skip to main content
10.1145/1160633.1160930acmconferencesArticle/Chapter ViewAbstractPublication PagesaamasConference Proceedingsconference-collections
Article

Implantable medical devices as agents and part of multiagent systems

Published:08 May 2006Publication History

ABSTRACT

The consideration of medical implants as an increasingly important population of isolated agents is a valuable perspective that should not be ignored by the agent community. Implanted Medical Device (IMD) applications are complex, naturally distributed, and could benefit from such attention. This paper explores implantable medical devices and their attributes in an agent context and terminology. It submits that an increasing body of IMDs should be considered agents and that there are opportunities for incorporating these implantable agents into multiagent systems (MAS). This will include: (i) Discussion of several IMDs in traditional agent terms. (ii) Discussion of trends and issues in IMDs related to their potential role in MAS. (iii) Experimental exploration of some potential MAS applications in the problem of medical monitoring. (iv) Broader discussion of the value of framing IMDs and applications involving them in the agent paradigm.

References

  1. M. A. Arent and I. A. Sun Microsystems. EP1022035A1: Communication network and devices to be implanted within a subject.Google ScholarGoogle Scholar
  2. T. Bachmor, J. Schochlin, and A. Bolz. Transmitting patient and device data via gsm - central management for decentral mobile medical devices. Biomedizinische Technik. Biomedical Engineering, 47(1):346--349, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  3. A. F. DiMarco. Restoration of respiratory muscle function following spinal cord injury. Review of electrical and magnetic stimulation techniques. Respir Physiol Neurobiol, 147(2--3):273--287, Jul 2005.Google ScholarGoogle Scholar
  4. T. Drew and M. Gini. Implantable Medical Devices as Agents and Part of MAS. November 2005.Google ScholarGoogle Scholar
  5. L. Fauchier, N. Sadoul, C. Kouakam, F. Briand, M. Chauvin, D. Babuty, and J. Clementy. Potential cost savings by telemedicine-assisted long-term care of implantable cardioverter defibrillator recipients. PACE, 28(2):S255--S259, January 2005.Google ScholarGoogle ScholarCross RefCross Ref
  6. G. Flammia. The Web: A communication medium for healthcare. IEEE Intelligent Systems, 17(2):88--89, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. H. D. Funke and I. A. Medtronic. Patent: US4987897: Body bus medical device communication system.Google ScholarGoogle Scholar
  8. S. D. Harpstead, L. M. Otten, T. R. Prentice, and I. A. Medtronic. Patent: US5697951: Implantable stimulation and drug infusion techniques.Google ScholarGoogle Scholar
  9. J. Huang, N. R. Jennings, and J. Fox. An agent architecture for distributed medical care. In ECAI-94: Proceedings of the Workshop on Agent Theories, Architectures, and Languages on Intelligent Agents, pages 219--232, New York, NY, USA, 1995. Springer-Verlag New York, Inc. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. V. Koutkias, I. Chouvarda, and N. Maglaveras. Multi-agent system architecture for heart failure management in a home care environment. IEEE Computers in Cardiology, 30(3):383--386, 2003.Google ScholarGoogle Scholar
  11. B. Larsson, H. Elmqvist, L. Ryden, and H. Schuller. Lessons from the first patient with an implanted pacemaker: 1958--2001. Pacing Clin Electrophysiol, 26(1 Pt 1):114--124, Jan 2003.Google ScholarGoogle Scholar
  12. R. P. Lesser, W. R. S. Webber, Y. Motamedi, Gholam K. and Mizuno-Matsumoto, and T. J. H. U. (Asignee). Patent: US20050149123A1: Techniques using heat flow management, stimulation, and signal analysis to treat medical disorders.Google ScholarGoogle Scholar
  13. S. P. Levine, J. E. Huggins, S. L. BeMent, R. K. Kushwaha, L. A. Schuh, E. A. Passaro, M. M. Rohde, and D. A. Ross. Identification of electrocorticogram patterns as the basis for a direct brain interface. J Clin Neurophysiol, 16(5):439--447, Sep 1999.Google ScholarGoogle ScholarCross RefCross Ref
  14. C. Lewis. Emerging Trends in Medical Device Technology: Home Is Where the Heart Monitor Is. FDA Consumer, May 2001.Google ScholarGoogle ScholarCross RefCross Ref
  15. N. Maglaveras, G. Gogou, I. Chouvarda, V. Koutakias, I. Lekka, D. Adamidas, C. Karvounis, G. Louridas, and E. Balas. Using contact centers in tele-management and home care of congestive heart failure patients: The CHS experience. IEEE Computers in Cardiology, 29(02):281--284, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  16. I. Medtronic. Carmel Biosensors Collaborates With Medtronic In Research And Development Of Innovative Biosensors. {Online; accessed 07-Nov-2005}.Google ScholarGoogle Scholar
  17. I. Medtronic. Medtronic Initiates "Concerto AT" Study In United States. {Online; accessed 01-February-2006}.Google ScholarGoogle Scholar
  18. I. NeuroPace. Implantation and testing of responsive neurostimulator (RNS) system for epilepsy. Annual Meeting of the American Society for Stereotactic and Functional Neurosurgery, May 2003. {Online; accessed 07-November-2005}.Google ScholarGoogle Scholar
  19. Z. Obrenovic, D. Starcevic, E. Jovanov, and V. Radivojevic. An agent based framework for virtual medical devices. In AAMAS '02: Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems, pages 659--660, New York, NY, USA, 2002. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. A. Ohlsson, S. H. Kubo, D. Steinhaus, D. T. Connelly, S. Adler, C. Bitkover, R. Nordlander, L. Ryden, and T. Bennett. Continuous ambulatory monitoring of absolute right ventricular pressure and mixed venous oxygen saturation in patients with heart failure using an implantable haemodynamic monitor: results of a 1 year multicentre feasibility study. European Heart Journal, 22(11):942--954, June 2001. Clinical Trial.Google ScholarGoogle ScholarCross RefCross Ref
  21. M. E. Pollack. Intelligent Technology for an Aging Population: The Use of AI to Assist Elders with Cognitive Impairment. AI Magazine, 2005.Google ScholarGoogle Scholar
  22. E. K. Ritzl, E. H. Kossoff, G. K. Bergey, P. S. Coe, and D. S. Gupta. Complementing the responsive neurostimulator system with a patient operated data transmitter on demand monitoring in the outpatient environment, 2005. {Abstract; accessed 11-Nov-2005}.Google ScholarGoogle Scholar
  23. S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Pearson Education, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. M. H. Schoenfeld, S. J. Compton, R. H. Mead, D. N. Weiss, L. Sherfesee, J. Englund, and L. R. Mongeon. Remote monitoring of implantable cardioverter defibrillators: A prospective analysis. PACE, 27(1):757--763, June 2002.Google ScholarGoogle Scholar
  25. J. Van. Remotes keep tab on heart devices: Wireless tracking offers piece of mind. Chicago Tribune, November 2005.Google ScholarGoogle Scholar
  26. P. Walter. {Electronic visual prostheses}. Klin Monatsbl Augenheilkd, 222(6):471--479, Jun 2005.Google ScholarGoogle ScholarCross RefCross Ref

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Conferences
    AAMAS '06: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
    May 2006
    1631 pages
    ISBN:1595933034
    DOI:10.1145/1160633

    Copyright © 2006 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 8 May 2006

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • Article

    Acceptance Rates

    Overall Acceptance Rate1,155of5,036submissions,23%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader