PERVASIVEHEALTH 2010
AGEmap 2010PH-Home 2010PervaSense 2010UCD-PHA 2010

    PERVASIVEHEALTH

    4th International ICST Conference on Pervasive Computing Technologies for Healthcare

    Pervasive healthcare is an emerging research discipline, focusing on the development and application of pervasive and ubiquitous computing technology for healthcare and wellness. Pervasive healthcare seeks to respond to a variety of pressures on healthcare systems, including the increased incidence…

    Pervasive healthcare is an emerging research discipline, focusing on the development and application of pervasive and ubiquitous computing technology for healthcare and wellness. Pervasive healthcare seeks to respond to a variety of pressures on healthcare systems, including the increased incidence of life-style related and chronic diseases, emerging consumerism in healthcare, need for empowering patients and relatives for self-care and management of their health, and need to provide seamless access for health care services, independent of time and place. Pervasive healthcare may be defined from two perspectives. First, it is the development and application of pervasive computing (or ubiquitous computing, ambient intelligence) technologies for healthcare, health and wellness management. Second, it seeks to make healthcare available to anyone, anytime, and anywhere by removing locational, time and other restraints while increasing both the coverage and quality of healthcare. The Pervasive Healthcare conference aims to gather together technology experts, practitioners, industry and national authorities contributing towards the development and application of human-centered pervasive and ubiquitous computing technology for healthcare and wellness.

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    Editor(s): Heinz Gerhauser, Katie Siek, Joachim Hornegger and Tim Christian Lueth
    Publisher
    IEEE
    ISBN
    978-963-9799-89-9
    Conference dates
    22nd–25th Mar 2010
    Location
    Munchen, Germany
    Appeared in EUDL
    7th Jun 2010
    Appears in
    IEEEXplore

    Copyright © 2010–2012 ICST

    • Toward free-living walking speed estimation using Gaussian Process-based Regression with on-body accelerometers and gyroscopes

      Research Article in 4th International ICST Conference on Pervasive Computing Technologies for Healthcare

      Harshvardhan Vathsangam, Adar Emken, Donna Spruijt-Metz, Gaurav S. Sukhatme

      Abstract
      Walking speed is an important determinant of energy expenditure. We present the use of Gaussian Process-based Regression (GPR), a non-linear, non-parametric regression framework to estimate walking s…Walking speed is an important determinant of energy expenditure. We present the use of Gaussian Process-based Regression (GPR), a non-linear, non-parametric regression framework to estimate walking speed using data obtained from a single on-body sensor worn on the right hip. We compare the performance of GPR with Bayesian Linear Regression (BLR) and Least Squares Regression (LSR) in estimating treadmill walking speeds. We also examine whether using gyroscopes to augment accelerometry data can improve prediction accuracy. GPR shows a lower average RMS prediction error when compared to BLR and LSR across all subjects. Per subject, GPR has significantly lower RMS prediction error than LSR and BLR (p <; 0.05) with increasing training data. The addition of tri-axial gyroscopes as inputs reduces RMS prediction error (p <; 0.05 per subject) when compared to using only acclerometers. We also study the effect of using treadmill walking data to predict overground walking speeds and that of combining data from more than one person to predict overground walking speed. A strong linear correlation exists (rX,Y = .8861) between overground walking speeds predicted from treadmill data and ground truth walking speed measured. Combining treadmill data from multiple subjects with similar height characteristics improved the prediction capability of GPR for overground walking speeds as measured by correllation between ground truth and GP-predicted values (rX,Y = .8204 with combined data).
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    • User-friendly system for recognition of activities with an accelerometer

      Research Article in 4th International ICST Conference on Pervasive Computing Technologies for Healthcare

      Gerd Krassnig, Daniel Tantinger, Christian Hofmann, Thomas Wittenberg, Matthias Struck

