1,197,355 research outputs found

    The Ethical Implications of Personal Health Monitoring

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    Personal Health Monitoring (PHM) uses electronic devices which monitor and record health-related data outside a hospital, usually within the home. This paper examines the ethical issues raised by PHM. Eight themes describing the ethical implications of PHM are identified through a review of 68 academic articles concerning PHM. The identified themes include privacy, autonomy, obtrusiveness and visibility, stigma and identity, medicalisation, social isolation, delivery of care, and safety and technological need. The issues around each of these are discussed. The system / lifeworld perspective of Habermas is applied to develop an understanding of the role of PHMs as mediators of communication between the institutional and the domestic environment. Furthermore, links are established between the ethical issues to demonstrate that the ethics of PHM involves a complex network of ethical interactions. The paper extends the discussion of the critical effect PHMs have on the patient’s identity and concludes that a holistic understanding of the ethical issues surrounding PHMs will help both researchers and practitioners in developing effective PHM implementations

    A remote sensor for electromagnetic personal safety monitoring

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    Abstract: Citizens are often afraid of electromagnetic fields. This creates a need for logging and quantifying the exposure to fields in the civil environment. An electromagnetic field strength sensor (from 1MHz to 1GHz) has been developed which is connected to a logging system and a modem. The systems output level is independent of frequencies i.e. follows the standards limit curve. It can be powered by solar cells. So it can operate without human interaction anywhere. The system can emit a warning when the exposure level is exceeded. In normal mode, it transmits the logged levels once per week to a central data collection system. This paper describes the design and operation of the system

    A 64-channel, 1.1-pA-accurate on-chip potentiostat for parallel electrochemical monitoring

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    Electrochemical monitoring is crucial for both industrial applications, such as microbial electrolysis and corrosion monitoring as well as consumer applications such as personal health monitoring. Yet, state-of-the-art integrated potentiostat monitoring devices have few parallel channels with limited flexibility due to their channel architecture. This work presents a novel, widely scalable channel architecture using a switch capacitor based Howland current pump and a digital potential controller. An integrated, 64-channel CMOS potentiostat array has been fabricated. Each individual channel has a dynamic current range of 120dB with 1.1pA precision with up to 100kHz bandwidth. The on-chip working electrodes are post-processed with gold to ensure (bio)electrochemical compatibility

    A realisation of ethical concerns with smartphone personal health monitoring apps

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    The pervasiveness of smartphones has facilitated a new way in which owners of devices can monitor their health using applications (apps) that are installed on their smartphones. Smartphone personal health monitoring (SPHM) collects and stores health related data of the user either locally or in a third party storing mechanism. They are also capable of giving feedback to the user of the app in response to conditions are provided to the app therefore empowering the user to actively make decisions to adjust their lifestyle. Regardless of the benefits that this new innovative technology offers to its users, there are some ethical concerns to the user of SPHM apps. These ethical concerns are in some way connected to the features of SPHM apps. From a literature survey, this paper attempts to recognize ethical issues with personal health monitoring apps on smartphones, viewed in light of general ethics of ubiquitous computing. The paper argues that there are ethical concerns with the use of SPHM apps regardless of the benefits that the technology offers to users due to SPHM apps’ ubiquity leaving them open to known and emerging ethical concerns. The paper then propose a need further empirical research to validate the claim

    Project HealthDesign: Rethinking the Power and Potential of Personal Health Records: Round One Final Report

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    Describes an initiative to develop prototypes for next-generation personal health record applications on a common platform focused on self-management for better health. Outlines grantees' prototypes for user-centered daily monitoring and lessons learned

    Factors effecting an obesity reduction treatment programme in a secondary school : a thesis presented in partial fulfilment of the requirements for the degree of Master of Arts in Applied Psychology at Massey University /

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    The present study examined the effects of a 21 week programme on 9 obese adolescents in a school setting. The study's theme was chosen because research in the area of adolescent obesity is sparse. Self monitoring of intake, self monitoring of increased exercise, varying frequency of weighings and continuing instruction in the behavioural control of eating were used. Varying measures were examined to try to find predictors of the Ss' success probabilities and to describe psychological aspects associated with adolescent obesity. Significant correlations with weight loss indicated that: (a) gains in personal adjustment followed weight loss; (b) California Test of Personality Scores and Primary School Record Personal Effort Scores, were good predictors of success; (c) degree of self monitoring of intake and degree of family support were closely associated with success; It was found that: (d) increased exercise output was an important factor; (e) trends were present showing improved academic performance following weight loss; (f) obese adolescents had significantly more absences from school and were high risks for truancy and premature termination of schooling. These findings were discussed relative to the literature on obesity

    Ontology based annotation of contextualized vital signs

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    Representing the kinetic state of a patient (posture, motion, and activity) during vital sign measurement is an important part of continuous monitoring applications, especially remote monitoring applications. In contextualized vital sign representation, the measurement result is presented in conjunction with salient measurement context metadata. We present an automated annotation system for vital sign measurements that uses ontologies from the Open Biomedical Ontology Foundry (OBO Foundry) to represent the patient’s kinetic state at the time of measurement. The annotation system is applied to data generated by a wearable personal status monitoring (PSM) device. We demonstrate how annotated PSM data can be queried for contextualized vital signs as well as sensor algorithm configuration parameters

    A look into the information your smartphone leaks

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    The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Some smartphone applications (apps) pose a risk to users’ personal information. Events of apps leaking information stored in smartphones illustrate the danger that they present. In this paper, we investigate the amount of personal information leaked during the installation and use of apps when accessing the Internet. We have opted for the implementation of a Man-in-the-Middle proxy to intercept the network traffic generated by 20 popular free apps installed on different smartphones of distinctive vendors. This work describes the technical considerations and requirements for the deployment of the monitoring WiFi network employed during the conducted experiments. The presented results show that numerous mobile and personal unique identifiers, along with personal information are leaked by several of the evaluated apps, commonly during the installation process

    Personal Hand Safety Monitoring System

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    Techniques for monitoring user hand health and safety, estimating risks associated with user hand activity, and generation of suitable user alerts based on the estimated risk are described. With user permission, wearable devices such as AR headsets are utilized to determine a state of health of a user’s hands based on user activities and the user’s interactions with their environment. Actions such as hand washing, disinfecting, cleansing, etc. are identified. Machine learning models are utilized to identify the user practices based on observed user behavior. Protective hand wear use is identified, and surfaces, objects, and/or people touched by a user during the course of the user’s activities are monitored. A hand contamination index for the user is generated based on monitored parameters. Based on the determined hand contamination index and an analysis of a user’s potential activity, suitable alerts are generated and provided to the user
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