emerging era of Big Data in the field of health care and focuses on their benefits, challenges and ethics providing a broad overview for healthcare researchers, practitioners and health policy makers and proposed a three-dimensional model for assessing Big Data concerns in the medical context.
Abstract: Our century has been described as the electronic age and every day new technologies or applications, that generate data with exponential rates, are emerged. As a consequence, all and more organizations are facing the problem of managing large amounts of data. Generally, the large amount of data and their handling, storage and analysis is referred as Big Data. The emerging field of Big Data poses many challenges for healthcare organizations, as healthcare data and information increases. The paper describes the emerging era of Big Data in the field of health care and focuses on their benefits, challenges and ethics providing a broad overview for healthcare researchers, practitioners and health policy makers. Furthermore, we proposed a three-dimensional model for assessing Big Data concerns in the medical context. The paper is not intended to be a comprehensive review of the state-of-the-art of Big Data technology, but rather to raise the awareness of the considerations that healthcare professionals may face or will face in the near future.

22 citations


Journal ArticleDOI
TL;DR: It is argued that concrete solutions allowing for DCD already exist and that policy makers should join efforts together with other stakeholders to foster the concrete adoption of the DCD approach.
Abstract: This article claims that the Notice and Consent (N&C) approach is not efficient to protect the privacy of personal data. On the contrary, N&C could be seen as a license to freely exploit the individual’s personal data. For this reason, legislators and regulators around the world have been advocating for different and more efficient safeguards, notably through the implementation of the Privacy by Design (PbD) concept, which is predicated on the assumption that privacy cannot be assured solely by compliance with regulatory frameworks. In this sense, PbD affirms that privacy should become a key concern for developers and organisations alike, thus permeating new products and services as well as the organisational modi operandi. Through this paper, we aim at uncovering evidences of the inefficiency of the N&C approach, as well as the possibility to further enhance PbD, in order to provide the individual with increased control on her personal data. The paper aims at shifting the focus of the discussion from “take it or leave it” contracts to concrete solutions aimed at empowering individuals. As such, we are putting forth the Data Control by Design (DCD) concept, which we see as an essential complement to N&C and PbD approaches advocated by data-protection regulators. The technical mechanisms that would enable DCD are currently available (for example, User Managed Access (UMA) v1.0.1 Core Protocol). We, therefore, argue that data protection frameworks should foster the adoption of DCD mechanisms in conjunction with PbD approaches, and privacy protections should be designed in a way that allows every individual to utilise interoperable DCD tools to efficiently manage the privacy of her personal data. After having scrutinised the N&C, PbD and DCD approaches we discuss the specificities of health and genetic data, and the role of DCD in this context, stressing that the sensitivity of genetic and health data requires special scrutiny from regulators and developers alike. In conclusion, we argue that concrete solutions allowing for DCD already exist and that policy makers should join efforts together with other stakeholders to foster the concrete adoption of the DCD approach.

21 citations


Journal ArticleDOI
TL;DR: This service builds on the existing work in the United Kingdom in seeking to establish the motivations for different stakeholders to become involved and therefore assisting in prioritising the use-cases based on the level of need and support within the research community.
Abstract: The domain of biobanking has gone through many stages and as a result there are a wide range of commercial and open source software solutions available. The utilization of these software tools requires different levels of domain and technical skills for installation, configuration and ultimate us of these biobank software tools. To compound this complexity the biobanking community are required to work together in order to share knowledge and jointly build solutions to underpin the research infrastructure. We have evaluated the available tools, described them in a catalogue (BiobankApps) and made a selection of tools available to biobanks in a reference toolbox (BIBBOX) that are use-case driven. In the BiobankApps tool catalogue, both commercial and open source software solutions related to the biobanking domain are included, classified and evaluated. The evaluation covers: 1) "user review" by an authenticated user 2) domain expert: quick analysis by BBMRI members and 3) domain expert: detailed analysis and test installation with real world data. The evaluation is paired with a survey across the more "advanced" (from a technology perspective) biobanks to investigate what tools are currently used and summarises known benefits/drawbacks of the respective packages. In the second step we recommend tools for specific use cases, and install, configure and connect these in the BIBBOX framework. This service also builds on the existing work in the United Kingdom in seeking to establish the motivations for different stakeholders to become involved and therefore assisting in prioritising the use-cases based on the level of need and support within the research community. All tools associated to a use-case are available as BIBBOX applications (technically this is achieved by docker containers), which are integrated in the BIBBOX framework with central identification and user management. In future work we plan to share the acquired knowledge with other networks, develop an Application Programmable Interface (API) for the exchange of metadata with other tool catalogues and work on an ontology for the evaluation of biobank software.

