scholarly journals Visualizing the Provenance of Personal Data using Comics

2017 ◽  
Author(s):  
Andreas Schreiber ◽  
Regina Struminski
Keyword(s):  
Personal Data ◽  
Cloud Service ◽  
Smartphone Application ◽  
Health Data ◽  
Personal Health ◽  
Data Provenance ◽  
Visualization Technique ◽  
Comic Strips

Personal health data is acquired, processed, stored, and accessed using a variety of different devices, applications, and services. These are often complex and highly connected. Therefore, use or misuse of the data is hard to detect for people, if they are not capable to understand the trace (i.e., the provenance) of that data. We present a visualization technique for personal health data provenance using comics strips. Each strip of the comic represents a certain activity, such as entering data using a smartphone application, storing or retrieving data on a cloud service, or generating a diagram from the data. The comic strips are generated automatically using recorded provenance graphs. The easy-to-understand comics enable all people to notice crucial points regarding their data such as, for example, privacy violations.

scholarly journals The funhouse mirror: the I in personalised healthcare

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Mira W. Vegter ◽  
Hub A. E. Zwart ◽  
Alain J. van Gool
Keyword(s):  
Precision Medicine ◽  
Personal Data ◽  
Health Data ◽  
Personal Health ◽  
Lifestyle Interventions ◽  
Phenotypic Data ◽  
Individual Health ◽  
Data Source ◽  
Tracking Devices ◽  
Personalised Healthcare

AbstractPrecision Medicine is driven by the idea that the rapidly increasing range of relatively cheap and efficient self-tracking devices make it feasible to collect multiple kinds of phenotypic data. Advocates of N = 1 research emphasize the countless opportunities personal data provide for optimizing individual health. At the same time, using biomarker data for lifestyle interventions has shown to entail complex challenges. In this paper, we argue that researchers in the field of precision medicine need to address the performative dimension of collecting data. We propose the fun-house mirror as a metaphor for the use of personal health data; each health data source yields a particular type of image that can be regarded as a ‘data mirror’ that is by definition specific and skewed. This requires competence on the part of individuals to adequately interpret the images thus provided.

scholarly journals Smart Mask – Wearable IoT Solution for Improved Protection and Personal Health

2021 ◽  
Author(s):  
Jarkko Hyysalo ◽  
Sandun Dasanayake ◽  
Jari Hannu ◽  
Christian Schuss ◽  
Mikko Rajanen ◽  
...  
Keyword(s):  
Large Scale ◽  
Personal Data ◽  
Health Data ◽  
Future Research ◽  
Personal Health ◽  
Public Data ◽  
Research Problems ◽  
Health Related ◽  
Treatment Plans ◽  
And Control

<div> <div> <div> <p>The use of face masks is an important way to fight the COVID-19 pandemic. In this paper, we envision the Smart Mask, an IoT supported platform and ecosystem aiming to prevent and control the spreading of COVID-19 and other respiratory viruses. The integration of sensing, materials, AI, wireless, IoT, and software will help gathering of health data and health-related event detection in real time from the user as well as from their environment. In larger scale, with the help of AI-based analysis for health data it is possible to predict and decrease medical costs with accurate diagnoses and treatment plans, where comparison of personal data to large-scale public data enables drawing up a personal health trajectory, for example. Key research problems for smart respiratory protective equipment are identified in addition to future research directions. </p> </div> </div> </div>

scholarly journals Data Control and Surveillance in the Global TB Response: A Human Rights Analysis

2020 ◽  
Vol 2 (1) ◽  
pp. 107-123
Author(s):  
Kat Albrecht ◽  
Brian Citro
Keyword(s):  
Human Rights ◽  
Personal Data ◽  
Health Data ◽  
Case Finding ◽  
Personal Health ◽  
Active Case Finding ◽  
Public And Private ◽  
Active Case ◽  
Data Control ◽  
Colonial Histories

