Integrated Home Monitoring and Compliance Optimization for Patients with Mechanical Circulatory Support Devices

  • Lars Klack
  • Thomas Schmitz-Rode
  • Wiktoria Wilkowska
  • Kai Kasugai
  • Felix Heidrich
  • Martina Ziefle
Article

Abstract

This article presents an integrated, automatic home-monitoring, and assist system for patients suffering from end-stage heart failure, particularly patients with implanted mechanical circulatory support devices, such as ventricular assist devices and total artificial hearts. The system incorporates various biosensors to monitor the vital parameters of the patient unobtrusively in the home environment. Recorded data can be accessed online and in real time by a supervising physician, and these data serve as a means for immediate diagnosis of emergency events. The retrieved information can also be continuously analyzed to generate suggestions for medication, nutrition, and exercise for the patient to optimize their rehabilitation and overall health. An experimental environment (the Future Care Lab) was set up at RWTH Aachen University to serve as a testing environment for the development and evaluation of this novel integrated system. The Future Care Lab was not only used as a platform for technically testing the monitoring system, but also more concretely demonstrating to users the integration of these new medical technologies in a home. Thus, the Future Care Lab provides a unique environment for an interdisciplinary research approach consisting of iterative cycles of system development and evaluation of user acceptance.

Keywords

MCSD Heart failure Aftercare Biosensors 

References

  1. 1.
    Alagöz, F., et al. Technik ohne Herz? Nutzungsmotive und Akzeptanzbarrieren medizintechnischer Systeme aus Sicht von Kunstherzpatienten. Ambient Assisted Living 2010. Berlin: VDE Verlag, 2010.Google Scholar
  2. 2.
    Arning, K., et al. Same same but different. In: How Service Contexts of Mobile Technologies Shape Usage Motives and Barriers. HCI in Work and Learning, Life and Leisure. 6389/2010, 2010, pp. 34–54.Google Scholar
  3. 3.
    Beul, S., et al. Users’ preferences for telemedical consultations. Comparing users’ attitude towards different media in technology-mediated doctor–patient-communication. In: Proceedings of the 2nd International Workshop on User-Centred-Design of Pervasive Health Applications. IEEE Xplore Digital Library, 2011.Google Scholar
  4. 4.
    Brooke, J. SUS: a quick and dirty usability scale. In: Usability Evaluation in Industry, edited by P. W. Jordan, B. Thomas, B. A. Weerdmeester, and I. L. McClelland. London: Taylor and Francis, 1996.Google Scholar
  5. 5.
    Comas-Herrera, A., et al. Cognitive impairment in older people: future demand for long-term care services and the associated costs. Int. J. Geriatr. Psychiatry 22(10):1037–1045, 2007.PubMedCrossRefGoogle Scholar
  6. 6.
    Costa-Font, J., et al. Projecting long-term care expenditure in four European Union member states: the influence of demographic scenarios. Soc. Indic. Res. 86(2):303–321, 2007.CrossRefGoogle Scholar
  7. 7.
    Cvrcek, D., et al. A study on the value of location privacy. In: Proceedings of the 5th ACM Workshop on Privacy in Electronic Society, ACM, Alexandria, Virginia, USA, 2006, pp. 109–118.Google Scholar
  8. 8.
    Holman, W. L., et al. Device related infections: are we making progress? J. Card. Surg. 25(4):478–483, 2010.PubMedCrossRefGoogle Scholar
  9. 9.
    Kasugai, K., et al. Creating spatio-temporal contiguities between real and virtual rooms in an assistive living environment. In: Proceedings of Create 10. Electronic Workshops in Computing (eWic), Loughborough, UK, 2010, pp. 62–67.Google Scholar
  10. 10.