Journal ArticleDOI
TL;DR: The results demonstrate that the Fuzzy Expert System has the high ability to diagnose the patient based on the records with a high percentage of accuracy and can be efficiently used for diagnosing the Chronic Heart Disease (CHD)based on the medical records in Jordan.
Abstract: According to recently published research survey, Coronary Heart Diseases (CHD) are becoming a major severe health problem for Jordanians, where the number of deaths by CHD is 4329 out of 22,784 deaths in Jordan which forms a percentage of 18.8%. More specifically, CHD accounted for 18% of the overall mortality in Jordan. Using a fuzzy logic system which is a common approach for computing based on “degrees of truth” or non-crisp values. Nowadays, applying advanced computer technology systems in the medicine fields for diagnosis and treatment purposes is becoming more common for accuracy analysis. Therefore, the aim of this study is to detect heart diseases in subjects by using Fuzzy Expert System using visual studio 2010 with C#. A windows application fuzzy-based system was applied to diagnose the severity of the heart disease of a patient using existing data in the common medical records in Jordan. The results show that the system can be efficiently used for diagnosing the Chronic Heart Disease (CHD) based on the medical records in Jordan. The results demonstrate that the system has the high ability to diagnose the patient based on the records with a high percentage of accuracy.

Journal ArticleDOI
TL;DR: This work evaluated eight methods for deriving respiration rate from EIP signals measured from 15 subjects in three conditions: standing, walking slowly, and walking fast and showed that advanced counting method is the most promising approach among the ones studied in this work.
Abstract: Respiration rate (RR) is considered as a useful parameter in characterizing the health condition of a person. Among the methods used for respiration measurement, Electrical Impedance Pneumography (EIP) can be easily obtained in wearable applications due to the possibility of using the electrocardiography (ECG) electrodes for the EIP measurement. In the fast growing field of wearable devices, having clinically valuable and reliable information along with providing the convenience of the user, is probably the most important and challenging issue. To address the need of small sized devices for ECG (and EIP) measurements, EASI electrode configuration is an acceptable solution. The signals from EASI system not only provide useful information by themselves when directly used for cardiological analyses, but can also be converted to the standard 12-lead ECG information. With aforementioned advantages of EASI system, the question then arises how suitable the electrode locations of the system are for EIP measurements and what algorithms perform better for respiration rate derivation. In this work, we evaluated eight methods for deriving respiration rate from EIP signals measured from 15 subjects (10 males +5 females) in three conditions: standing, walking slowly, and walking fast. The algorithms were autoregressive (AR) modeling (three different approaches), Fast Fourier Transform (FFT), autocorrelation, peak detection and two counting algorithms. Our results show that advanced counting method is the most promising approach among the ones studied in this work. For this algorithm, the concordance correlation coefficients of the respiration rate estimates between EIP and the reference measurement were 0.96, 0.90 and 0.97 for standing, walking with 3 km/h speed, and walking with 6 km/h speed, respectively.