The global response to the tuberculosis (TB) epidemic is generating copious amounts of personal health data. The emerging emphasis on the use of active case finding and digital adherence technologies in the TB response will increase the amount and expand the kind of data produced and used by public and private health officials. The production of personal data in high TB burden countries, in particular, must be considered in light of their colonial histories. In doing so, we argue that interventions to eliminate TB at global and national levels are ushering in a new era of data colonisation and surveillance in the name of public health. This, in turn, raises critical concerns for the human rights of people affected by TB, many of whom belong to vulnerable or marginalised groups. We examine the normative and legal content for a set of international human rights critical to the TB response, highlighting how each right implicates the production and use of personal health data. We also demonstrate that these rights are, by and large, enshrined in the constitutions of each high TB burden country. Finally, we use these rights to analyse active case finding and digital adherence technologies to pinpoint their unique data risks and the threats they pose to the human rights of people affected by TB.

scholarly journals EL CONSENTIMIENTO PARA TRATAMIENTO DE DATOS PERSONALES DE SALUD EN TIEMPOS DEL COVID-19

2020 ◽  
pp. 145-164
Author(s):  
RAÚL VÁSQUEZ RODRÍGUEZ
Keyword(s):  
Data Processing ◽  
Data Protection ◽  
Personal Data ◽  
Emergency Situation ◽  
Health Data ◽  
Fundamental Rights ◽  
Health Protection ◽  
Personal Health ◽  
Constitutional Development ◽  
Personal Data Protection

El presente artículo se centra en la interacción entre los derechos fundamentales a la protección de los datos personales y a la protección de la salud, en el marco de la lucha contra el covid-19 en el Perú. Se inicia el estudio con el desarrollo constitucional de tales derechos, para luego revisar sus respectivas normas legales, teniendo como objetivo esclarecer una de las herramientas básicas que permiten superar los conflictos que se presenten entre ambos en la presente circunstancia de emergencia nacional por el covid-19, concerniente al consentimiento para el tratamiento de datos personales. Adicionalmente, se estudiarán dos casos de tratamiento de datos personales en acciones de prevención del covid-19, que evidencian la pacífica coexistencia entre los derechos constitucionales y los intereses surgidos de la actual situación sanitaria. This paper focuses on interaction between fundamental rights of personal data protection and health protection, in the frame of fighting against covid-19 in Peru. This research begins with constitutional development of those rights, in order to review their related laws, having like an objective clarifying one of their basic legal resources which allow overcome any struggling between those rights during the current emergency state due to covid-19, related to c onsent for personal health data processing. In addition, twocases of personal data processing in preventing covid-19 actions will be studied, which show a peaceful interaction between aforementioned rights and interests arising from current emergency situation.

scholarly journals Assessment of Nursing Students’ Attitudes Towards Recording and Protecting Patients’ Personal Health Data: A Descriptive Study

2021 ◽  
Vol 28 (3) ◽  
pp. E202133
Author(s):  
Sebahat Atalıkoğlu Başkan ◽  
Papatya Karakurt ◽  
Necla Kasımoğlu
Keyword(s):  
Nursing Students ◽  
Data Sharing ◽  
Sample Selection ◽  
Personal Data ◽  
Attitude Scale ◽  
Health Data ◽  
Personal Health ◽  
Academic Level ◽  
Significant Difference ◽  
Students Attitudes

Introduction. Since health information is considered as sensitive personal data and requires more careful protection, healthcare professionals need to be careful about this issue. The objective of this research was to determine nursing students’ attitudes towards recording and protecting patients’ personal health data. Materials and Methods. The population of this descriptive research consisted of 450 students who studied at the Department of Nursing, Faculty of Health Sciences, Erzincan Binali Yildirim University. Sample selection was not used, and the research was completed with 374 students who were continuing education and who were accepted to participate in the research. Descriptive Information template and Attitude Scale for Recording and Protecting Personal Health Data for nursing students were used as data-collection instruments. The numbers, percentage, mean, standard deviation, non-parametric tests (the Mann-Whitney U test and the Kruskal-Wallis test) were used in data analysis. Results. Among our research participants, 68.4% of the students were females; 28.1% of the students were freshmen; 69% of the students were graduates of Anatolian high schools. Approximately 72.5% and 52.9% of the participants stated that they were aware of the concept of “personal data” and “personal health data” , respectively. The mean score of nursing students on the Attitude Scale for Recording and Protecting Personal Health Data was 3.97±0.71. The means scores obtained from subscales were as follows: 3.91±0.72 for Personal Health Data Information, 4.15±0.80 for Legal Information, 4.05±0.94 for Legal Data Sharing, 3.90±0.80 for Personal Health Data Sharing, and 3.77±0.33 for Recording of Personal Health Data, respectively. A statistically significant difference was found between the total scale and subscale scores of the students regarding their academic level. Conclusions. Students were found to have a positive attitude towards recording and protecting personal data. Increasing the responsibilities and raising awareness of the students for the protection of personal health data during their study is suggested to be important.

