Symposium on Computational Physiology
AAAI 2011 Spring Symposia (

March 21-23, 2011. Stanford University.

Computational Physiology – SECOND CALL FOR ABSTRACTS (Supplemental

* Abstracts submissions (200 - 400 Words): November 19, 2010.
* Notification of acceptance: December 10, 2010.
* Extended Abstract (2 Pages) or Short Paper (4 - 6 Pages) Due: January 21,

* Dave Andre - (Body Media)
* Jeff Ashe, (GE Research), Environmental sensing: non-contact vital signs.
* Matthew Goodwin - (MIT Media Lab, Director of Clinical Research |
Co-Director, Autism & Communication Technology)
* David Klonoff (Clinical Professor of Medicine, U.C. San Francisco,
Editor-in-Chief, Journal of Diabetes Science and Technology Medical *
Director, Diabetes Research Institute) Key Note Talk: Smart sensors for
Maintaining Homestasis.
Brent Ruby (University of Montana, Department of Health and Human
Performance) Wildland firefighters application area.
* Zeeshan Syed - (University of Michigan, Assistant Professor University of
Michigan, Department of Electrical Engineering and Computer Science)

Automated human health-state monitoring aims to identify when an individual
moves from a healthy to a compromised state. For example, changes in diet
or physical activity can lead to life-threatening hypo or hyperglycemia in
diabetics. Similarly, elderly individuals managing multiple chronic
conditions may experience rapid changes in physical and cognitive health
state that must be caught quickly for treatments to be most effective. Even
in healthy individuals, heavy exertion in extreme climates can quickly lead
to life threatening situations.

The emergence of inexpensive and unobtrusive health sensors promises to
shift the health care industry‘s focus from episodic care in acute
settings to early detection and longitudinal care for chronic conditions in
natural living environments. While these sensing systems are able to
provide a wealth of physiological information, the non-invasive
measurements are often quite different from the high-quality but limited
quantities of data used by physicians. As the availability of longitudinal
data increases, we have an unprecedented opportunity to discover new early
predictors of clinically significant events.

This symposium will bring together researchers from the fields of
artificial intelligence, machine learning, engineering, physiology, and
medicine for a set of talks and discussions aimed at bridging these
inter-disciplinary perspectives. Researchers in all fields related to
computational physiology are invited to submit extended abstracts (2 pages)
or short papers (4-6 pages) describing:

* New ambulatory and non-contact sensing technologies or novel applications
of existing sensors
* Specific difficulties associated with measuring human health states of
interest (e.g. internal body temperature, hydration, cognitive decline,
blood glucose level).
* Inference techniques that address the challenges of decision-making with
these data (e.g. continuous monitoring, multi-sensor fusion, movement
* Interfaces/Approaches for providing real-time advice to individuals
towards preventing injury and maintaining health.

Reports on experimental results, descriptions of implemented systems, and
position papers are all welcome; papers will be chosen for either oral or
poster presentations.

Extended Abstracts and Short Papers should be in AAAI format
[]. Please e-mail
submissions to

* Mark Buller, (Brown University,
* Paul Cuddihy (GE Research,
* Finale Doshi-Velez (Massachusetts Institute of Technology,