Journal ArticleDOI
TL;DR: In this paper, the authors address the problem of constructing a public space to build sustainable data ecosystems for the biomedical field, where privacy and data protection can be explored in connection with the existing ethical frameworks for Public Health Data, and the Theory of Justice.
Abstract: This article addresses the problem of constructing a public space to build sustainable data ecosystems for the biomedical field It outlines three models of democracy —deliberative, epistemic, and linked— where privacy and data protection can be explored in connection with the existing ethical frameworks for Public Health Data, and the Theory of Justice For the construction of a sustainable public space, it suggests exploring the analytical dimension of Linked Democracy, and the need for building new tools to regulate ‘Linked Open Data’, based on rule of law and the analytical dimension of the meta-rule of law The construction of ‘intermediate’ or ‘anchoring’ institutions would help in embedding the protections of the rule of law into specific ecosystems (including direct, indirect and tactic modelling of privacy by design)


Journal ArticleDOI
TL;DR: The wishes and needs of people with type 2 diabetes (T2DM) for a future information and communication technology (ICT) self-management service to help manage their condition and their everyday life are reported.
Abstract: This paper reports the wishes and needs of people with type 2 diabetes (T2DM) for a future information and communication technology (ICT) self-management service to help manage their condition and ...

Journal ArticleDOI
TL;DR: This paper attempts to comprehensively review the current status of research and development of RPMS which measures physiological parameters continuously and sends the data to the healthcare professionals wirelessly in real time.
Abstract: In rural areas, people die at their early ages because of lack of proper facilities and infrastructure for monitoring patient’s health at the right time. Therefore, the design and development of a Remote Patient Monitoring System (RPMS) has a lot of significance in the scientific community and industry for the last few years. Nowadays, researchers give importance to wearable low cost RPMS which measure the body parameters in real time by using non invasive methods. This paper attempts to comprehensively review the current status of research and development of RPMS which measures physiological parameters continuously and sends the data to the healthcare professionals wirelessly in real time. The aim of this survey is to provide a reference for researchers and developers in this area to give direction for future research improvements.

Journal ArticleDOI
TL;DR: Performance of RF has been investigated as feature selection and classification in splice site domain and shows that the RF outperforms the SVM when the same Markovian encoding methods are used on both donor and acceptor datasets.
Abstract: Gene identification has been an increasingly important task due to developments of Human Genome Project. Splice site prediction lies at the heart of identifying human genes, thus development of new methods which detect the splice site accurately is crucial. Machine learning classifiers are utilized to detect the splice sites. Performance of those classifiers mainly depends on DNA encoding methods (feature extraction) and feature selection. The feature extraction methods try to capture as much information as the DNA sequences have, while the feature selection methods provide useful biological knowledge by cleaning out the redundant information. According to the literature, Markovian models are popular encoding methods and the support vector machine (SVM) is known as the best algorithm for classification of splice sites. However, random forest (RF) may outperform the SVM in this domain using those Markovian encoding methods. In this study, performance of RF has been investigated as feature selection and classification in splice site domain. We proposed three methods, namely MM1-RF, MM2-RF and MCM-RF by combining RF with first order Markov Model (MM1), second order Markov model (MM2), and Markov Chain Model (MCM). We compared the performance of the RF with the SVM competitively on HS3D and NN269 benchmark datasets. Also, we evaluated the efficiency of the proposed methods with other current state of arts methods such as Reduced MM1-SVM, SVM-B and LVMM2. The experimental results show that the RF outperforms the SVM when the same Markovian encoding methods are used on both donor and acceptor datasets. Furthermore, the RF classifier performs much faster than the SVM classifier in detecting the splice sites.