scholarly journals Smart Mask – Wearable IoT Solution for Improved Protection and Personal Health

2021 ◽  
Author(s):  
Jarkko Hyysalo ◽  
Sandun Dasanayake ◽  
Jari Hannu ◽  
Christian Schuss ◽  
Mikko Rajanen ◽  
...  
Keyword(s):  
Large Scale ◽  
Personal Data ◽  
Health Data ◽  
Future Research ◽  
Personal Health ◽  
Public Data ◽  
Research Problems ◽  
Health Related ◽  
Treatment Plans ◽  
And Control

<div> <div> <div> <p>The use of face masks is an important way to fight the COVID-19 pandemic. In this paper, we envision the Smart Mask, an IoT supported platform and ecosystem aiming to prevent and control the spreading of COVID-19 and other respiratory viruses. The integration of sensing, materials, AI, wireless, IoT, and software will help gathering of health data and health-related event detection in real time from the user as well as from their environment. In larger scale, with the help of AI-based analysis for health data it is possible to predict and decrease medical costs with accurate diagnoses and treatment plans, where comparison of personal data to large-scale public data enables drawing up a personal health trajectory, for example. Key research problems for smart respiratory protective equipment are identified in addition to future research directions. </p> </div> </div> </div>

(Preprint)

2018 ◽  
Author(s):  
Ram Dixit ◽  
Sahiti Myneni
Keyword(s):  
Cancer Survivors ◽  
Mental Models ◽  
Health Systems ◽  
Information Needs ◽  
Health Data ◽  
Information Architecture ◽  
Personal Health ◽  
User Centered Design ◽  
Card Sort ◽  
Connected Health

BACKGROUND Connected Health technologies are a promising solution for chronic disease management. However, the scope of connected health systems makes it difficult to employ user-centered design in their development, and poorly designed systems can compound the challenges of information management in chronic care. The Digilego Framework addresses this problem with informatics methods that complement quantitative and qualitative methods in system design, development, and architecture. OBJECTIVE To determine the accuracy and validity of the Digilego information architecture of personal health data in meeting cancer survivors’ information needs. METHODS We conducted a card sort study with 9 cancer survivors (patients and caregivers) to analyze correspondence between the Digilego information architecture and cancer survivors’ mental models. We also analyzed participants’ card sort groups qualitatively to understand their conceptual relations. RESULTS We observed significant correlation between the Digilego information architecture and cancer survivors’ mental models of personal health data. Heuristic analysis of groups also indicated informative discordances and the need for patient-centric categories relating health tracking and social support in the information architecture. CONCLUSIONS Our pilot study shows that the Digilego Framework can capture cancer survivors’ information needs accurately; we also recognize the need for larger studies to conclusively validate Digilego information architectures. More broadly, our results highlight the importance of complementing traditional user-centered design methods and innovative informatics methods to create patient-centered connected health systems.

scholarly journals Artificial Intelligence in Biomedicine: A Legal Insight

BioTech ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 15
Author(s):  
Takis Vidalis
Keyword(s):  
Artificial Intelligence ◽  
Personal Data ◽  
Health Data ◽  
The Self ◽  
Data Handling ◽  
Direct Control ◽  
Eu Legislation ◽  
Attending Physicians ◽  
Self Learning ◽  
The Eu

The involvement of artificial intelligence in biomedicine promises better support for decision-making both in conventional and research medical practice. Yet two important issues emerge in relation to personal data handling, and the influence of AI on patient/doctor relationships. The development of AI algorithms presupposes extensive processing of big data in biobanks, for which procedures of compliance with data protection need to be ensured. This article addresses this problem in the framework of the EU legislation (GDPR) and explains the legal prerequisites pertinent to various categories of health data. Furthermore, the self-learning systems of AI may affect the fulfillment of medical duties, particularly if the attending physicians rely on unsupervised applications operating beyond their direct control. The article argues that the patient informed consent prerequisite plays a key role here, not only in conventional medical acts but also in clinical research procedures.

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