309
Views
26
CrossRef citations to date
0
Altmetric
Articles

Monitoring systems for the support of home care

, , , , , , , , , , & show all
Pages 157-176 | Published online: 06 Dec 2010

References

  • Charness N, Schaie KW. Impact of technology on successful aging. Springer PublishingNew York2003.
  • Courtney K, Demiris G, Rantz M, Skubic M. Needing smart home technologies: the perspective of older adults in continuing care retirement communities. Informatics in Primary Care 2008;16:195–201.
  • Orre CJ. Using technologies with care. Notes on technology assimilation processes in home care. [dissertation]. Sweden: Umeå University; 2009.
  • Wälivaara B-M. Mobile distance-spanning technology in home care. Views and reasoning among persons in need of health care and general practitioners. [dissertation] Sweden: Luleå University of Technology; 2009.
  • Levett-Jones T, Kenny R, Van der Riet P, Hazelton M, Kable A, Bourgeois S, Luxford Y. Exploring the information and communication technology competence and confidence of nursing students and their perception of its relevance to clinical practice. Nurse Education Today 2009;29:612–616.
  • Staggers N, Gassert C, Curran C. A delphi study to determine inforamtic competencies for nurses at four levels of practice. Nursing Research 2002;51:383–390.
  • Mahoney FI, Barthel D. Functional evaluation: the Barthel Index. Maryland State Medical Journal 1965;14:56–61.
  • Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist 1969;9:179–186.
  • Morris JN, Murphy K, Nonemaker S. Long term care resident assessment instrument user's maunal. Version 2.0, 1995.
  • Sidenvall B, Nydahl M, Fjellström C. The meal as a gift- the meaning of cooking among retired women. The Journal of Applied Gerontology 2000;19:405–423.
  • Warde A. Consumption, food and taste. Culinary antinomies and commodity culture. London: Sage Publications; 1997.
  • Quandt SA, Vitolins MZ, De Walt KM, Roos GM. Meal patterns of older adults in rural communities: life course analysis and implications for undernutrition. Journal of Applied Gerontology 1997;16:152–171.
  • Söderhamn O. Potential for self-care. Assessing and describing self-care ability among elderly people. [dissertation]. LinköpingLinköping University Medical1998.
  • Monekosso DN, Remagnino P. Monitoring behavior with an array of sensors. Computational Intelligence 2007;23:420–438.
  • Barger TS, Brown DE, Alwan M. Health-status monitoring through analysis of behavioral patterns. IEEE Transactions on Systems, Man and Cybernetics, Part A 2005;35:22–27.
  • van Kasteren T; Noulas A, Englebienne G, Kröse B. Accurate activity recognition in a home setting. In Proceedings of the 10th International Conference on Ubiquitous Computing, Seoul, Korea, 2008, pp 1–9.
  • Philipose M, Fishkin KP, Perkowitz M, Patterson DJ, Fox D, Kautz H, Hahnel D. Inferring activities from interactions with objects. Pervasive Computing IEEE 2004;3:50–57.
  • Quinn EL. Smart metering and privacy: existing laws and competing policies. SSRN eLibrary; 2009.
  • Hart GW. Nonintrusive appliance load monitoring. Proceedings of the IEEE 1992;80:1870–1891.
  • Mueller W. Überwachung elektrischer Hausgeräte durch Leistungsanalyse (Monitoring of electrical home appliances by load analysis). Pflaum; 2002.
  • Patel S, Robertson T, Kientz J, Reynolds M, Abowd G. At the flick of a switch: detecting and classifying unique electrical events on the residential power line (Nominated for the best paper award). In UbiComp 2007: Ubiquitous Computing. 2007, pp 271–288.
  • Prudenzi A. A neuron nets based procedure for identifying domestic appliances pattern-of-use from energy recordings at meter panel. Power Engineering Society Winter Meeting 2002;2:941–946.
  • Moeslund TB, Granum E. A survey of computer vision-based human motion capture. Computer Vision and Image Understanding 2001;81:231–268.
  • Moeslund TB, Hilton A, Krueger V. A survey of advances in vision-based human motion capture and analysis. Computer Vision and Image Understanding 2006;104:90–126.
  • Efros AA, Berg AC, Mori G, Malik J. Recognizing action at a distance. IEEE International Conf. on Computer Vision, Nice, France2003. pp 726–733.
  • Laptev I, Lindeberg T. Space-time interest points. Proceedings of the IEEE International Conference on Computer Vision, 2003, pp 432–439.
  • Marszałek M, Laptev I and Schmid C. Actions in Context. In Proceedings of CVPR′09, Miami, US, 2009.
  • Dollar P, Rabaud V, Cottrell G, Belongie S. Behavior recognition via sparse spatiotemporal features, 2nd Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, 2005, pp 65–72.
  • Chung P, Liu C. A daily behavior enabled hidden Markov model for human behavior understanding. Pattern Recognition 2008;41:1589–1597.
  • Wang X, Ma X and Grimson W. Unsupervised activity perception in crowded and complicated scenes using hierarchical bayesian models. IEEE Transactions on Pattern Analytical and Machine Intelligence 2009;31:539–555.
  • Saponas T, Lester J, Froehlich J, Fogarty J, Landay J. iLearn on the iPhone. Real-time human activity classification on commodity mobile phones. University of Washington CSE Tech Report UW-CSE-08-04-02; 2008.
  • Huynh T, Blanke U, Schiele B. Scalable recognition of daily activities with wearable sensors. In 3rd International Workshop on Location and Context Awareness, 2007. pp 50–67.
  • Roy S, Cheng M, Chang S, Moore J, De Luca G, Nawab S, De Luca C. A combined sEMG and accelerometer system for monitoring functional activity in stroke. IEEE Transactions of Neural Systems and Rehabilitation Engineering 2009;17:585–594.
  • Lester J, Choudhury T, Borriello G: A Practical Approach to Recognizing Physical Activities. In: Pervasive Computing, LNCS Vol. 3968, 2006;1–16.
  • Ermes M, Pärkka J, Mantyjarvi J, Korhonen I. Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions. IEEE Transactions of Information Technology and Biomedicine 2008;12:20–26.
  • Sutton C, McCallum A. Collective segmentation and labelling of distant entities in information extraction. Technical Report TR04-49, University of Massachusetts, Amherst, 2004.
  • Hu DH, Yang Q. CIGAR: concurrent and interleaving goal and activity recognition. AAAI 2008;1363–1368.
  • Huynh T, Fritz M, Schiele B. Discovery of activity patterns using topic models. In Proceedings of the 10th International Conference on Ubiquitous Computing, New York, NY, USAACM2008, pp 10–19.
  • Krueger RA, Casey MA. Focus groups: a practical guide for applied research. Thousand Oaks, CASage Publications2009.
  • Barbour R, Kitzinger J, editors. Developing focus group – politics, theory and practice. Sage PublicationsLondon1999.
  • Robinson N. The use of focus group methodology – with selected examples from sexual health research. Journal of Advanced Nursing 1999;29:905–913.
  • Kitzinger J. Introducing focus groups. British Medical Journal 1995;311:299–302.
  • Carey AM: The group effect in focus groups: planning, implementing, and interpreting focus groups research. In: Critical issues in qualitative research methods. Morse JM, editor. Thousand Oaks: Sage Publication; 1994. Chapter 12.
  • Meis M, Hülsken-Giesler M, Gövercin M, Költzsch Y, Hein A, Marschollek M, Steinhagen-Thiessen E, Remmers H. Nutzerzentrierte Konzeptentwicklung bei assistiven Technologien für pflegebedürftige und sturzgefährdete Patienten (User-centred development of concepts for assistance systems for people who need health care or with a high risk of falls).Jöckel K-H, editors. 54.GMDS-Jahrestagung. Abstractband/Tagungsband der 54. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS) e.V. 2009.
  • Hülsken-Giesler M, Meis M, Gövercin M, Költzsch Y, Hein A, Marschollek M, Remmers H. Bedarfserhebung zur Entwicklung assistiver Technologien für pflegebedürftige und sturzgefährdete Patienten – pflegewissenschaftliche Implikationen (Requirement analysis for the development of assistance systems for people who need health care or with a high risk of falls). Tagungsband des 3. Deutschen AAL-Kongresses 2010, Paper 16.5. VDE: Berlin, Offenbach; 2010.
  • Remmers H, Hülsken-Giesler M. E-health technologies in home care nursing: recent survey results and subsequent ethical issues. Human-centered design of e-health technologies. Concepts, methods and applications. In: Ziefle M, Röcker C, editors. Hersehy, PA: IGI Global; 2010.
  • Hall MA. Correlation-based feature selection for machine learning. PhD-thesis. University of Waikato: Hamilton, New Zealand; 1999.
  • Witten IH, Frank E. Data mining: practical machine learning tools and techniques. 2nd ed. San Francisco: Morgan Kaufmann; 2005.
  • Shimmer Research [Internet]. Dublin, IrelandShimmer Research Available from: http://www.shimmer-research.com (accessed 20 May 2010).
  • Wilken O, Hülsmann N, Hein A. Bestimmung von Verhaltensmustern basierend auf der Nutzung elektrischer Geräte (Determination of behaviour patterns based on the usage of electrical devices). 2. Deutscher AAL-Kongress, Berlin, Germany, 27.-28.01.2009, pp 116–120.
  • Wilken O, Hülsken-Giesler M, Remmers H, Martens B, Hein A. Aktivitätsbestimmung und Datenerhebung von älteren Menschen basierend auf der Nutzung elektrischer Geräte (Activity detection and monitoring of older people based on the usage of electrical devices). Tagungsband zur GI-Jahrestagung 2009, Seite 73 und 899 –909.
  • Zach C, Pock T, Bischof H. A duality based approach for realtime tv-l1 optical flow. In ‘Pattern Recognition (Proc. DAGM) 2007’, Heidelberg, Germanypp 214–223.
  • Nock, R, Nielsen, F. Statistical region merging. IEEE Transactions on Pattern Analytics and Machine Intelligence 2004;26:1452–1458.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.