Journal ArticleDOI
Jane Reichel1
TL;DR: This article investigates the role of national oversight bodies in the transfer of health data in cross-border research, from an EU law point of view, in the light of the recently enacted EU-US Privacy Shield.
Abstract: The notion of privacy has long had a central role in human rights law, not least in connection to health and medicine. International, regional and national bodies have enacted a number of binding and non-binding document for physicians and researchers to adhere to, in order to protect the autonomy, dignity and privacy of patients and research subjects. With the development of new technologies, the right to privacy has gained a new perspective; the right to protection of personal data within information and communication technologies. The right to data protection has been attributed an increasing importance within EU law. Accordingly, the use of health data in medical research in general and in biobank-related medical research in particular, has made data protection law highly relevant. In medical research involving biobanks, transferring human biological samples and/or individual health data is taking place on a daily basis. These transfers involve several oversight bodies, institutional review boards (IRBs), research ethics committees, or even data protection authorities. This article investigates the role of these national oversight bodies in the transfer of health data in cross-border research, from an EU law point of view. A special focus is laid on transfer of health data for research purposes from the EU to the US, in the light of the recently enacted EU-US Privacy Shield. The main question posed is how American oversight bodies for medical research can be expected to handle the increasingly strict EU requirements for the processing of health data in medical research review.

Journal ArticleDOI
TL;DR: A classifier composed by 3 Artificial Neural Networks (ANN) able to distinguish between malignant and healthy areas through a voting strategy is developed able to improve the performance of a CAD system in term of reduction of FPs findings, without affecting the sensitivity.
Abstract: Prostate cancer (PCa) is the most common cancer afflicting men in USA. Multiparametric Magnetic Resonance imaging is recently emerging as a powerful tool for PCa diagnosis, but its analysis and interpretation is time-consuming and affected by the radiologist experience. Computer aided detection (CAD) systems have been developed to overcome this limitation and to support radiologists in the PCa diagnosis. Although several studies proposed CAD systems with very high performances in terms of sensitivity, the analysis of false positive (FP) areas is usually not clearly presented. The aim of this study is to improve the performance of a CAD system in term of reduction of FPs findings, without affecting the sensitivity. To this scope, we developed a classifier composed by 3 Artificial Neural Networks (ANN) able to distinguish between malignant and healthy areas through a voting strategy. In this method, we exploit the role of the Gray Level Co-occurrence Matrix, the Gray Level Difference Method and Gray Level Run Length Method Matrix in differentiating tumoural from healthy tissues. We first extract 64 textural features from T2-weighted (T2w) images and the apparent diffusion coefficient (ADC) maps, then we discretized them to reduce the data variability. A features selection method, based on the correlation matrix, is finally applied to remove redundant variables, that are those highly correlated with others. The remaining set of features is fed into the three ANNs and a post-processing step is applied to remove very small areas. Results applied on a dataset of 58 patients showed a significant decrease of FPs (20 vs 12; p-value < 0.0001) and an increase of the precision of PCa segmentation (0.62 vs 0.71; p-value < 0.0001). Having less FPs is helpful to increase the performance of CAD systems in terms of specificity and to decrease the reporting time of radiologists. Moreover, having more precise PCa segmentation areas could be useful if a step of PCa characterization will be added to the CAD system.

Journal ArticleDOI
TL;DR: Aadhyay et al. as discussed by the authors pointed out that India is known the world over for many wondrous details; history of human origins, languages, mathematics, medicine, music, foods, culture, scenic beauty, landmarks, diversity of peoples, climates, contrasts and above all, spirituality.
Abstract: India is known the world over for many wondrous details; history of human origins, languages, mathematics, medicine, music, foods, culture, scenic beauty, landmarks, diversity of peoples, climates, contrasts and above all, spirituality. More recently, however, India, and the distressing privacy annulling actions on the sub-continent have become the chief discussion point among those in the world who are alarmed over the ways in which personal privacy is being encroached upon by moneyed interests of all variety, and by those governments who are willing to collude with them, under false pretenses. In a nation with nearly 1.4 billion people, one readily identified as the world’s largest democracy, forces are now at work, arbitrarily, autocratically, undemocratically, and unconstitutionally deploying, what has come to be known as the world’s largest biometric national ID program (scans and captures iris, fingerprints and facial inputs into a government database), called The Aadhaar. The Aadhaar, initially sold to the tax-payer as a program only to exist per volunteer citizen participation, has speedily, and in the span of less than 2 years, gone from being that volunteer participation program, to a “you must enroll” program, intent on siphoning a citizen’s most personal information into government custody. More importantly, the government, against initial Supreme Court ruling, is now actively pushing for the widespread adoption of the Aadhaar into every segment of the Indian Society, without any constitutional reading, deliberation or ruling. As a member of the national parliament, and as the only opposing voice to the implementation of the Aadhaar, in a chamber of 545 members, the author aims to candidly introduce the reader to the leading issues that are enabling the Central government and moneyed interests to collude, and to suppress democratic processes to ramrod the Aadhaar legislation through the parliament as a ‘money bill,’ and what this Indian program and experience could herald.

Journal ArticleDOI
TL;DR: In this paper, the authors point out that privacy is a deeply misunderstood concept; one that is experienced, protected, defended, adjudicated, and enforced in highly inconsistent ways across legislative, judicial, cultural, linguistic, economic, social, racial, ethnic and inter-national boundaries.
Abstract: More than 4 decades ago, Sociologist Daniel Bell in “The Coming of Post-industrial Society” [1] attempted to draw people’s attention to the impending transit of the United States’ from a smoke-stack, assembly line-industrial economy to something different – quite different, a knowledge intensive creative economy, where entirely different skill-sets than those the ‘educational factories’ were dispensing to “future workforces” would be needed. Fundamentally, Information and Communications Technology (ICT) tool-chest dominated ‘knowledge creation’ economies were going to present different societal challenges. 24 years later, at the dawn of a new millennium, Sir Leon Brittan, thenVice-President of the EuropeanCommission, speaking at the EU-Japan Cooperation Week in Tokyo lamented that the EuropeanCommunitywas“...managing a difficult transition to becoming post-industrial societies with aging populations” [2]. To be sure, in his speech, Sir Leon was surely not ruling out mal-adjustment among other nations outside the European Community. From germane observations, 20 more years beyond Sir Leon’s speech that day, all are still wrestling poorly with key transitional pathways into post-industrial societies. History will judge humanity as not having been well equipped to deal with the self-created problems of the industrial world [3]. Could we blindly expect humankind to be anticipatory, and be prepared to deal with challenges we summon and make plain in a post-smokestack world? Beyond the historicity of the Industrial Revolution’s burning waters itself, is that ever unfamiliar ‘transition phase’ from one world into the next, where aging and inadaptive populations, failing educational systems and new skill-set demands, new thought directions, failure to systemically understand changes occurring at societal components, and associated interfaces have only exacerbated running issues related to Personal Privacy and Security. Privacy is a deeply misunderstood concept; one that is experienced, protected, defended, adjudicated, and enforced in highly inconsistent ways across legislative, judicial, cultural, linguistic, economic, social, racial, ethnic and inter-national boundaries. Likewise, and to make matters worse, generally, parties fail to understand and to represent correctly, the linkage/relationship between privacy and security in models spoken of, or in those models that are employed in society. This aforementioned lack of understanding and representation is at least in significant parts, connectable to states of global transitions to informational societies, and attributable to our inability to transit, and acclimatize to a post-industrial world. Collectively, given the aforementioned paradoxes, where, pervading failures to understand the meaning of

Journal ArticleDOI
TL;DR: In this paper, the authors present a ministerial view that one should not have to trade-off between privacy and security, or be told to give-up privacy for safety, and this declaration is foundationally germane to Rwanda's digital transformation, and our society's approach to erecting Privacy protections, harnessing the deep value that Privacy had once held in Rwanda's pre-colonial tradition, and has again, in her most recent history.
Abstract: The Information and Communication Technology (ICT) revolution has brought considerable socio-economic benefits to humanity over the last 50 years. However, one of its side effects has been an increased threat to personal privacy owing to the widespread use of digital services that make utility of personal information, the extreme ease with which that information is captured, transmitted, analyzed and stored coupled with the incentives for a range of actors to misuse the information at their disposal or reach. This article presents a ministerial view that one should not have to trade-off between privacy and security, or be told to give-up privacy for safety. In part, this declaration is foundationally germane to Rwanda’s digital transformation, and our society’s approach to erecting Privacy protections, harnessing the deep value that Privacy had once held in Rwanda’s pre-colonial tradition, and has again, in her most recent history. In view of a rapid transformation that is presently turning the country into a digital hub for the Continent of Africa, Rwanda is charting a path forward to achieve a double purpose; on one hand the prospect of leveraging information technology for the benefits of her citizens, and on the other hand, securing and protecting the privacy of her citizens, as a key component of Rwanda’s societal identity. This article further presents that given the leadership that Rwanda has demonstrated in Information and Communication Technology (ICT) for Development in Africa, the nation’s course of action in relation to data and personal privacy protection will have a positive influence on the rest of the African continent that is now bracing to form a single digital market through the Continent-wide Smart Africa initiative.

Journal ArticleDOI
TL;DR: Results indicate that the use of the mobility monitoring system can improve the assessment of night-time mobility and activity supporting nurses in planning and implementing care interventions such as repositioning, continence care and inspection rounds.
Abstract: Sleep disturbances are common in nursing homes residents with dementia. In this study, the use of a mobility monitoring system accompanied with case conferences was investigated in order to improve sleep quality in nursing home residents with cognitive impairment. An open two-phase randomized controlled trial was conducted at three nursing homes between November 2014 and September 2015. Residents were randomly assigned to an intervention group using the monitoring system and a control group not using the system. A 10-week period of intensive use of the monitoring system and case conferences led by an advanced nurse practitioner (Phase I) was followed by three months of reduced use of the monitoring system and case conferences led by an internal registered nurse (Phase II). Data were collected before intervention started (T0), after Phase I (T1) and after Phase II (T2). The night shift nurse in charge rated the residents’ sleep quality on a four point scale over five subsequent nights. Data from 44 residents were included in the analysis with a linear mixed model. We observed a significant interaction between the time and groups with a more pronounced increase in sleep quality in the intervention group in T1, but a decrease in T2. Sleep quality in the control group stayed almost stable (F = 3.566, p = 0.034). Results indicate that the use of the mobility monitoring system can improve the assessment of night-time mobility and activity supporting nurses in planning and implementing care interventions such as repositioning, continence care and inspection rounds.

Journal ArticleDOI
TL;DR: Density based clustering algorithms are applied to the data to provide long-term insights into how the high density regions change over time, suggesting that this form of evaluation has strong potential in the analysis of cognitive and physical status deterioration.
Abstract: Recently much research has been conducted on early detection of cognitive and physical status deterioration in elderly adults. Primarily the focus is on gait analysis methodologies exploiting average speed, however this presents an issue when used for context aware applications. Additionally data capture tends to be in short bursts over a long period, allowing for localized temporal factors, such as short term injury, to potentially skew measurements. As such this work collects gait and trajectory IoT data from elderly adults in senior homes (“in the wild”) over a sustained period of time (1 year). Density based clustering algorithms are then applied to the data to provide long-term insights into how the high density regions change over time. The data is collected, analyzed and made available by the indoor analytics client utilizing available processing resources and delivers the analytics outcome even when it is hosted in hardware with constrained resources. Promising results are obtained from the long-term study, suggesting that this form of evaluation has strong potential in the analysis of cognitive and physical status deterioration.

