Dynamic Message Server for Personal Health Data Transmission in u-Health Service Environment

2011 ◽  
pp. 459-466
Author(s):  
Eun Jeong Choi ◽  
Hee Joung Hwang
Keyword(s):  
Health Service ◽  
Data Transmission ◽  
Health Data ◽  
Personal Health ◽  
Service Environment

scholarly journals A Data Transmission Technique for Personal Health Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Jih-Fu Tu ◽  
Chih-yung Chen
Keyword(s):  
Health Systems ◽  
Data Transmission ◽  
Health Data ◽  
Functional Integral ◽  
Personal Health ◽  
The Core ◽  
Transmission Technique ◽  
Cloud Server

We used the modular technique to design a personal health data transmitter (PHDT) that is composed of the following components: (1) the core is an embedded signal chip, (2) three kinds of transmutation modules such as USB, RF, and UART, (3) an I2C interface is used to acquire the users data, and (4) through Internet it links to the cloud server to store the personal-health data. By the experiment, we find that the modular manner is feasible, stable of functional, integral, and accurate, while it is exploited to design the PHDT. For the experiment, we present each module algorithm to find that our system is very helpful to people.

(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.

NATIONAL OR PERSONAL HEALTH SERVICE?

The Lancet ◽  
1967 ◽  
Vol 289 (7501) ◽  
pp. 1223-1224
Author(s):  
Arthur Seldon
Keyword(s):  
Health Service ◽  
Personal Health

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 Public Interest, Health Research and Data Protection Law: Establishing a Legitimate Trade-Off between Individual Control and Research Access to Health Data

Laws ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Mark J. Taylor ◽  
Tess Whitton
Keyword(s):  
Public Interest ◽  
Data Protection ◽  
Health Research ◽  
Health Data ◽  
Personal Health ◽  
Positive Contribution ◽  
Data Governance ◽  
The Public ◽  
Individual Control ◽  
Data Protection Law

The United Kingdom’s Data Protection Act 2018 introduces a new public interest test applicable to the research processing of personal health data. The need for interpretation and application of this new safeguard creates a further opportunity to craft a health data governance landscape deserving of public trust and confidence. At the minimum, to constitute a positive contribution, the new test must be capable of distinguishing between instances of health research that are in the public interest, from those that are not, in a meaningful, predictable and reproducible manner. In this article, we derive from the literature on theories of public interest a concept of public interest capable of supporting such a test. Its application can defend the position under data protection law that allows a legal route through to processing personal health data for research purposes that does not require individual consent. However, its adoption would also entail that the public interest test in the 2018 Act could only be met if all practicable steps are taken to maximise preservation of individual control over the use of personal health data for research purposes. This would require that consent is sought where practicable and objection respected in almost all circumstances. Importantly, we suggest that an advantage of relying upon this concept of the public interest, to ground the test introduced by the 2018 Act, is that it may work to promote the social legitimacy of data protection legislation and the research processing that it authorises without individual consent (and occasionally in the face of explicit objection).

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