Sensor networks for medical care

By Victor Shnayder, Bor-rong Chen, Konrad Lorincz, Thaddeus R. F. Fulford Jones, Matt Welsh. ACM International Conference on Embedded Networked Sensor Systems, 2005

796 citations recorded by the source corpus.

Sensor networks have the potential to greatly impact many aspects of medical care. By outfitting patients with wireless, wearable vital sign sensors, collecting detailed real-time data on physiological status can be greatly simplified. However, there is a significant gap between existing sensor network systems and the needs of medical care. In particular, medical sensor networks must support multicast routing topologies, node mobility, a wide range of data rates and high degrees of reliability, and security. This paper describes our experiences with developing a combined hardware and software platform for medical sensor networks, called CodeBlue. CodeBlue provides protocols for device discovery and publish/subscribe multihop routing, as well as a simple query interface that is tailored for medical monitoring. We have developed several medical sensors based on the popular MicaZ and Telos mote designs, including a pulse oximeter, EKG and motion-activity sensor. We also describe a new, miniaturized sensor mote designed for medical use. We present initial results for the CodeBlue prototype demonstrating the integration of our medical sensors with the publish/subscribe routing substrate. We have experimentally validated the prototype on our 30-node sensor network testbed, demonstrating its scalability and robustness as the number of simultaneous queries, data rates, and transmitting sensors are varied. We also study the effect of node mobility, fairness across multiple simultaneous paths, and patterns of packet loss, confirming the system’s ability to maintain stable routes despite variations in node location and

Subfields: Biomedical Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/86485c12cc98a7f1adbac4032211c6d18c8c75e3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

  1. Dina Katabi
  2. Victor C. M. Leung
  3. Diane Joyce Cook
  4. Nikolaos G. Bourbakis
  5. Parisa Rashidi
  6. Giovanni Acampora
  7. Athanasios V. Vasilakos
  8. Alexandros Pantelopoulos

In Computer Networks and Communications

  1. Dina Katabi
  2. Athanasios V. Vasilakos
  3. Benjamin Ransford
  4. Shyamnath Gollakota
  5. Victor C. M. Leung
  6. Min Chen
  7. Kevin Fu
  8. Diane Joyce Cook

In Computer Vision and Pattern Recognition

  1. Diane Joyce Cook
  2. Parisa Rashidi
  3. Victor C. M. Leung
  4. Min Chen
  5. Kevin Fu
  6. Nikolaos G. Bourbakis
  7. Giovanni Acampora
  8. Athanasios V. Vasilakos

Citations in the corpus