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TL;DR: A novel means of detecting OSA is developed using standard measures of heart rate (ECG) and respiration (chest wall motion traces) performed by clinical personnel with standardly available monitoring equipment to test the hypothesis that these measures could differentiate between subjects with sleep apnea and non-OSA healthy adults of the same age.
Abstract: There is a strong relationship between sleep apnea, hypertension and cardiovascular disease. Traditionally, sleep apnea is diagnosed by overnight sleep study performed in a certified sleep laboratory, which is both costly and inconvenient. As a result, 100,000 s of adults with sleep apnea go undiagnosed each year at an annual estimated economic cost of $165 billion dollars in the United States alone. In this study, we explored sleep apnea related cardiorespiratory variability with the objective of devising a novel tool that could be used to detect sleep apnea in the very early stages of the disease well before progression to hypertension. Respiration-related expansion of the chest wall and heart rate were recorded during rest breathing in subjects diagnosed with moderate obstructive sleep apnea (n = 9) and in healthy aged matched adults (n = 11). Using a correlation between the chest wall motion and heart rate variability, we were able to detect marked differences in sleep apnea patients relative to healthy aged matched adults (P < 0.001). We developed a novel means of detecting OSA using standard measures of heart rate (ECG) and respiration (chest wall motion traces) performed by clinical personnel with standardly available monitoring equipment. Most importantly, we wanted to devise a tool that could detect OSA in awake individuals in <10 min. Diagnosis of sleep apnea and cardiorespiratory variability typically depend on time consuming measurements obtained during sleep. In this case we used RR variability and the correlation between the chest wall trace and heart rate variability to test the hypothesis that these measures could differentiate between subjects with sleep apnea and non-OSA healthy adults of the same age. Using these parameters, we were able to detect differences between healthy and OSA subjects in very short time windows (~ 2 min) during rest breathing in wakefulness and using vital signs monitoring devices available in most hospitals.

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TL;DR: A method for detecting possible neuropathy or myopathy cases of a subject based on surface electromyograms signals, and it is safe to state that based on the different tests performed, it is a robust approach for the classification of subjects.
Abstract: The present study introduces a method for detecting possible neuropathy or myopathy cases of a subject based on surface electromyograms signals; the same method has been developed as a classification tool for movements of the upper arm. This research is proposed for its capability to classify subjects from a clinical dataset in healthy, myopathic and neuropathic cases. The extraction of features with simple morphology but estimated on the signals wavelet domain increases the classification rate of the system drastically. Therefore, a set of features based mainly on energies of the EMG signals along with the Hudgins’ measurements, all estimated on the wavelet domain create a feature space consisted of highly discriminant subspaces for the three classes healthy, neuropathies or patients with myopathies. For the classification task the k-NN algorithm used and the validation performed with k-folds method; the predictions for the performance on unknown data was close to the actual validation results. Overall accuracy of the system for all three classes is 98.36 ± 0.79%, and it is safe to state that based on the different tests performed, it is a robust approach for the classification of subjects.



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TL;DR: In this article, the concept of privacy, as a legal term and a human right, and judicial remedies to enforce the right before national authorities are discussed. But the authors do not address how to find a fair balance between the competing public and private interests is a complicated task.
Abstract: The right to privacy generally belongs to constitutionally protected rights and is listed with fundamental human rights in international human rights instruments. Personal health information is particularly important element of private life, and health data is defined and accepted as sensitive personal data. Modern computer and information technology is capable of processing enormous amounts of data concerning health, which entails a growing risk of violations of privacy by both public authorities and private entities. This article addresses the concept of privacy, as a legal term and a human right, and judicial remedies to enforce the right before national authorities. Whereas no single comprehensive federal law exists in the US for instance, regulating the collection and use of personal data, European states have adopted an extensive regulatory framework on the issue. The European Court of Human Rights in Strasbourg has repeatedly confirmed that information about a person’s health is an important element of one’s private life. Accordingly, processing of health information is an interference with the right to privacy, which may however be justified with a reference to public interests such as scientific research, subject to certain legal requirements. Finding a fair balance between the competing public and private interests is a complicated task. A case study will be made of Iceland, where the European treaties and regulations on protection of personal data have been implemented into domestic law. The Icelandic courts have resolved questions related to processing of health data and violations of privacy, and inter alia declared unconstitutional, legislation on the establishment of a centralised health sector database. This illustrates how legislation, accompanied with effective individual access to the courts, may offer legal reliefs to individuals claiming violation of their right to privacy.