      Abstract
      Monitoring of a person's daily activities can provide valuable information for health care and prevention and can be an important supportive application in the field of ambient assisted living (AAL).…Monitoring of a person's daily activities can provide valuable information for health care and prevention and can be an important supportive application in the field of ambient assisted living (AAL). The goals of this study are the classification of postures and activities using knowledge-based methods as well as the evaluation of the performance of these methods. The acceleration data are gained by a single tri-axial accelerometer, which is mounted on a specific position on the test subject. A data set for training and testing was gained by collecting data from subjects, who performed varying postures and activities. For these purposes, three different knowledge-based (decision tree and neural network) classification methods and a hybrid classifier were implemented, tested and evaluated. The results of the tests illustrated that the hybrid classifier performed best with an overall accuracy of 98.99%. The advantages of knowledge-based methods are the exchangeable knowledge base, which can be developed for different types of sensor positions and the state of health of the subject.
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    • Comparison of accelerometer-based energy expenditure estimation algorithms

      Research Article in 4th International ICST Conference on Pervasive Computing Technologies for Healthcare

      Niall Twomey, Stephen Faul, William P. Marnane

      Abstract
      Many accelerometer-based energy expenditure estimation algorithms and platforms have been established in recent topical literature, and each boasts a high correlation against the gold standard in ene…Many accelerometer-based energy expenditure estimation algorithms and platforms have been established in recent topical literature, and each boasts a high correlation against the gold standard in energy expenditure measurement, i.e. indirect calorimetry. The aim of this study was to implement a set of these algorithms, run them all over a common dataset and investigate the strengths and weaknesses associated with each. The algorithms were then ported to a SHIMMER device for a real time, mobile and non-invasive energy expenditure estimation solution. High correlations were found between the accelerometer-regressed energy expenditure estimates and the reference dataset both on a computer and SHIMMER-implementation of the algorithms.
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    • Embedded assessment of aging adults: A concept validation with stakeholders

      Research Article in 4th International ICST Conference on Pervasive Computing Technologies for Healthcare

      Matthew L. Lee, Anind K. Dey

      Abstract
      Sensing systems embedded in the homes of elders have the potential to monitor individuals for early signs of functional and cognitive decline. However, it is not clear how the data collected from the…Sensing systems embedded in the homes of elders have the potential to monitor individuals for early signs of functional and cognitive decline. However, it is not clear how the data collected from these embedded assessment systems can be useful for elders to support awareness and for their doctors to make better diagnoses. We conduct a concept validation of embedded assessment sensing concepts with elders, family caregivers, and clinicians. We describe their reactions to the sensing concepts, their different information needs, how they would use the information, and what limits its usefulness and provide recommendations for designers of embedded assessment systems.
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    • Acceptance and use of a social robot by elderly users in a domestic environment

      Research Article in 4th International ICST Conference on Pervasive Computing Technologies for Healthcare

      Tineke Klamer, Somaya Ben Allouch

      Abstract
      The study presented in this article aims to improve our understanding of how people use zoomorphic robots in a health related setting in their domestic environments in general and, in particular, whe…The study presented in this article aims to improve our understanding of how people use zoomorphic robots in a health related setting in their domestic environments in general and, in particular, whether people are able to build (long- term) relationships with these robots. The influences of social and hedonic factors were examined, in addition to the normally studied utilitarian factors of the Technology Acceptance Model (TAM). Three elderly participants interacted with the Nabaztag, a zoomorphic robot, for 10 days to improve their overall health condition. Hedonic factors were not found to be important for the acceptance of the Nabaztag. However, these factors seemed to be important for building a relationship with the Nabaztag. Social factors were found to be important for the acceptance of robots, but not for building a relationship with the Nabaztag. The results yielded some interesting findings that need more study: (1) the relationship between the place of the Nabaztag and acceptance and use, (2) the relationship between naming the Nabaztag and building a relationship with it and (3) the relationship between using verbal/non-verbal communication and building a relationship with it.
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