    Klack, L., et al. Future care floor: a sensitive floor for movement monitoring and fall detection in home environments. In: Wireless Mobile Communication and Healthcare, edited by J. C. Lin, and K. S. Nikita. Berlin: Springer, 2011, pp. 211–218.CrossRefGoogle Scholar
  11. 11.
    Lewis, J. R., and J. Sauro. The factor structure of the system usability scale. In: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009. Springer, San Diego, CA, 2009, pp. 94–103.Google Scholar
  12. 12.
    Mandl, K. D., et al. Electronic patient–physician communication: problems and promise. Ann. Intern. Med. 129(6):495–500, 1998.PubMedGoogle Scholar
  13. 13.
    Patel, C. B., et al. Mechanical circulatory support for advanced heart failure. Curr. Treat. Options Cardiovasc. Med. 12(6):549–565, 2010.PubMedCrossRefGoogle Scholar
  14. 14.
    Penninx, B. W. J. H., et al. Social network, social support, and loneliness in older persons with different chronic diseases. J. Aging Health 11(2):151–168, 1999.PubMedCrossRefGoogle Scholar
  15. 15.
    Raymond, A. L., et al. Obesity and left ventricular assist device driveline exit site infection. ASAIO J. 56(1):57–60, 2010.PubMedCrossRefGoogle Scholar
  16. 16.
    Rosenblatt, R. A., et al. Shortages of medical personnel at community health centers: implications for planned expansion. JAMA 295(9):1042–1049, 2006.PubMedCrossRefGoogle Scholar
  17. 17.
    Suh, M.-k., et al.: WANDA B: weight and activity with blood pressure monitoring system for heart failure patients. In: 2010 IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks (WoWMoM), 2010, pp. 1–6.Google Scholar
  18. 18.
    Tam, T., et al. Perception of eye contact in video teleconsultation. J. Telemed. Telecare 13(1):35–39, 2007.PubMedCrossRefGoogle Scholar
  19. 19.
    Tigges-Limmer, K., et al. Suicide after ventricular assist device implantation. J. Heart Lung Transplant. 29(6):692–694, 2010.PubMedCrossRefGoogle Scholar
  20. 20.
    Wenger, G. C., et al. Social isolation and loneliness in old age: review and model refinement. Ageing Soc. 16(3):333–358, 1996.CrossRefGoogle Scholar
  21. 21.
    Wilkowska, W., and M. Ziefle. Perception of privacy and security for acceptance of E-health technologies: exploratory analysis for diverse user groups. In: Proceedings of the 2nd International Workshop on User-Centred-Design of Pervasive Health Applications. IEEE Xplore Digital Library, 2011.Google Scholar
  22. 22.
    Winkler, S., et al. A new telemonitoring system intended for chronic heart failure patients using mobile telephone technology—feasibility study. Int. J. Cardiol., 2010. ISSN 0167-5273, doi:10.1016/j.ijcard.2010.08.038, http://www.sciencedirect.com/science/article/pii/S0167527310006285.
  23. 23.
    Wolf, P., et al. SOPRANO—an extensible, open AAL platform for elderly people based on semantical contracts. In: 3rd Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI’08), 18th European Conference on Artificial Intelligence (ECAI 08), Patras, Greece, 2008.Google Scholar
  24. 24.
    Woolham, J., and B. Frisby. Building a local infrastructure that supports the use of assistive technology in the care of people with dementia. Res. Policy Plan. 20(1):11–24, 2002.Google Scholar
  25. 25.
    Ziefle, M., and W. Wilkowska. Technology acceptability for medical assistance. In: 4th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 1–9, 2010.Google Scholar

Copyright information

© Biomedical Engineering Society 2011

Authors and Affiliations

  • Lars Klack
    • 1
  • Thomas Schmitz-Rode
    • 1
  • Wiktoria Wilkowska
    • 1
  • Kai Kasugai
    • 1
  • Felix Heidrich
    • 1
  • Martina Ziefle
    • 1
  1. 1.Communication Science, Human Technology CentreRWTH Aachen UniversityAachenGermany

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